diff --git a/.github/workflows/save-BEA-data.yaml b/.github/workflows/save-BEA-data.yaml index 2313947f..e4cbec19 100644 --- a/.github/workflows/save-BEA-data.yaml +++ b/.github/workflows/save-BEA-data.yaml @@ -34,8 +34,6 @@ jobs: http-user-agent: ${{ matrix.config.http-user-agent }} use-public-rspm: true - - uses: r-lib/actions/setup-renv@v2 - - uses: r-lib/actions/setup-r-dependencies@v2 with: extra-packages: devtools diff --git a/.github/workflows/save-annual-BEA-data.yaml b/.github/workflows/save-annual-BEA-data.yaml index 64cc0b6c..361871da 100644 --- a/.github/workflows/save-annual-BEA-data.yaml +++ b/.github/workflows/save-annual-BEA-data.yaml @@ -34,8 +34,6 @@ jobs: http-user-agent: ${{ matrix.config.http-user-agent }} use-public-rspm: true - - uses: r-lib/actions/setup-renv@v2 - - uses: r-lib/actions/setup-r-dependencies@v2 with: extra-packages: devtools diff --git a/R/AdjustPrice.R b/R/AdjustPrice.R index ce63830d..3170f08a 100644 --- a/R/AdjustPrice.R +++ b/R/AdjustPrice.R @@ -46,11 +46,12 @@ calculateProducerbyPurchaserPriceRatio <- function(model) { Margins <- Margins[match(rownames(model$Rho), Margins$Code_Loc), ] # Prepare ratio table PHI PHI <- model$Rho + schema <- getSchemaCode(model$specs) for (year in colnames(model$Rho)) { # Adjust ProducersValue from model$specs$IOyear to currency year using model$Rho ProducersValue <- Margins$ProducersValue * (Margins[, year]/Margins[, as.character(model$specs$IOYear)]) # Adjust Transportation, Wholesale and Retail using corresponding CPI_ratio - TWR_CPI <- useeior::Sector_CPI_IO[c("48TW", "42", "44RT"), ] + TWR_CPI <- get(paste0(na.omit(c('Sector_CPI_IO', schema)), collapse = "_"))[c("48TW", "42", "44RT"), ] TWR_CPI_ratio <- TWR_CPI[, year]/TWR_CPI[, as.character(model$specs$IOYear)] TWRValue <- sweep(Margins[, c("Transportation", "Wholesale", "Retail")], 2, TWR_CPI_ratio, "*") # Generate PRObyPURRatios, or phi vector diff --git a/R/CrosswalkFunctions.R b/R/CrosswalkFunctions.R index ba1dc079..a1403570 100644 --- a/R/CrosswalkFunctions.R +++ b/R/CrosswalkFunctions.R @@ -1,19 +1,11 @@ # Functions that use sector crosswalks -#' Function to externalize the BEA to NAICS crosswalk -#' @return A crosswalk linking 2007 and 2012 NAICS codes to 2012 Sector, Summary, and Detail BEA codes -loadMasterCrosswalk <- function(){ - # Pull the mastercrosswalk created in the data-raw subdirectory - BEAtoNAICSCrosswalk <- useeior::MasterCrosswalk2012 - return(BEAtoNAICSCrosswalk) -} - #' Determine allocation factors between NAICS and BEA sectors based on Industry output. #' @param model A complete EEIO model: a list with USEEIO model components and attributes. #' @param year Year of model Industry output. #' @return A table of allocation factors between NAICS and BEA sectors. getNAICStoBEAAllocation <- function (year, model) { - # Keep USEEIO and NAICS columns in MasterCrosswalk2012 table based on the model specs + # Keep USEEIO and NAICS columns in MasterCrosswalk table based on the model specs NAICStoBEA <- unique(model$crosswalk[, c("NAICS", "USEEIO")]) colnames(NAICStoBEA) <- c("NAICS_Code", "BEA_Code") # Drop 2-digit NAICS code @@ -41,26 +33,40 @@ getNAICStoBEAAllocation <- function (year, model) { return(AllocationTable) } - -#' Get 2-6 digit NAICS codes and names for year specified. -#' @param year int. 2012 or 2007 accepted. -#' @return dataframe with columns NAICS_year_Code and NAICS_year_Name. -getNAICS2to6DigitsCodeName <- function (year) { +#' Download NAICS file for 2-6 digit NAICS codes if not present. +#' @param year int, 2017, 2012, or 2007 accepted. +#' @return FileName str +downloadNAICS2to6DigitsFile <- function (year) { # Download 2-6 digits NAICS table - if (year == 2012) { - FileName <- "inst/extdata/2-digit_2012_Codes.xls" + dir <- file.path(rappdirs::user_data_dir(), "USEEIO-input") + if (year == 2017) { + FileName <- file.path(dir, "2-digit_2017_Codes.xlsx") + url <- "https://www.census.gov/naics/2017NAICS/2-6%20digit_2017_Codes.xlsx" + } else if (year == 2012) { + FileName <- file.path(dir, "2-digit_2012_Codes.xls") url <- "https://www.census.gov/eos/www/naics/2012NAICS/2-digit_2012_Codes.xls" - } else { - FileName <- "inst/extdata/naics07.xls" + } else if (year == 2007) { + FileName <- file.path(dir, "naics07.xls") url <- "https://www.census.gov/eos/www/naics/reference_files_tools/2007/naics07.xls" + } else { + stop('Specify available year for crosswalk') } if(!file.exists(FileName)) { utils::download.file(url, FileName, mode = "wb") } - + return(FileName) +} + + +#' Get 2-6 digit NAICS codes and names for year specified. +#' @param year int. 2017, 2012, or 2007 accepted. +#' @return dataframe with columns NAICS_year_Code and NAICS_year_Name. +getNAICS2to6DigitsCodeName <- function (year) { + FileName <- downloadNAICS2to6DigitsFile(year) # Load 2-6 digits NAICS table NAICS <- as.data.frame(readxl::read_excel(FileName, sheet = 1, col_names = TRUE))[-1,-1] colnames(NAICS) <- c("NAICS_Code", "NAICS_Name") + NAICS <- NAICS[c("NAICS_Code", "NAICS_Name")] # Avoid extra columns # Split the NAICS code with dash ("-) DashSplit <- do.call("rbind.data.frame", apply(do.call("rbind", strsplit(NAICS$NAICS_Code, "-")), 1, function(x) seq(x[1], x[2], 1))) @@ -80,24 +86,14 @@ getNAICS2to6DigitsCodeName <- function (year) { } #' Get 2-6 digit NAICS codes in a crosswalk format for year specified. -#' @param year int, 2012 or 2007 accepted. +#' @param year int, 2017, 2012 or 2007 accepted. #' @return data frame with columns NAICS_2, NAICS_3, NAICS_4, NAICS_5, NAICS_6. getNAICS2to6Digits <- function (year) { - # Download 2-6 digits NAICS table - if (year == 2012) { - FileName <- "inst/extdata/2-digit_2012_Codes.xls" - url <- "https://www.census.gov/eos/www/naics/2012NAICS/2-digit_2012_Codes.xls" - } else { - FileName <- "inst/extdata/naics07.xls" - url <- "https://www.census.gov/eos/www/naics/reference_files_tools/2007/naics07.xls" - } - if(!file.exists(FileName)) { - utils::download.file(url, FileName, mode = "wb") - } - + FileName <- downloadNAICS2to6DigitsFile(year) # Load 2-6 digits NAICS table NAICS <- as.data.frame(readxl::read_excel(FileName, sheet = 1, col_names = TRUE))[-1,-1] colnames(NAICS) <- c("NAICS_Code", "NAICS_Name") + NAICS <- NAICS[c("NAICS_Code", "NAICS_Name")] # Avoid extra columns NAICS$NAICS_Code <- suppressWarnings(as.integer(NAICS$NAICS_Code)) NAICS <- NAICS[!is.na(NAICS$NAICS_Code), ] # Reshape the table @@ -201,7 +197,7 @@ getNAICSCodeName <- function(year) { #' @return data frame with columns '2012 NAICS Code', '2012 NAICS Title', #' '2007 NAICS Code', and '2007 NAICS Title'. getNAICS2012to2007Concordances <- function() { - filename <- "inst/extdata/2012_to_2007_NAICS.xls" + filename <- file.path(rappdirs::user_data_dir(), "USEEIO-input", "2012_to_2007_NAICS.xls") if(!file.exists(filename)) { utils::download.file("https://www.census.gov/naics/concordances/2012_to_2007_NAICS.xls", filename, mode = "wb") @@ -215,9 +211,9 @@ getNAICS2012to2007Concordances <- function() { #' @return data frame with columns '2012 NAICS Code', '2012 NAICS Title', #' '2017 NAICS Code', and '2017 NAICS Title'. getNAICS2012to2017Concordances <- function() { - filename <- "inst/extdata/2012_to_2017_NAICS.xlsx" + filename <- file.path(rappdirs::user_data_dir(), "USEEIO-input", "2012_to_2017_NAICS.xlsx") if(!file.exists(filename)) { - utils::download.file("https://www.census.gov/naics/concordances/2012_to_2017_NAICS.xlsx", + utils::download.file("https://www.census.gov/naics/concordances/2012_to_2017_NAICS.xls", filename, mode = "wb") } df <- as.data.frame(readxl::read_excel(filename, sheet = 1, col_names = TRUE, skip = 2)) diff --git a/R/DataDocumentation.R b/R/DataDocumentation.R index 9bb71b1a..c3ed098e 100644 --- a/R/DataDocumentation.R +++ b/R/DataDocumentation.R @@ -285,263 +285,6 @@ #' @note Remove 'backslash' before 'percent sign' in url to access the source of data. "Summary_Use_2021_PRO_AfterRedef" -#' Sector 2010 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2010_BeforeRedef" - -#' Sector 2011 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2011_BeforeRedef" - -#' Sector 2012 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2012_BeforeRedef" - -#' Sector 2013 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2013_BeforeRedef" - -#' Sector 2014 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2014_BeforeRedef" - -#' Sector 2015 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2015_BeforeRedef" - -#' Sector 2016 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2016_BeforeRedef" - -#' Sector 2017 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2017_BeforeRedef" - -#' Sector 2018 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2018_BeforeRedef" - -#' Sector 2019 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Make_2019_BeforeRedef" - -#' Sector 2020 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Make_2020_BeforeRedef" - -#' Sector 2021 Make Before Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Make_2021_BeforeRedef" - -#' Sector 2010 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2010_PRO_BeforeRedef" - -#' Sector 2011 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2011_PRO_BeforeRedef" - -#' Sector 2012 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2012_PRO_BeforeRedef" - -#' Sector 2013 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2013_PRO_BeforeRedef" - -#' Sector 2014 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2014_PRO_BeforeRedef" - -#' Sector 2015 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2015_PRO_BeforeRedef" - -#' Sector 2016 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2016_PRO_BeforeRedef" - -#' Sector 2017 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2017_PRO_BeforeRedef" - -#' Sector 2018 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2018_PRO_BeforeRedef" - -#' Sector 2019 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Use_2019_PRO_BeforeRedef" - -#' Sector 2020 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Use_2020_PRO_BeforeRedef" - -#' Sector 2021 Use Producer's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Use_2021_PRO_BeforeRedef" - -#' Sector 2012 Use Purchaser's Value Before Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2012_PUR_BeforeRedef" - -#' Sector 2010 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2010_AfterRedef" - -#' Sector 2011 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2011_AfterRedef" - -#' Sector 2012 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2012_AfterRedef" - -#' Sector 2013 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2013_AfterRedef" - -#' Sector 2014 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2014_AfterRedef" - -#' Sector 2015 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2015_AfterRedef" - -#' Sector 2016 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2016_AfterRedef" - -#' Sector 2017 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2017_AfterRedef" - -#' Sector 2018 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Make_2018_AfterRedef" - -#' Sector 2019 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Make_2019_AfterRedef" - -#' Sector 2020 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Make_2020_AfterRedef" - -#' Sector 2021 Make After Redefinition (2012 schema) -#' @format A dataframe with 16 obs. and 18 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Make_2021_AfterRedef" - -#' Sector 2010 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2010_PRO_AfterRedef" - -#' Sector 2011 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2011_PRO_AfterRedef" - -#' Sector 2012 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2012_PRO_AfterRedef" - -#' Sector 2013 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2013_PRO_AfterRedef" - -#' Sector 2014 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2014_PRO_AfterRedef" - -#' Sector 2015 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2015_PRO_AfterRedef" - -#' Sector 2016 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2016_PRO_AfterRedef" - -#' Sector 2017 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2017_PRO_AfterRedef" - -#' Sector 2018 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -"Sector_Use_2018_PRO_AfterRedef" - -#' Sector 2019 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Use_2019_PRO_AfterRedef" - -#' Sector 2020 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Use_2020_PRO_AfterRedef" - -#' Sector 2021 Use Producer's Value After Redefinition (2012 schema) -#' @format A dataframe with 23 obs. and 24 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -#' @note Remove 'backslash' before 'percent sign' in url to access the source of data. -"Sector_Use_2021_PRO_AfterRedef" - #' Detail 2012 Import Before Redefinition (2012 schema) #' @format A dataframe with 405 obs. and 427 variables #' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_DET_2007_2012.xlsx} @@ -786,25 +529,35 @@ #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} "Summary_Supply_2016" -#' Summary 2017 Supply (2012 schema) +#' Summary 2017 Supply (2017 schema) +#' @format A dataframe with 74 obs. and 83 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +"Summary_Supply_2017_17sch" + +#' Summary 2018 Supply (2017 schema) #' @format A dataframe with 74 obs. and 83 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Supply_2017" +"Summary_Supply_2018_17sch" -#' Summary 2018 Supply (2012 schema) +#' Summary 2019 Supply (2017 schema) #' @format A dataframe with 74 obs. and 83 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Supply_2018" +"Summary_Supply_2019_17sch" -#' Summary 2019 Supply (2012 schema) +#' Summary 2020 Supply (2017 schema) #' @format A dataframe with 74 obs. and 83 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Supply_2019" +"Summary_Supply_2020_17sch" -#' Summary 2020 Supply (2012 schema) +#' Summary 2021 Supply (2017 schema) #' @format A dataframe with 74 obs. and 83 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Supply_2020" +"Summary_Supply_2021_17sch" + +#' Summary 2022 Supply (2017 schema) +#' @format A dataframe with 74 obs. and 83 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +"Summary_Supply_2022_17sch" #' Summary 2010 Use (2012 schema) #' @format A dataframe with 82 obs. and 92 variables @@ -841,132 +594,378 @@ #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} "Summary_Use_SUT_2016" -#' Summary 2017 Use (2012 schema) +#' Summary 2017 Use (2017 schema) #' @format A dataframe with 82 obs. and 92 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Use_SUT_2017" +"Summary_Use_SUT_2017_17sch" -#' Summary 2018 Use (2012 schema) +#' Summary 2018 Use (2017 schema) #' @format A dataframe with 82 obs. and 92 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Use_SUT_2018" +"Summary_Use_SUT_2018_17sch" -#' Summary 2019 Use (2012 schema) +#' Summary 2019 Use (2017 schema) #' @format A dataframe with 82 obs. and 92 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Use_SUT_2019" +"Summary_Use_SUT_2019_17sch" -#' Summary 2020 Use (2012 schema) +#' Summary 2020 Use (2017 schema) #' @format A dataframe with 82 obs. and 92 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Summary_Use_SUT_2020" +"Summary_Use_SUT_2020_17sch" -#' Sector 2010 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables +#' Summary 2021 Use (2017 schema) +#' @format A dataframe with 82 obs. and 92 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2010" +"Summary_Use_SUT_2021_17sch" -#' Sector 2011 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables +#' Summary 2022 Use (2017 schema) +#' @format A dataframe with 82 obs. and 92 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2011" +"Summary_Use_SUT_2022_17sch" -#' Sector 2012 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables +#' Detail 2017 Supply (2017 schema) +#' @format A dataframe with 403 obs. and 414 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2012" +"Detail_Supply_2017_17sch" -#' Sector 2013 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables +#' Detail 2017 Use (under the Supply-Use framework, 2017 schema) +#' @format A dataframe with 411 obs. and 423 variables #' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2013" +"Detail_Use_SUT_2017_17sch" -#' Sector 2014 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2014" +#' Master Crosswalk table (2017 schema) +#' @format A dataframe with 4095 obs. and 5 variables: +#' \describe{ +#' \item{BEA_2017_Sector_Code}{text code} +#' \item{BEA_2017_Summary_Code}{text code} +#' \item{BEA_2017_Detail_Code}{text code} +#' \item{NAICS_2017_Code}{text code} +#' \item{NAICS_2012_Code}{text code} +#' } +"MasterCrosswalk2017" -#' Sector 2015 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2015" +#' Master Crosswalk table (2017 schema) +#' @format A dataframe with 4095 obs. and 12 variables: +#' \describe{ +#' \item{BEA_2017_Sector_Code}{text code} +#' \item{BEA_2017_Sector_Name}{text code} +#' \item{BEA_2017_Summary_Code}{text code} +#' \item{BEA_2017_Summary_Name}{text code} +#' \item{BEA_2017_Detail_Code}{text code} +#' \item{BEA_2017_Detail_Name}{text code} +#' \item{USEEIO_Code}{text code} +#' \item{USEEIO_Name}{text code} +#' \item{NAICS_2017_Code}{text code} +#' \item{NAICS_2017_Name}{text code} +#' \item{NAICS_2012_Code}{text code} +#' \item{NAICS_2007_Code}{text code} +#' } +"MasterCrosswalk" -#' Sector 2016 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2016" -#' Sector 2017 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2017" +#' Detail 2017 Make Before Redefinition (2017 schema) +#' @format A dataframe with 403 obs. and 403 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_Make_2017_BeforeRedef_17sch" -#' Sector 2018 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2018" +#' Detail 2017 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 408 obs. and 425 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_Use_2017_PRO_BeforeRedef_17sch" -#' Sector 2019 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2019" +#' Detail 2017 Use Purchaser's Value Before Redefinition (2017 schema) +#' @format A dataframe with 400 obs. and 425 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_Use_2017_PUR_BeforeRedef_17sch" -#' Sector 2020 Supply (2012 schema) -#' @format A dataframe with 18 obs. and 27 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Supply_2020" +#' Detail 2017 Make After Redefinition (2017 schema) +#' @format A dataframe with 403 obs. and 403 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_Make_2017_AfterRedef_17sch" -#' Sector 2010 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2010" +#' Detail 2017 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 408 obs. and 425 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_Use_2017_PRO_AfterRedef_17sch" -#' Sector 2011 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2011" +#' Detail 2017 Use Purchaser's Value After Redefinition (2017 schema) +#' @format A dataframe with 400 obs. and 425 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_Use_2017_PUR_AfterRedef_17sch" -#' Sector 2012 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2012" +#' Detail Margins (Before Redef) table for 2017 (2017 schema) +#' @format A dataframe with 58051 obs. and 9 variables: +#' \describe{ +#' \item{NIPACode}{text code} +#' \item{MarginsCategory}{text category name, like 'Therapeutic medical equipment'} +#' \item{CommodityCode}{BEA_2017_Detail_Code} +#' \item{CommodityDescription}{BEA_2017_Detail_Name} +#' \item{ProducersValue}{USD2017} +#' \item{Transportation}{USD2017} +#' \item{Wholesale}{USD2017} +#' \item{Retail}{USD2017} +#' \item{PurchasersValue}{USD2017} +#' } +#' @source \url{https://apps.bea.gov/industry/xls/underlying-estimates/Margins_Before_Redefinitions_2017.xlsx} +"Detail_Margins_2017_BeforeRedef_17sch" + +#' Detail 2017 Import Before Redefinition (2017 schema) +#' @format A dataframe with 402 obs. and 424 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_DET_2017.xlsx} +"Detail_Import_2017_BeforeRedef_17sch" + +#' Detail 2017-2022 Gross Output (2017 schema) +#' @format A dataframe with 402 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Detail_GrossOutput_IO_17sch" + +#' Summary 2017-2022 Gross Output (2017 schema) +#' @format A dataframe with 71 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Summary_GrossOutput_IO_17sch" + +#' Sector 2017-2022 Gross Output (2017 schema) +#' @format A dataframe with 15 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Sector_GrossOutput_IO_17sch" + +#' Detail 2017-2022 CPI (2017 schema) +#' @format A dataframe with 402 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Detail_CPI_IO_17sch" + +#' Summary 2017-2022 CPI (2017 schema) +#' @format A dataframe with 71 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Summary_CPI_IO_17sch" + +#' Sector 2017-2022 CPI (2017 schema) +#' @format A dataframe with 15 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Sector_CPI_IO_17sch" + +#' Summary 2017-2022 Value Added (2017 schema) +#' @format A dataframe with 71 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Summary_ValueAdded_IO_17sch" + +#' Sector 2017-2022 Value Added (2017 schema) +#' @format A dataframe with 15 obs. and 6 variables +#' @source \url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +"Sector_ValueAdded_IO_17sch" + +#' Detail Industry Code and Name (2017 schema) +#' @format A dataframe with 402 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_IndustryCodeName_2017" -#' Sector 2013 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2013" +#' Detail Commodity Code and Name (2017 schema) +#' @format A dataframe with 402 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_CommodityCodeName_2017" -#' Sector 2014 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2014" +#' Detail Value Added Code and Name (2017 schema) +#' @format A dataframe with 3 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_ValueAddedCodeName_2017" -#' Sector 2015 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2015" +#' Detail Final Demand Code and Name (2017 schema) +#' @format A dataframe with 20 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Detail_FinalDemandCodeName_2017" -#' Sector 2016 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2016" +#' Summary Industry Code and Name (2017 schema) +#' @format A dataframe with 73 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_IndustryCodeName_2017" -#' Sector 2017 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2017" +#' Summary Commodity Code and Name (2017 schema) +#' @format A dataframe with 73 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_CommodityCodeName_2017" -#' Sector 2018 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2018" +#' Summary Value Added Code and Name (2017 schema) +#' @format A dataframe with 3 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_ValueAddedCodeName_2017" -#' Sector 2019 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2019" +#' Summary Final Demand Code and Name (2017 schema) +#' @format A dataframe with 20 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_FinalDemandCodeName_2017" -#' Sector 2020 Use (2012 schema) -#' @format A dataframe with 26 obs. and 22 variables -#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -"Sector_Use_SUT_2020" +#' Sector Industry Code and Name (2017 schema) +#' @format A dataframe with 17 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Sector_IndustryCodeName_2017" + +#' Sector Commodity Code and Name (2017 schema) +#' @format A dataframe with 17 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Sector_CommodityCodeName_2017" + +#' Sector Value Added Code and Name (2017 schema) +#' @format A dataframe with 3 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Sector_ValueAddedCodeName_2017" + +#' Sector Final Demand Code and Name (2017 schema) +#' @format A dataframe with 6 obs. and 2 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Sector_FinalDemandCodeName_2017" + +#' Summary 2017 Import Before Redefinition (2017 schema) +#' @format A dataframe with 73 obs. and 93 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +"Summary_Import_2017_BeforeRedef_17sch" + +#' Summary 2018 Import Before Redefinition (2017 schema) +#' @format A dataframe with 73 obs. and 93 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +"Summary_Import_2018_BeforeRedef_17sch" + +#' Summary 2019 Import Before Redefinition (2017 schema) +#' @format A dataframe with 73 obs. and 93 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +"Summary_Import_2019_BeforeRedef_17sch" + +#' Summary 2020 Import Before Redefinition (2017 schema) +#' @format A dataframe with 73 obs. and 93 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +"Summary_Import_2020_BeforeRedef_17sch" + +#' Summary 2021 Import Before Redefinition (2017 schema) +#' @format A dataframe with 73 obs. and 93 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +"Summary_Import_2021_BeforeRedef_17sch" + +#' Summary 2022 Import Before Redefinition (2017 schema) +#' @format A dataframe with 73 obs. and 93 variables +#' @source \url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +"Summary_Import_2022_BeforeRedef_17sch" + +#' Summary 2017 Make Before Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2017_BeforeRedef_17sch" + +#' Summary 2018 Make Before Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2018_BeforeRedef_17sch" + +#' Summary 2019 Make Before Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2019_BeforeRedef_17sch" + +#' Summary 2020 Make Before Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2020_BeforeRedef_17sch" + +#' Summary 2021 Make Before Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2021_BeforeRedef_17sch" + +#' Summary 2022 Make Before Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2022_BeforeRedef_17sch" + +#' Summary 2017 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2017_PRO_BeforeRedef_17sch" + +#' Summary 2018 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2018_PRO_BeforeRedef_17sch" + +#' Summary 2019 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2019_PRO_BeforeRedef_17sch" + +#' Summary 2020 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2020_PRO_BeforeRedef_17sch" + +#' Summary 2021 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2021_PRO_BeforeRedef_17sch" + +#' Summary 2022 Use Producer's Value Before Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2022_PRO_BeforeRedef_17sch" + +#' Summary 2017 Use Purchaser's Value Before Redefinition (2017 schema) +#' @format A dataframe with 76 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2017_PUR_BeforeRedef_17sch" + +#' Summary 2017 Make After Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2017_AfterRedef_17sch" + +#' Summary 2018 Make After Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2018_AfterRedef_17sch" + +#' Summary 2019 Make After Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2019_AfterRedef_17sch" + +#' Summary 2020 Make After Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2020_AfterRedef_17sch" + +#' Summary 2021 Make After Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2021_AfterRedef_17sch" + +#' Summary 2022 Make After Redefinition (2017 schema) +#' @format A dataframe with 72 obs. and 74 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Make_2022_AfterRedef_17sch" + +#' Summary 2017 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2017_PRO_AfterRedef_17sch" + +#' Summary 2018 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2018_PRO_AfterRedef_17sch" + +#' Summary 2019 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2019_PRO_AfterRedef_17sch" + +#' Summary 2020 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2020_PRO_AfterRedef_17sch" + +#' Summary 2021 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2021_PRO_AfterRedef_17sch" + +#' Summary 2022 Use Producer's Value After Redefinition (2017 schema) +#' @format A dataframe with 79 obs. and 94 variables +#' @source \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +"Summary_Use_2022_PRO_AfterRedef_17sch" diff --git a/R/IOFunctions.R b/R/IOFunctions.R index 097edc29..39a71954 100644 --- a/R/IOFunctions.R +++ b/R/IOFunctions.R @@ -174,13 +174,16 @@ calculateLeontiefInverse <- function(A) { #' @param model, An EEIO model object with model specs and crosswalk table loaded #' @return A Domestic Use table with rows as commodity codes and columns as industry and final demand codes generateDomesticUse <- function(Use, model) { + schema <- getSchemaCode(model$specs) # Load Import matrix if (model$specs$BaseIOLevel != "Sector") { - Import <- get(paste(model$specs$BaseIOLevel, "Import", - model$specs$IOYear, "BeforeRedef", sep = "_"))*1E6 + Import <- get(paste(na.omit(c(model$specs$BaseIOLevel, "Import", + model$specs$IOYear, "BeforeRedef", schema)), + collapse = "_"))*1E6 } else { # Load Summary level Import matrix - Import <- get(paste("Summary_Import", model$specs$IOYear, "BeforeRedef", sep = "_"))*1E6 + Import <- get(paste(na.omit(c("Summary_Import", model$specs$IOYear, "BeforeRedef", schema)), + collapse = "_"))*1E6 # Aggregate Import from Summary to Sector Import <- as.data.frame(aggregateMatrix(as.matrix(Import), "Summary", "Sector", model)) } @@ -197,8 +200,8 @@ generateDomesticUse <- function(Use, model) { # needs to be subtracted from the original Import matrix if (model$specs$BasePriceType == "BAS") { # Find "MDTY - import duties" in Supply table - Supply <- get(paste(model$specs$BaseIOLevel, "Supply", model$specs$IOYear, - sep = "_")) * 1E6 + Supply <- get(paste(na.omit(c(model$specs$BaseIOLevel, "Supply", model$specs$IOYear, schema)), + collapse = "_")) * 1E6 ImportDuty <- Supply[rownames(Import), "MDTY"] # Subtract import duties from Import matrix # Expanding it to a matrix based on the Import matrix, except for the import column @@ -228,12 +231,15 @@ generateDomesticUse <- function(Use, model) { #' @param model, An EEIO model object with model specs and crosswalk table loaded #' @return An international trade adjustment vector with names as commodity codes generateInternationalTradeAdjustmentVector <- function(Use, model) { + schema <- getSchemaCode(model$specs) # Load Import matrix if (model$specs$BaseIOLevel!="Sector") { - Import <- get(paste(model$specs$BaseIOLevel, "Import", model$specs$IOYear, "BeforeRedef", sep = "_"))*1E6 + Import <- get(paste(na.omit(c(model$specs$BaseIOLevel, "Import", model$specs$IOYear, "BeforeRedef", schema)), + collapse = "_"))*1E6 } else { # Load Summary level Import matrix - Import <- get(paste("Summary_Import", model$specs$IOYear, "BeforeRedef", sep = "_"))*1E6 + Import <- get(paste(na.omit(c("Summary_Import", model$specs$IOYear, "BeforeRedef", schema)), + collapse = "_"))*1E6 # Aggregate Import from Summary to Sector Import <- as.data.frame(aggregateMatrix(as.matrix(Import), "Summary", "Sector", model)) } @@ -261,10 +267,11 @@ generateInternationalTradeAdjustmentVector <- function(Use, model) { convertUsefromPURtoBAS <- function(UseSUT_PUR, specs, io_codes) { # Load UsePRO and UsePUR under Make-Use framework Redef <- ifelse(specs$BasewithRedefinitions, "AfterRedef", "BeforeRedef") - UsePUR <- get(paste(specs$BaseIOLevel, "Use", specs$IOYear, "PUR", Redef, sep = "_")) - UsePRO <- get(paste(specs$BaseIOLevel, "Use", specs$IOYear, "PRO", Redef, sep = "_")) + schema <- getSchemaCode(specs) + UsePUR <- get(paste(na.omit(c(specs$BaseIOLevel, "Use", specs$IOYear, "PUR", Redef, specs)), collapse = "_")) + UsePRO <- get(paste(na.omit(c(specs$BaseIOLevel, "Use", specs$IOYear, "PRO", Redef, specs)), collapse = "_")) # Load Supply table - Supply <- get(paste(specs$BaseIOLevel, "Supply", specs$IOYear, sep = "_")) + Supply <- get(paste(na.omit(c(specs$BaseIOLevel, "Supply", specs$IOYear, specs)), collapse = "_")) # Convert from PUR to PRO by removing margins obtained from Supply table rows <- io_codes$Commodities @@ -309,9 +316,10 @@ convertUsefromPURtoBAS <- function(UseSUT_PUR, specs, io_codes) { #' @return A data.frame containing CommodityCode, basic price, tax less subsidies, #' and producer price of total product supply generateTaxLessSubsidiesTable <- function(model) { + schema <- getSchemaCode(model$specs) # Load Supply table - Supply <- get(paste(model$specs$BaseIOLevel, "Supply", model$specs$IOYear, - sep = "_")) + Supply <- get(paste(na.omit(c(model$specs$BaseIOLevel, "Supply", model$specs$IOYear, schema)), + collapse = "_")) # Get basic price and tax less subsidies vectors from Supply import_cols <- getVectorOfCodes(model$specs$BaseIOSchema, model$specs$BaseIOLevel, diff --git a/R/InitializeModel.R b/R/InitializeModel.R index 56fa11f1..e1bfce37 100644 --- a/R/InitializeModel.R +++ b/R/InitializeModel.R @@ -12,19 +12,26 @@ initializeModel <- function(modelname, configpaths = NULL) { if (is.null(model$specs)) { stop(paste("No configuration exists for a model named", modelname)) } else { - # Get model crosswalk - crosswalk <- get(paste0("MasterCrosswalk", model$specs$BaseIOSchema), - as.environment("package:useeior")) - crosswalk <- unique(crosswalk[, c("NAICS_2012_Code", - colnames(crosswalk)[startsWith(colnames(crosswalk), "BEA")])]) - colnames(crosswalk) <- gsub(paste0("_", model$specs$BaseIOSchema, "|_Code"), - "", colnames(crosswalk)) - rownames(crosswalk) <- NULL - # Assign initial model crosswalk based on base schema - modelschema <- "USEEIO" - baseschema <- paste0("BEA_", model$specs$BaseIOLevel) - crosswalk[modelschema] <- crosswalk[baseschema] - model$crosswalk <- crosswalk + model$crosswalk <- getModelCrosswalk(model) } return(model) -} \ No newline at end of file +} + +#' Get model crosswalk based on BaseIOSchema and BaseIOLevel +#' @param model EEIO model with specs assigned +#' @return crosswalk as dataframe +getModelCrosswalk <- function(model) { + # Get model crosswalk + crosswalk <- get(paste0("MasterCrosswalk", model$specs$BaseIOSchema), + as.environment("package:useeior")) + crosswalk <- unique(crosswalk[, c(paste0("NAICS_", model$specs$BaseIOSchema, "_Code"), + colnames(crosswalk)[startsWith(colnames(crosswalk), "BEA")])]) + colnames(crosswalk) <- gsub(paste0("_", model$specs$BaseIOSchema, "|_Code"), + "", colnames(crosswalk)) + rownames(crosswalk) <- NULL + # Assign initial model crosswalk based on base schema + modelschema <- "USEEIO" + baseschema <- paste0("BEA_", model$specs$BaseIOLevel) + crosswalk[modelschema] <- crosswalk[baseschema] + return(crosswalk) +} diff --git a/R/LoadGOandCPI.R b/R/LoadGOandCPI.R index 876a051f..1cd2320d 100644 --- a/R/LoadGOandCPI.R +++ b/R/LoadGOandCPI.R @@ -5,8 +5,10 @@ #' @return A data.frame of US Gross Output. loadNationalGrossOutputTable <- function(specs) { logging::loginfo("Initializing Gross Output tables...") + schema <- getSchemaCode(specs) # Load pre-saved Gross Output tables - GrossOutput <- get(paste0(specs$BaseIOLevel, "_GrossOutput_IO")) * 1E6 # data frame, values are in dollars ($) + GrossOutput <- get(paste0(na.omit(c(specs$BaseIOLevel, "GrossOutput_IO", schema)), + collapse = "_")) * 1E6 # data frame, values are in dollars ($) return(GrossOutput) } @@ -15,6 +17,7 @@ loadNationalGrossOutputTable <- function(specs) { #' @return A data.frame of Chain Price Index. loadChainPriceIndexTable <- function(specs) { logging::loginfo("Initializing Chain Price Index tables...") - ChainPriceIndex <- get(paste0(specs$BaseIOLevel, "_CPI_IO")) + schema <- getSchemaCode(specs) + ChainPriceIndex <- get(paste0(na.omit(c(specs$BaseIOLevel, "CPI_IO", schema)), collapse = "_")) return(ChainPriceIndex) } diff --git a/R/LoadIOTables.R b/R/LoadIOTables.R index 03926ae7..29e71b5f 100644 --- a/R/LoadIOTables.R +++ b/R/LoadIOTables.R @@ -231,11 +231,12 @@ loadNationalIOData <- function(model, io_codes) { #' @return A list with BEA IO tables loadBEAtables <- function(specs, io_codes) { BEA <- list() + schema <- getSchemaCode(specs) if (specs$BasePriceType != "BAS") { # Load pre-saved Make and Use tables Redef <- ifelse(specs$BasewithRedefinitions, "AfterRedef", "BeforeRedef") - BEA$Make <- get(paste(specs$BaseIOLevel, "Make", specs$IOYear, Redef, sep = "_")) - BEA$Use <- get(paste(specs$BaseIOLevel, "Use", specs$IOYear, specs$BasePriceType, Redef, sep = "_")) + BEA$Make <- get(paste(na.omit(c(specs$BaseIOLevel, "Make", specs$IOYear, Redef, schema)), collapse="_")) + BEA$Use <- get(paste(na.omit(c(specs$BaseIOLevel, "Use", specs$IOYear, specs$BasePriceType, Redef, schema)), collapse="_")) # Separate Make table into specific IO tables (all values in $) BEA$MakeTransactions <- BEA$Make[io_codes$Industries, io_codes$Commodities] * 1E6 # Separate Use table into specific IO tables (all values in $) @@ -248,8 +249,8 @@ loadBEAtables <- function(specs, io_codes) { io_codes$Industries] * 1E6 } else if (specs$BasePriceType == "BAS") { # Load pre-saved Supply and Use tables - BEA$Supply <- get(paste(specs$BaseIOLevel, "Supply", specs$IOYear, sep = "_")) - UseSUT_PUR <- get(paste(specs$BaseIOLevel, "Use_SUT", specs$IOYear, sep = "_")) + BEA$Supply <- get(paste(na.omit(c(specs$BaseIOLevel, "Supply", specs$IOYear, schema)), collapse = "_")) + UseSUT_PUR <- get(paste(na.omit(c(specs$BaseIOLevel, "Use_SUT", specs$IOYear, schema)), collapse = "_")) BEA$Use <- convertUsefromPURtoBAS(UseSUT_PUR, specs, io_codes) # Separate Supply table into specific IO tables (all values in $) # Transpose Supply table to conform the structure of Make table diff --git a/R/LoadMargins.R b/R/LoadMargins.R index a0fb4144..c76d7bf2 100644 --- a/R/LoadMargins.R +++ b/R/LoadMargins.R @@ -6,11 +6,11 @@ getMarginsTable <- function (model) { # Define value_columns in Margins table value_columns <- c("ProducersValue", "Transportation", "Wholesale", "Retail") + schema <- getSchemaCode(model$specs) # Use BEA Margin Details table - if (model$specs$BaseIOSchema==2012) { - MarginsTable <- useeior::Detail_Margins_2012_BeforeRedef - MarginsTable[, value_columns] <- MarginsTable[, value_columns]*1E6 - } + MarginsTable <- get(paste0(na.omit(c('Detail_Margins', model$specs$BaseIOSchema, 'BeforeRedef', schema)), + collapse = "_")) + MarginsTable[, value_columns] <- MarginsTable[, value_columns]*1E6 # Remove Export, Import and Change in Inventory records. # Exports do not reflect what a US consumer would pay for margins, hence the removal. # Imports have negative PRO price which impacts calculations. diff --git a/R/LoadSatellites.R b/R/LoadSatellites.R index d060d9dc..3790243b 100644 --- a/R/LoadSatellites.R +++ b/R/LoadSatellites.R @@ -43,7 +43,10 @@ loadSatTables <- function(model) { } else { logging::loginfo(paste0("Loading ", sat_spec$FullName, " flows from ", sat_spec$FileLocation, "...")) } - + if(sat_spec$SectorListSource == "NAICS" && sat_spec$SectorListYear != model$specs$BaseIOSchema) { + logging::logwarn(paste0("SectorListYear of ", sat_spec$FullName," does not match the BaseIOSchema ", + "and may not map to sectors correctly.")) + } ### Generate totals_by_sector, tbs tbs0 <- generateTbSfromSatSpec(sat_spec, model) @@ -161,7 +164,8 @@ conformTbStoIOSchema <- function(tbs, sat_spec, model) { # If not, map data from original sector to BEA. if (sat_spec$SectorListSource == "BEA") { # If BEA years is not the same as model year, must perform allocation - if (all(sat_spec$SectorListLevel == "Detail", sat_spec$SectorListYear == 2007, model$specs$BaseIOSchema == 2012)) { + if (all(sat_spec$SectorListLevel == "Detail", sat_spec$SectorListSource == "BEA", + sat_spec$SectorListYear == 2007, model$specs$BaseIOSchema == 2012)) { tbs <- mapFlowTotalsbySectorfromBEASchema2007to2012(tbs) } # If the original data is at Detail level but model is not, apply aggregation diff --git a/R/SatelliteFunctions.R b/R/SatelliteFunctions.R index 4fee438e..a0cbe8b0 100644 --- a/R/SatelliteFunctions.R +++ b/R/SatelliteFunctions.R @@ -346,5 +346,10 @@ removeMissingSectors <- function(tbs) { if(n > 0){ logging::logdebug(paste0(n, "records dropped with no sector")) } + sectors <- unique(tbs[is.na(tbs$SectorName), ]) + if(nrow(sectors)>0){ + logging::logwarn(paste0("Lost sectors due to missing mapping: ", + paste0(unique(sectors[['Sector']]), collapse=', '))) + } return(df) } diff --git a/R/UtilityFunctions.R b/R/UtilityFunctions.R index b51d7074..381422cd 100644 --- a/R/UtilityFunctions.R +++ b/R/UtilityFunctions.R @@ -464,6 +464,19 @@ getInputFilePath <- function(configpaths, folderPath="extdata", filename, packag return(filepath) } +#' Return the schema subscript for accessing useeior objects +#' @param specs list of model specs must include BaseIOSchema +#' @return schema, str in form "YYsch" or NULL for 2012 +getSchemaCode <- function(specs) { + if(specs$BaseIOSchema != 2012) { + schema <- paste0(substring(specs$BaseIOSchema, 3,4), "sch") + } else { + # despite the file name, the objects don't have the schema so it should not be used + schema <- NULL + } + return(schema) +} + #' Reorder sectors in the model objects according to the provided order. #' @param model An EEIO model object with model specs and IO tables loaded #' @param comOrder A list containing the order of the commodities in the model diff --git a/R/ValidateModel.R b/R/ValidateModel.R index 1e938597..99cccdc1 100644 --- a/R/ValidateModel.R +++ b/R/ValidateModel.R @@ -143,10 +143,17 @@ compareCommodityOutputandDomesticUseplusProductionDemand <- function(model, tole #' @return A list with pass/fail validation result and the cell-by-cell relative diff matrix #' @export compareCommodityOutputXMarketShareandIndustryOutputwithCPITransformation <- function(model, tolerance=0.05) { - commodityCPI_ratio <- model$MultiYearCommodityCPI[, "2017"]/model$MultiYearCommodityCPI[, "2012"] + if(model$specs$BaseIOSchema == 2012){ + target_year <- "2017" + } else if(model$specs$BaseIOSchema == 2017){ + target_year <- "2022" + } + commodityCPI_ratio <- (model$MultiYearCommodityCPI[, target_year]/ + model$MultiYearCommodityCPI[, as.character(model$specs$BaseIOSchema)]) commodityCPI_ratio[is.na(commodityCPI_ratio)] <- 1 - industryCPI_ratio <- model$MultiYearIndustryCPI[, "2017"]/model$MultiYearIndustryCPI[, "2012"] + industryCPI_ratio <- (model$MultiYearIndustryCPI[, target_year]/ + model$MultiYearIndustryCPI[, as.character(model$specs$BaseIOSchema)]) industryCPI_ratio[is.na(industryCPI_ratio)] <- 1 q <- removeHybridProcesses(model, model$q * commodityCPI_ratio) diff --git a/data-raw/BEAData.R b/data-raw/BEAData.R index d551e1eb..210d0640 100644 --- a/data-raw/BEAData.R +++ b/data-raw/BEAData.R @@ -1,9 +1,19 @@ -# Download all IO tables under Make-Use framework from BEA iTable +url_ls <- c(IO = "https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip", + imports = "https://apps.bea.gov/industry/xls/io-annual", + GDP = "https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip", + SUP = "https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip", + margins = "https://apps.bea.gov/industry/xls/underlying-estimates" + ) + +dir <- file.path(rappdirs::user_data_dir(), "USEEIO-input") +dir.create(dir, showWarnings = FALSE) + +# Download and unzip all IO tables under Make-Use framework from BEA iTable getBEAIOTables <- function() { # Create the placeholder file - AllTablesIO <- "inst/extdata/AllTablesIO.zip" + AllTablesIO <- paste0(dir, "/", "AllTablesIO.zip") # Download all BEA IO tables into the placeholder file - url <- "https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip" + url <- url_ls["IO"] if (!file.exists(AllTablesIO)) { utils::download.file(url, AllTablesIO, mode = "wb") } @@ -11,9 +21,9 @@ getBEAIOTables <- function() { files <- unzip(AllTablesIO, list = TRUE) fname <- files[files$Length > 0, ]$Name if (all(fname == basename(fname))) { - exdir <- "inst/extdata/AllTablesIO" + exdir <- paste0(dir, "/", "AllTableIO") } else { - exdir <- "inst/extdata/" + exdir <- dir } # Unzip the file to the designated directory unzip(AllTablesIO, files = fname, exdir = exdir, @@ -26,1134 +36,774 @@ getBEAIOTables <- function() { } -# Get BEA Detail Make (Before Redef, 2012 schema) table from static Excel -getBEADetailMakeBeforeRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesIO", - files[startsWith(files, "IOMake_Before_Redefinitions") & - endsWith(files, "Detail.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - DetailMake <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Assign row and column names - DetailMake <- DetailMake[!is.na(DetailMake[, 2]), ] - colnames(DetailMake) <- DetailMake[1, ] - rownames(DetailMake) <- DetailMake$Code - # Trim table, convert all values to numeric, assign row names - DetailMake <- as.data.frame(lapply(DetailMake[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailMake[-1, 1]) - # Replace NA with zero - DetailMake[is.na(DetailMake)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailMake, - data_name = paste0("Detail_Make_", year, "_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Make_", year, "_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Download and unzip all Supply and Use tables from BEA AllTablesSUP.zip +getBEASupplyUseTables <- function() { + # Create the placeholder file + AllTablesSUP <- paste0(dir, "/", "AllTablesIOSUP.zip") + # Download all BEA IO tables into the placeholder file + url <- url_ls["SUP"] + if (!file.exists(AllTablesSUP)) { + utils::download.file(url, AllTablesSUP, mode = "wb") + } + # Get the name of all files in the zip archive + files <- unzip(AllTablesSUP, list = TRUE) + fname <- files[files$Length > 0, ]$Name + if (all(fname == basename(fname))) { + exdir <- paste0(dir, "/", "AllTablesSUP") + } else { + exdir <- dir + } + # Unzip the file to the designated directory + unzip(AllTablesSUP, files = fname, exdir = exdir, + overwrite = TRUE, setTimes = TRUE) + # Create output + ls <- list("url" = url, + "date_accessed" = as.character(as.Date(file.mtime(AllTablesSUP))), + "files" = basename(fname)) + return(ls) } -# Get BEA Detail Use (PRO, Before Redef, 2012 schema) table from static Excel -getBEADetailUsePROBeforeRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesIO", - files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & - endsWith(files, "Detail.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - DetailUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Assign row and column names - DetailUse <- DetailUse[!is.na(DetailUse[, 2]), ] - colnames(DetailUse) <- DetailUse[1, ] - rownames(DetailUse) <- DetailUse$Code - # Trim table, convert all values to numeric, assign row names - DetailUse <- as.data.frame(lapply(DetailUse[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailUse[-1, 1]) - # Replace NA with zero - DetailUse[is.na(DetailUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailUse, - data_name = paste0("Detail_Use_", year, "_PRO_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Use_", year, "_PRO_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Download and unzip all GDP tables from BEA +getBEAUnderlyingTables <- function() { + # Create the placeholder file + UnderlyingTables <- paste0(dir, "/", "UGdpByInd.zip") + # Download all BEA IO tables into the placeholder file + url <- url_ls["GDP"] + if (!file.exists(UnderlyingTables)) { + utils::download.file(url, UnderlyingTables, mode = "wb") + } + # Get the name of all files in the zip archive + files <- unzip(UnderlyingTables, list = TRUE) + fname <- files[files$Length > 0, ]$Name + if (all(fname == basename(fname))) { + exdir <- paste0(dir, "/", "UGdpByInd") + } else { + exdir <- dir + } + # Unzip the file to the designated directory + unzip(UnderlyingTables, files = fname, exdir = exdir, + overwrite = TRUE, setTimes = TRUE) + # Create output + ls <- list("url" = url, + "date_accessed" = as.character(as.Date(file.mtime(UnderlyingTables))), + "files" = basename(fname)) + return(ls) } -# Get BEA Detail Use (PUR, Before Redef, 2012 schema) 2012 table from static Excel -getBEADetailUsePURBeforeRedef2012Schema <- function(year) { +#' Extract table from BEA data +#' @param year, str IOschema year +#' @param filename, str e.g. "IOUse_Before_Redefinitions_PRO" +#' @param ioschema, str e.g. "Detail" +unpackFile <- function(year, filename, ioschema) { # Download data url <- getBEAIOTables()[["url"]] date_accessed <- getBEAIOTables()[["date_accessed"]] files <- getBEAIOTables()[["files"]] # Load data - FileName <- file.path("inst/extdata/AllTablesIO", - files[startsWith(files, "IOUse_Before_Redefinitions_PUR") & - endsWith(files, "Detail.xlsx")]) + FileName <- file.path(rappdirs::user_data_dir(), "USEEIO-input", "AllTableIO", + files[startsWith(files, filename) & + endsWith(files, paste0(ioschema, ".xlsx"))]) date_last_modified <- as.character(as.Date(file.mtime(FileName))) - DetailUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) + df <- as.data.frame(readxl::read_excel(FileName, + sheet = as.character(year))) + # return multiple items to access later + ls <- list("df" = df, + "url" = url, + "date_accessed" = date_accessed, + "date_last_modified" = date_last_modified) + return(ls) +} + +#' Process dataframe to remove spaces and assign col/row names +#' @param df, dataframe of matrix (i.e., make or use table) +processDetailMatrix <- function(df) { # Assign row and column names - DetailUse <- DetailUse[!is.na(DetailUse[, 2]), ] - colnames(DetailUse) <- DetailUse[1, ] - rownames(DetailUse) <- DetailUse$Code + df <- df[!is.na(df[, 2]), ] + colnames(df) <- df[1, ] + rownames(df) <- df$Code # Trim table, convert all values to numeric, assign row names - DetailUse <- as.data.frame(lapply(DetailUse[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailUse[-1, 1]) + df <- as.data.frame(lapply(df[-1, -c(1:2)], as.numeric), + check.names = FALSE, + row.names = df[-1, 1]) # Replace NA with zero - DetailUse[is.na(DetailUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailUse, - data_name = paste0("Detail_Use_", year, "_PUR_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Use_", year, "_PUR_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + df[is.na(df)] <- 0 + return(df) } -# Get BEA Detail Make (After Redef, 2012 schema) table from static Excel -getBEADetailMakeAfterRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesIO", - files[startsWith(files, "IOMake_After_Redefinitions") & - endsWith(files, "Detail.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - DetailMake <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Assign row and column names - DetailMake <- DetailMake[!is.na(DetailMake[, 2]), ] - colnames(DetailMake) <- DetailMake[1, ] - rownames(DetailMake) <- DetailMake$Code - # Trim table, convert all values to numeric, assign row names - DetailMake <- as.data.frame(lapply(DetailMake[-1, -c(1:2)], as.numeric), +#' Process dataframe to remove spaces and assign col/row names +#' @param df, dataframe of matrix (i.e., make or use table) +processSummaryMatrix <- function(df) { + # Trim table, assign column names + df <- df[!is.na(df[, 2]), ] + colnames(df) <- df[1, ] + colname_check <- is.na(colnames(df)) + colnames(df)[colname_check] <- df[2, colname_check] + # Fill NA in code column with corresponding name + df[is.na(df[, 1]), 1] <- df[is.na(df[, 1]), 2] + # Convert all values to numeric, assign row names + df <- as.data.frame(lapply(df[-c(1:2), -c(1:2)], as.numeric), check.names = FALSE, - row.names = DetailMake[-1, 1]) + row.names = df[-c(1:2), 1]) # Replace NA with zero - DetailMake[is.na(DetailMake)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailMake, - data_name = paste0("Detail_Make_", year, "_AfterRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Make_", year, "_AfterRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + df[is.na(df)] <- 0 + return(df) } -# Get BEA Detail Use (PRO, After Redef, 2012 schema) table from static Excel -getBEADetailUsePROAfterRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesIO", - files[startsWith(files, "IOUse_After_Redefinitions_PRO") & - endsWith(files, "Detail.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - DetailUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Assign row and column names - DetailUse <- DetailUse[!is.na(DetailUse[, 2]), ] - colnames(DetailUse) <- DetailUse[1, ] - rownames(DetailUse) <- DetailUse$Code - # Trim table, convert all values to numeric, assign row names - DetailUse <- as.data.frame(lapply(DetailUse[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailUse[-1, 1]) - # Replace NA with zero - DetailUse[is.na(DetailUse)] <- 0 +#' Write RDA and json metadata files +#' @param df, dataframe of matrix (i.e., make or use table) +#' @param year, str IO data year +#' @param name, str +#' @param ls, list of metadata items +#' @param scehma_year str of schema year (e.g., 2012 or 2017) +writeFile <- function(df, year, name, ls, schema_year) { + if (!is.null(schema_year)){ + # append schema to filename e.g., _17sch + name <- paste0(name, "_", substring(schema_year, 3, 4), "sch") + } # Write data to .rda - writeDatatoRDA(data = DetailUse, - data_name = paste0("Detail_Use_", year, "_PRO_AfterRedef")) + writeDatatoRDA(data = df, + data_name = name) # Write metadata to JSON writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Use_", year, "_PRO_AfterRedef"), + name = name, year = year, source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + url = ls[["url"]], + date_last_modified = ls[["date_last_modified"]], + date_accessed = ls[["date_accessed"]]) } -# Get BEA Detail Use (PUR, After Redef, 2012 schema) table from static Excel -getBEADetailUsePURAfterRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesIO", - files[startsWith(files, "IOUse_After_Redefinitions_PUR") & - endsWith(files, "Detail.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - DetailUse <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Assign row and column names - DetailUse <- DetailUse[!is.na(DetailUse[, 2]), ] - colnames(DetailUse) <- DetailUse[1, ] - rownames(DetailUse) <- DetailUse$Code - # Trim table, convert all values to numeric, assign row names - DetailUse <- as.data.frame(lapply(DetailUse[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailUse[-1, 1]) - # Replace NA with zero - DetailUse[is.na(DetailUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailUse, - data_name = paste0("Detail_Use_", year, "_PUR_AfterRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Use_", year, "_PUR_AfterRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Detail Make (Before Redef) table from static Excel +getBEADetailMakeBeforeRedef <- function(year) { + ls <- unpackFile(year, filename="IOMake_Before_Redefinitions", ioschema="Detail") + DetailMake <- data.frame(ls["df"]) + DetailMake <- processDetailMatrix(DetailMake) + writeFile(df = DetailMake, year = year, + name = paste0("Detail_Make_", year, "_BeforeRedef"), ls = ls, + schema_year = year) } -# Get BEA Summary Make (Before Redef, 2012 schema) table from static Excel -getBEASummaryMakeBeforeRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOMake_Before_Redefinitions") & - endsWith(files, "Summary.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SummaryMake <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SummaryMake <- SummaryMake[!is.na(SummaryMake[, 2]), ] - colnames(SummaryMake) <- SummaryMake[1, ] - colname_check <- is.na(colnames(SummaryMake)) - colnames(SummaryMake)[colname_check] <- SummaryMake[2, colname_check] - # Fill NA in code column with corresponding name - SummaryMake[is.na(SummaryMake[, 1]), 1] <- SummaryMake[is.na(SummaryMake[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryMake <- as.data.frame(lapply(SummaryMake[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryMake[-c(1:2), 1]) - # Replace NA with zero - SummaryMake[is.na(SummaryMake)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryMake, - data_name = paste0("Summary_Make_", year, "_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Make_", year, "_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) - } +# Get BEA Detail Use (PRO, Before Redef) table from static Excel +getBEADetailUsePROBeforeRedef <- function(year) { + ls <- unpackFile(year, filename="IOUse_Before_Redefinitions_PRO", ioschema="Detail") + DetailUse <- data.frame(ls["df"]) + DetailUse <- processDetailMatrix(DetailUse) + writeFile(df = DetailUse, year = year, + name = paste0("Detail_Use_", year, "_PRO_BeforeRedef"), ls = ls, + schema_year = year) } -# Get BEA Summary Use (PRO, Before Redef, 2012 schema) table from static Excel -getBEASummaryUsePROBeforeRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & - endsWith(files, "Summary.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SummaryUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SummaryUse <- SummaryUse[!is.na(SummaryUse[, 2]), ] - colnames(SummaryUse) <- SummaryUse[1, ] - colname_check <- is.na(colnames(SummaryUse)) - colnames(SummaryUse)[colname_check] <- SummaryUse[2, colname_check] - # Fill NA in code column with corresponding name - SummaryUse[is.na(SummaryUse[, 1]), 1] <- SummaryUse[is.na(SummaryUse[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryUse <- as.data.frame(lapply(SummaryUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryUse[-c(1:2), 1]) - # Replace NA with zero - SummaryUse[is.na(SummaryUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryUse, - data_name = paste0("Summary_Use_", year, "_PRO_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Use_", year, "_PRO_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) - } +# Get BEA Detail Use (PUR, Before Redef) table from static Excel +getBEADetailUsePURBeforeRedef <- function(year) { + ls <- unpackFile(year, filename="IOUse_Before_Redefinitions_PUR", ioschema="Detail") + DetailUse <- data.frame(ls["df"]) + DetailUse <- processDetailMatrix(DetailUse) + writeFile(df = DetailUse, year = year, + name = paste0("Detail_Use_", year, "_PUR_BeforeRedef"), ls = ls, + schema_year = year) } -# Get BEA Summary Use (PUR, Before Redef, 2012 schema) table from static Excel -getBEASummaryUsePURBeforeRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOUse_Before_Redefinitions_PUR") & - endsWith(files, "Summary.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Load data - SummaryUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SummaryUse <- SummaryUse[!is.na(SummaryUse[, 2]), ] - colnames(SummaryUse) <- SummaryUse[1, ] - colname_check <- is.na(colnames(SummaryUse)) - colnames(SummaryUse)[colname_check] <- SummaryUse[2, colname_check] - # Fill NA in code column with corresponding name - SummaryUse[is.na(SummaryUse[, 1]), 1] <- SummaryUse[is.na(SummaryUse[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryUse <- as.data.frame(lapply(SummaryUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryUse[-c(1:2), 1]) - # Replace NA with zero - SummaryUse[is.na(SummaryUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryUse, - data_name = paste0("Summary_Use_", year, "_PUR_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Use_", year, "_PUR_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Detail Make (After Redef) table from static Excel +getBEADetailMakeAfterRedef <- function(year) { + ls <- unpackFile(year, filename="IOMake_After_Redefinitions", ioschema="Detail ") + ### ^^ Typo in filename from BEA requires extra space in ioschema ^^^ + DetailMake <- data.frame(ls["df"]) + DetailMake <- processDetailMatrix(DetailMake) + writeFile(df = DetailMake, year = year, + name = paste0("Detail_Make_", year, "_AfterRedef"), ls = ls, + schema_year = year) } -# Get BEA Summary Make (After Redef, 2012 schema) table from static Excel -getBEASummaryMakeAfterRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOMake_After_Redefinitions") & - endsWith(files, "Summary.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SummaryMake <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SummaryMake <- SummaryMake[!is.na(SummaryMake[, 2]), ] - colnames(SummaryMake) <- SummaryMake[1, ] - colname_check <- is.na(colnames(SummaryMake)) - colnames(SummaryMake)[colname_check] <- SummaryMake[2, colname_check] - # Fill NA in code column with corresponding name - SummaryMake[is.na(SummaryMake[, 1]), 1] <- SummaryMake[is.na(SummaryMake[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryMake <- as.data.frame(lapply(SummaryMake[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryMake[-c(1:2), 1]) - # Replace NA with zero - SummaryMake[is.na(SummaryMake)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryMake, - data_name = paste0("Summary_Make_", year, "_AfterRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Make_", year, "_AfterRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) - } +# Get BEA Detail Use (PRO, After Redef) table from static Excel +getBEADetailUsePROAfterRedef <- function(year) { + ls <- unpackFile(year, filename="IOUse_After_Redefinitions_PRO", ioschema="Detail") + DetailUse <- data.frame(ls["df"]) + DetailUse <- processDetailMatrix(DetailUse) + writeFile(df = DetailUse, year = year, + name = paste0("Detail_Use_", year, "_PRO_AfterRedef"), ls = ls, + schema_year = year) } -# Get BEA Summary Use (PRO, After Redef, 2012 schema) table from static Excel -getBEASummaryUsePROAfterRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOUse_After_Redefinitions_PRO") & - endsWith(files, "Summary.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SummaryUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SummaryUse <- SummaryUse[!is.na(SummaryUse[, 2]), ] - colnames(SummaryUse) <- SummaryUse[1, ] - colname_check <- is.na(colnames(SummaryUse)) - colnames(SummaryUse)[colname_check] <- SummaryUse[2, colname_check] - # Fill NA in code column with corresponding name - SummaryUse[is.na(SummaryUse[, 1]), 1] <- SummaryUse[is.na(SummaryUse[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryUse <- as.data.frame(lapply(SummaryUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryUse[-c(1:2), 1]) - # Replace NA with zero - SummaryUse[is.na(SummaryUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryUse, - data_name = paste0("Summary_Use_", year, "_PRO_AfterRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Use_", year, "_PRO_AfterRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) - } +# Get BEA Detail Use (PUR, After Redef) table from static Excel +getBEADetailUsePURAfterRedef <- function(year) { + ls <- unpackFile(year, filename="IOUse_After_Redefinitions_PUR", ioschema="Detail") + DetailUse <- data.frame(ls["df"]) + DetailUse <- processDetailMatrix(DetailUse) + writeFile(df = DetailUse, year = year, + name = paste0("Detail_Use_", year, "_PUR_AfterRedef"), ls = ls, + schema_year = year) } -# Get BEA Sector Make (Before Redef, 2012 schema) table from static Excel -getBEASectorMakeBeforeRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOMake_Before_Redefinitions") & - endsWith(files, "Sector.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SectorMake <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorMake <- SectorMake[!is.na(SectorMake[, 2]), ] - colnames(SectorMake) <- SectorMake[1, ] - colname_check <- is.na(colnames(SectorMake)) - colnames(SectorMake)[colname_check] <- SectorMake[2, colname_check] - # Fill NA in code column with corresponding name - SectorMake[is.na(SectorMake[, 1]), 1] <- SectorMake[is.na(SectorMake[, 1]), 2] - # Convert all values to numeric, assign row names - SectorMake <- as.data.frame(lapply(SectorMake[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorMake[-c(1:2), 1]) - # Replace NA with zero - SectorMake[is.na(SectorMake)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorMake, - data_name = paste0("Sector_Make_", year, "_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Make_", year, "_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Summary Make (Before Redef) table from static Excel +getBEASummaryMakeBeforeRedef <- function(year) { + end_year <- 2022 + for (y in 2017:end_year) { + ls <- unpackFile(y, filename="IOMake_Before_Redefinitions", ioschema="Summary") + SummaryMake <- data.frame(ls["df"]) + SummaryMake <- processSummaryMatrix(SummaryMake) + writeFile(df = SummaryMake, year = y, + name = paste0("Summary_Make_", y, "_BeforeRedef"), ls = ls, + schema_year = year) } } -# Get BEA Sector Use (PRO, Before Redef, 2012 schema) table from static Excel -getBEASectorUsePROBeforeRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & - endsWith(files, "Sector.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - for (year in 2010:end_year) { - SectorUse <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] - colnames(SectorUse) <- SectorUse[1, ] - colname_check <- is.na(colnames(SectorUse)) - colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] - # Fill NA in code column with corresponding name - SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] - # Convert all values to numeric, assign row names - SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorUse[-c(1:2), 1]) - # Replace NA with zero - SectorUse[is.na(SectorUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorUse, - data_name = paste0("Sector_Use_", year, "_PRO_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Use_", year, "_PRO_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Summary Use (PRO, Before Redef) table from static Excel +getBEASummaryUsePROBeforeRedef <- function(year) { + end_year <- 2022 + for (y in 2017:end_year) { + ls <- unpackFile(y, filename="IOUse_Before_Redefinitions_PRO", ioschema="Summary") + SummaryUse <- data.frame(ls["df"]) + SummaryUse <- processSummaryMatrix(SummaryUse) + writeFile(df = SummaryUse, year = y, + name = paste0("Summary_Use_", y, "_PRO_BeforeRedef"), ls = ls, + schema_year = year) } } -# Get BEA Sector Use (PUR, Before Redef, 2012 schema) table from static Excel -getBEASectorUsePURBeforeRedef2012Schema <- function(year) { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOUse_Before_Redefinitions_PUR") & - endsWith(files, "Sector.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Load data - SectorUse <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] - colnames(SectorUse) <- SectorUse[1, ] - colname_check <- is.na(colnames(SectorUse)) - colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] - # Fill NA in code column with corresponding name - SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] - # Convert all values to numeric, assign row names - SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorUse[-c(1:2), 1]) - # Replace NA with zero - SectorUse[is.na(SectorUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorUse, - data_name = paste0("Sector_Use_", year, "_PUR_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Use_", year, "_PUR_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Summary Use (PUR, Before Redef) table from static Excel +getBEASummaryUsePURBeforeRedef <- function(year) { + ls <- unpackFile(year, filename="IOUse_Before_Redefinitions_PUR", ioschema="Summary") + SummaryUse <- data.frame(ls["df"]) + SummaryUse <- processSummaryMatrix(SummaryUse) + writeFile(df = SummaryUse, year = year, + name = paste0("Summary_Use_", year, "_PUR_BeforeRedef"), ls = ls, + schema_year = year) } -# Get BEA Sector Make (After Redef, 2012 schema) table from static Excel -getBEASectorMakeAfterRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOMake_After_Redefinitions") & - endsWith(files, "Sector.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SectorMake <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorMake <- SectorMake[!is.na(SectorMake[, 2]), ] - colnames(SectorMake) <- SectorMake[1, ] - colname_check <- is.na(colnames(SectorMake)) - colnames(SectorMake)[colname_check] <- SectorMake[2, colname_check] - # Fill NA in code column with corresponding name - SectorMake[is.na(SectorMake[, 1]), 1] <- SectorMake[is.na(SectorMake[, 1]), 2] - # Convert all values to numeric, assign row names - SectorMake <- as.data.frame(lapply(SectorMake[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorMake[-c(1:2), 1]) - # Replace NA with zero - SectorMake[is.na(SectorMake)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorMake, - data_name = paste0("Sector_Make_", year, "_AfterRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Make_", year, "_AfterRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Summary Make (After Redef) table from static Excel +getBEASummaryMakeAfterRedef <- function(year) { + end_year <- 2022 + for (y in 2017:end_year) { + ls <- unpackFile(y, filename="IOMake_After_Redefinitions", ioschema="Summary") + SummaryMake <- data.frame(ls["df"]) + SummaryMake <- processSummaryMatrix(SummaryMake) + writeFile(df = SummaryMake, year = y, + name = paste0("Summary_Make_", y, "_AfterRedef"), ls = ls, + schema_year = year) } } -# Get BEA Sector Use (PRO, After Redef, 2012 schema) table from static Excel -getBEASectorUsePROAfterRedef2012Schema <- function() { - # Download data - url <- getBEAIOTables()[["url"]] - date_accessed <- getBEAIOTables()[["date_accessed"]] - files <- getBEAIOTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "IOUse_After_Redefinitions_PRO") & - endsWith(files, "Sector.xlsx")] - FileName <- file.path("inst/extdata/AllTablesIO", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - for (year in 2010:end_year) { - SectorUse <- data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] - colnames(SectorUse) <- SectorUse[1, ] - colname_check <- is.na(colnames(SectorUse)) - colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] - # Fill NA in code column with corresponding name - SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] - # Convert all values to numeric, assign row names - SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorUse[-c(1:2), 1]) - # Replace NA with zero - SectorUse[is.na(SectorUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorUse, - data_name = paste0("Sector_Use_", year, "_PRO_AfterRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Use_", year, "_PRO_AfterRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) +# Get BEA Summary Use (PRO, After Redef) table from static Excel +getBEASummaryUsePROAfterRedef <- function(year) { + end_year <- 2022 + for (y in 2017:end_year) { + ls <- unpackFile(y, filename="IOUse_After_Redefinitions_PRO", ioschema="Summary") + SummaryUse <- data.frame(ls["df"]) + SummaryUse <- processSummaryMatrix(SummaryUse) + writeFile(df = SummaryUse, year = y, + name = paste0("Summary_Use_", y, "_PRO_AfterRedef"), ls = ls, + schema_year = year) } } -# Get BEA Detail Import (Before Redef, 2012 schema) from static Excel -getBEADetailImportBeforeRedef2012Schema <- function(year) { +# # Get BEA Sector Make (Before Redef, 2012 schema) table from static Excel +# getBEASectorMakeBeforeRedef2012Schema <- function() { +# # Download data +# url <- getBEAIOTables()[["url"]] +# date_accessed <- getBEAIOTables()[["date_accessed"]] +# files <- getBEAIOTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "IOMake_Before_Redefinitions") & +# endsWith(files, "Sector.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesIO", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Find latest data year +# file_split <- unlist(stringr::str_split(file, pattern = "_")) +# year_range <- file_split[length(file_split) - 1] +# end_year <- sub(".*-", "", year_range) +# # Load data +# for (year in 2010:end_year) { +# SectorMake <- data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorMake <- SectorMake[!is.na(SectorMake[, 2]), ] +# colnames(SectorMake) <- SectorMake[1, ] +# colname_check <- is.na(colnames(SectorMake)) +# colnames(SectorMake)[colname_check] <- SectorMake[2, colname_check] +# # Fill NA in code column with corresponding name +# SectorMake[is.na(SectorMake[, 1]), 1] <- SectorMake[is.na(SectorMake[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorMake <- as.data.frame(lapply(SectorMake[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorMake[-c(1:2), 1]) +# # Replace NA with zero +# SectorMake[is.na(SectorMake)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorMake, +# data_name = paste0("Sector_Make_", year, "_BeforeRedef")) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Make_", year, "_BeforeRedef"), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# } +# +# # Get BEA Sector Use (PRO, Before Redef, 2012 schema) table from static Excel +# getBEASectorUsePROBeforeRedef2012Schema <- function() { +# # Download data +# url <- getBEAIOTables()[["url"]] +# date_accessed <- getBEAIOTables()[["date_accessed"]] +# files <- getBEAIOTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & +# endsWith(files, "Sector.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesIO", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Find latest data year +# file_split <- unlist(stringr::str_split(file, pattern = "_")) +# year_range <- file_split[length(file_split) - 1] +# end_year <- sub(".*-", "", year_range) +# for (year in 2010:end_year) { +# SectorUse <- data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] +# colnames(SectorUse) <- SectorUse[1, ] +# colname_check <- is.na(colnames(SectorUse)) +# colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] +# # Fill NA in code column with corresponding name +# SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorUse[-c(1:2), 1]) +# # Replace NA with zero +# SectorUse[is.na(SectorUse)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorUse, +# data_name = paste0("Sector_Use_", year, "_PRO_BeforeRedef")) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Use_", year, "_PRO_BeforeRedef"), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# } +# +# # Get BEA Sector Use (PUR, Before Redef, 2012 schema) table from static Excel +# getBEASectorUsePURBeforeRedef2012Schema <- function(year) { +# # Download data +# url <- getBEAIOTables()[["url"]] +# date_accessed <- getBEAIOTables()[["date_accessed"]] +# files <- getBEAIOTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "IOUse_Before_Redefinitions_PUR") & +# endsWith(files, "Sector.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesIO", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Load data +# SectorUse <- data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] +# colnames(SectorUse) <- SectorUse[1, ] +# colname_check <- is.na(colnames(SectorUse)) +# colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] +# # Fill NA in code column with corresponding name +# SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorUse[-c(1:2), 1]) +# # Replace NA with zero +# SectorUse[is.na(SectorUse)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorUse, +# data_name = paste0("Sector_Use_", year, "_PUR_BeforeRedef")) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Use_", year, "_PUR_BeforeRedef"), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# +# # Get BEA Sector Make (After Redef, 2012 schema) table from static Excel +# getBEASectorMakeAfterRedef2012Schema <- function() { +# # Download data +# url <- getBEAIOTables()[["url"]] +# date_accessed <- getBEAIOTables()[["date_accessed"]] +# files <- getBEAIOTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "IOMake_After_Redefinitions") & +# endsWith(files, "Sector.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesIO", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Find latest data year +# file_split <- unlist(stringr::str_split(file, pattern = "_")) +# year_range <- file_split[length(file_split) - 1] +# end_year <- sub(".*-", "", year_range) +# # Load data +# for (year in 2010:end_year) { +# SectorMake <- data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorMake <- SectorMake[!is.na(SectorMake[, 2]), ] +# colnames(SectorMake) <- SectorMake[1, ] +# colname_check <- is.na(colnames(SectorMake)) +# colnames(SectorMake)[colname_check] <- SectorMake[2, colname_check] +# # Fill NA in code column with corresponding name +# SectorMake[is.na(SectorMake[, 1]), 1] <- SectorMake[is.na(SectorMake[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorMake <- as.data.frame(lapply(SectorMake[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorMake[-c(1:2), 1]) +# # Replace NA with zero +# SectorMake[is.na(SectorMake)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorMake, +# data_name = paste0("Sector_Make_", year, "_AfterRedef")) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Make_", year, "_AfterRedef"), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# } +# +# # Get BEA Sector Use (PRO, After Redef, 2012 schema) table from static Excel +# getBEASectorUsePROAfterRedef2012Schema <- function() { +# # Download data +# url <- getBEAIOTables()[["url"]] +# date_accessed <- getBEAIOTables()[["date_accessed"]] +# files <- getBEAIOTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "IOUse_After_Redefinitions_PRO") & +# endsWith(files, "Sector.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesIO", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Find latest data year +# file_split <- unlist(stringr::str_split(file, pattern = "_")) +# year_range <- file_split[length(file_split) - 1] +# end_year <- sub(".*-", "", year_range) +# for (year in 2010:end_year) { +# SectorUse <- data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] +# colnames(SectorUse) <- SectorUse[1, ] +# colname_check <- is.na(colnames(SectorUse)) +# colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] +# # Fill NA in code column with corresponding name +# SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorUse[-c(1:2), 1]) +# # Replace NA with zero +# SectorUse[is.na(SectorUse)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorUse, +# data_name = paste0("Sector_Use_", year, "_PRO_AfterRedef")) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Use_", year, "_PRO_AfterRedef"), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# } + +# Get BEA Detail Import (Before Redef schema) from static Excel +getBEADetailImportBeforeRedef <- function(year) { # Download data - file <- "ImportMatrices_Before_Redefinitions_DET_2007_2012.xlsx" - url <- file.path("https://apps.bea.gov/industry/xls/io-annual", file) - FileName <- file.path("inst/extdata/", file) + file <- paste0("ImportMatrices_Before_Redefinitions_DET_", year, ".xlsx") + url <- file.path(url_ls["imports"], file) + FileName <- file.path(dir, "/", file) if (!file.exists(FileName)) { utils::download.file(url, FileName, mode = "wb") } # Load data DetailImport <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(year))) - # Trim table, assign column names - DetailImport <- DetailImport[!is.na(DetailImport[, 2]), ] - colnames(DetailImport) <- DetailImport[1, ] - colname_check <- is.na(colnames(DetailImport)) - colnames(DetailImport)[colname_check] <- DetailImport[2, colname_check] - # Fill NA in code column with corresponding name - DetailImport[is.na(DetailImport[, 1]), 1] <- DetailImport[is.na(DetailImport[, 1]), 2] - # Convert all values to numeric, assign row names - DetailImport <- as.data.frame(lapply(DetailImport[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailImport[-1, 1]) - # Replace NA with zero - DetailImport[is.na(DetailImport)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailImport, - data_name = paste0("Detail_Import_", year, "_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Import_", year, "_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = "unknown", - date_accessed = as.character(as.Date(file.mtime(FileName)))) + DetailImport <- processDetailMatrix(DetailImport) + ls <- list("url" = url, + "date_accessed" = as.character(as.Date(file.mtime(FileName))), + "date_last_modified" = "unknown") + writeFile(df = DetailImport, year = year, + name = paste0("Detail_Import_", year, "_BeforeRedef"), ls = ls, + schema_year = year) } -# Get BEA Summary Import (Before Redef, 2012 schema) from static Excel -getBEASummaryImportBeforeRedef2012Schema <- function() { +# Get BEA Summary Import (Before Redef) from static Excel +getBEASummaryImportBeforeRedef <- function(year) { # Download data - file <- "ImportMatrices_Before_Redefinitions_SUM_1997-2020.xlsx" - url <- file.path("https://apps.bea.gov/industry/xls/io-annual", file) - FileName <- file.path("inst/extdata/", file) + file <- "ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx" + url <- file.path(url_ls["imports"], file) + FileName <- file.path(dir, file) if (!file.exists(FileName)) { utils::download.file(url, FileName, mode = "wb") } - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- sub(".xlsx", "", file_split[length(file_split)]) - end_year <- sub(".*-", "", year_range) + end_year <- 2022 # Load data - for (year in 2010:end_year) { + for (y in 2017:end_year) { SummaryImport <- data.frame(readxl::read_excel(FileName, sheet = as.character(year))) - # Trim table, assign column names - SummaryImport <- SummaryImport[!is.na(SummaryImport[, 2]), ] - colnames(SummaryImport) <- SummaryImport[1, ] - colname_check <- is.na(colnames(SummaryImport)) - colnames(SummaryImport)[colname_check] <- SummaryImport[2, colname_check] - # Fill NA in code column with corresponding name - SummaryImport[is.na(SummaryImport[, 1]), 1] <- SummaryImport[is.na(SummaryImport[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryImport <- as.data.frame(lapply(SummaryImport[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryImport[-c(1:2), 1]) - # Replace NA with zero - SummaryImport[is.na(SummaryImport)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryImport, - data_name = paste0("Summary_Import_", year, "_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Import_", year, "_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = "2022-02-11", # obtained from notes on BEA webpage about "BEA's use tables were updated on Feb.11, 2022." - date_accessed = as.character(as.Date(file.mtime(FileName)))) + SummaryImport <- processSummaryMatrix(SummaryImport) + ls <- list("url" = url, + "date_accessed" = as.character(as.Date(file.mtime(FileName))), + "date_last_modified" = "2024-02-01") # page last modified + writeFile(df = SummaryImport, year = y, + name = paste0("Summary_Import_", y, "_BeforeRedef"), ls = ls, + schema_year = year) } } -# Download all GDP tables from BEA -getBEAUnderlyingTables <- function() { - # Create the placeholder file - UnderlyingTables <- "inst/extdata/UGdpByInd.zip" - # Download all BEA IO tables into the placeholder file - url <- "https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip" - if (!file.exists(UnderlyingTables)) { - utils::download.file(url, UnderlyingTables, mode = "wb") - } - # Get the name of all files in the zip archive - files <- unzip(UnderlyingTables, list = TRUE) - fname <- files[files$Length > 0, ]$Name - if (all(fname == basename(fname))) { - exdir <- "inst/extdata/UGdpByInd" - } else { - exdir <- "inst/extdata/" - } - # Unzip the file to the designated directory - unzip(UnderlyingTables, files = fname, exdir = exdir, - overwrite = TRUE, setTimes = TRUE) - # Create output - ls <- list("url" = url, - "date_accessed" = as.character(as.Date(file.mtime(UnderlyingTables))), - "files" = basename(fname)) - return(ls) -} - -# Get Detail BEA Gross Output (2012 schema) since 2002 -getBEADetailGrossOutput2012Schema <- function() { - # Download data - files <- getBEAUnderlyingTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "GrossOutput")] - FileName <- file.path("inst/extdata/UGdpByInd", file) - # Load data - content <- na.omit(as.data.frame(readxl::read_excel(FileName, - sheet = "Contents", - na = ""))) - sheet <- paste0(content[content$Title == - "U.Gross Output by Industry - Detail Level", "Code"], - "-A") - DetailGrossOutput <- as.data.frame(readxl::read_excel(FileName, - sheet = sheet)) - # Trim table, assign column names - DetailGrossOutput <- DetailGrossOutput[!is.na(DetailGrossOutput[, 4]), ] - colnames(DetailGrossOutput) <- DetailGrossOutput[1, ] - Gross_Output_Detail_Industry <- DetailGrossOutput[-1, 2] - # Convert all values to numeric, assign row names - DetailGrossOutput <- cbind.data.frame(Gross_Output_Detail_Industry, - lapply(DetailGrossOutput[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2002 - col_2002 <- which(colnames(DetailGrossOutput) == "2002") - DetailGrossOutput <- DetailGrossOutput[, c(1, col_2002:ncol(DetailGrossOutput))] - return(DetailGrossOutput) -} - -# Get Summary BEA Gross Output (2012 schema) since 2002 -getBEASummaryGrossOutput2012Schema <- function() { - # Download data - files <- getBEAUnderlyingTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "GrossOutput")] - FileName <- file.path("inst/extdata/UGdpByInd", file) - # Load data - content <- na.omit(as.data.frame(readxl::read_excel(FileName, - sheet = "Contents", - na = ""))) - sheet <- paste0(content[content$Title == "U.Gross Output by Industry", "Code"], - "-A") - SummaryGrossOutput <- as.data.frame(readxl::read_excel(FileName, - sheet = sheet)) - # Trim table, assign column names - SummaryGrossOutput <- SummaryGrossOutput[!is.na(SummaryGrossOutput[, 4]), ] - colnames(SummaryGrossOutput) <- SummaryGrossOutput[1, ] - Gross_Output_Industry <- SummaryGrossOutput[-1, 2] - # Convert all values to numeric, assign row names - SummaryGrossOutput <- cbind.data.frame(Gross_Output_Industry, - lapply(SummaryGrossOutput[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2002 - col_2002 <- which(colnames(SummaryGrossOutput) == "2002") - SummaryGrossOutput <- SummaryGrossOutput[, c(1, col_2002:ncol(SummaryGrossOutput))] - return(SummaryGrossOutput) -} -# Get Sector BEA Gross Output (2012 schema) since 2002 -getBEASectorGrossOutput2012Schema <- function() { +#' Get Detail BEA Gross Output +#' @param level, str "Detail", "Summary", or "Sector" +getBEAGrossOutput <- function(level) { # Download data files <- getBEAUnderlyingTables()[["files"]] # Prepare file name file <- files[startsWith(files, "GrossOutput")] - FileName <- file.path("inst/extdata/UGdpByInd", file) + FileName <- file.path(dir, "UGdpByInd", file) # Load data content <- na.omit(as.data.frame(readxl::read_excel(FileName, sheet = "Contents", na = ""))) - sheet <- paste0(content[content$Title == "U.Gross Output by Industry", "Code"], - "-A") - SectorGrossOutput <- as.data.frame(readxl::read_excel(FileName, - sheet = sheet)) + if(level=="Detail"){ + tag = "U.Gross Output by Industry - Detail Level" + } else { + tag = "U.Gross Output by Industry" + } + sheet <- paste0(content[content$Title == tag, "Code"], "-A") + GrossOutput <- as.data.frame(readxl::read_excel(FileName, sheet = sheet)) # Trim table, assign column names - SectorGrossOutput <- SectorGrossOutput[!is.na(SectorGrossOutput[, 4]), ] - colnames(SectorGrossOutput) <- SectorGrossOutput[1, ] - Gross_Output_Industry <- SectorGrossOutput[-1, 2] + GrossOutput <- GrossOutput[!is.na(GrossOutput[, 4]), ] + colnames(GrossOutput) <- GrossOutput[1, ] + sector <- GrossOutput[-1, 2] # Convert all values to numeric, assign row names - SectorGrossOutput <- cbind.data.frame(Gross_Output_Industry, - lapply(SectorGrossOutput[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2002 - col_2002 <- which(colnames(SectorGrossOutput) == "2002") - SectorGrossOutput <- SectorGrossOutput[, c(1, col_2002:ncol(SectorGrossOutput))] - return(SectorGrossOutput) + GrossOutput <- cbind.data.frame(sector, + lapply(GrossOutput[-1, -c(1:3)], as.numeric)) + return(GrossOutput) } -# Map gross output ($) from GDP industries to IO industries (2012 schema) at Detail, Summary, and Sector IO levels. -mapBEAGrossOutputtoIOIndustry2012Schema <- function() { - # Download data - url <- getBEAUnderlyingTables()[["url"]] - date_accessed <- getBEAUnderlyingTables()[["date_accessed"]] - files <- getBEAUnderlyingTables()[["files"]] - FileName <- file.path("inst/extdata/UGdpByInd", - files[startsWith(files, "GrossOutput")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# Map gross output ($) from GDP industries to IO industries at Detail, Summary, and Sector IO levels. +mapBEAGrossOutputtoIOIndustry <- function(schema_year) { + ls <- getBEAUnderlyingTables() + FileName <- file.path(dir, "UGdpByInd", + ls[["files"]][startsWith(ls[["files"]], "GrossOutput")]) + ls["date_last_modified"] <- as.character(as.Date(file.mtime(FileName))) ### Detail ### - DetailGrossOutput <- getBEADetailGrossOutput2012Schema() + DetailGrossOutput <- getBEAGrossOutput(level="Detail") # Determine year range year_range <- colnames(DetailGrossOutput)[2:ncol(DetailGrossOutput)] # Map BEA Detail industry code to IO code Detail_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_DetailGDPIndustrytoIO2012Schema.csv", + "Crosswalk_DetailGDPIndustrytoIO.csv", package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE, quote = "\"") + Detail_mapping <- Detail_mapping[,c("Gross_Output_Detail_Industry", + paste0("BEA_", schema_year, "_Detail_Code"))] + colnames(Detail_mapping) <- c("sector", "BEA_Detail_Code") DetailGrossOutputIO <- merge(Detail_mapping, DetailGrossOutput, - by = "Gross_Output_Detail_Industry", + by = "sector", all.y = TRUE) # Aggregate by BEA Detail industry code DetailGrossOutputIO <- stats::aggregate(DetailGrossOutputIO[, year_range], - by = list(DetailGrossOutputIO$BEA_2012_Detail_Code), + by = list(DetailGrossOutputIO$BEA_Detail_Code), sum) # Assign sector code to row names rownames(DetailGrossOutputIO) <- DetailGrossOutputIO[, 1] DetailGrossOutputIO[, 1] <- NULL ### Summary ### - SummaryGrossOutput <- getBEASummaryGrossOutput2012Schema() + SummaryGrossOutput <- getBEAGrossOutput(level="Summary") # Map BEA Summary industry code to IO code Summary_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_SummaryGDPIndustrytoIO2012Schema.csv", + paste0("Crosswalk_SummaryGDPIndustrytoIO", 2012, "Schema.csv"), package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(Summary_mapping) <- c("sector", "BEA_Summary_Code") + ## TODO can update crosswalk file for 2017, 2017 summary schema is same as 2012 ^^ SummaryGrossOutputIO <- cbind(Summary_mapping, SummaryGrossOutput) # Keep Summary rows - SummaryGrossOutputIO <- SummaryGrossOutputIO[!SummaryGrossOutputIO$BEA_2012_Summary_Code == "", - c("BEA_2012_Summary_Code", year_range)] + SummaryGrossOutputIO <- SummaryGrossOutputIO[!SummaryGrossOutputIO$BEA_Summary_Code == "", + c("BEA_Summary_Code", year_range)] # Assign sector code to row names rownames(SummaryGrossOutputIO) <- SummaryGrossOutputIO[, 1] SummaryGrossOutputIO[, 1] <- NULL ### Sector ### - SectorGrossOutput <- getBEASectorGrossOutput2012Schema() + SectorGrossOutput <- getBEAGrossOutput(level="Sector") # Map BEA Sector industry code to IO code Sector_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_SectorGDPIndustrytoIO2012Schema.csv", + paste0("Crosswalk_SectorGDPIndustrytoIO", 2012, "Schema.csv"), package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(Sector_mapping) <- c("sector", "BEA_Sector_Code") + ## TODO can update crosswalk file for 2017, 2017 sector schema is same as 2012 ^^ SectorGrossOutputIO <- cbind(Sector_mapping, SectorGrossOutput) # Keep Summary rows - SectorGrossOutputIO <- SectorGrossOutputIO[!SectorGrossOutputIO$BEA_2012_Sector_Code == "", - c("BEA_2012_Sector_Code", year_range)] + SectorGrossOutputIO <- SectorGrossOutputIO[!SectorGrossOutputIO$BEA_Sector_Code == "", + c("BEA_Sector_Code", year_range)] # Assign sector code to row names rownames(SectorGrossOutputIO) <- SectorGrossOutputIO[, 1] SectorGrossOutputIO[, 1] <- NULL ### Save and Document data - ls <- list("Detail_GrossOutput_IO" = DetailGrossOutputIO, + dfs <- list("Detail_GrossOutput_IO" = DetailGrossOutputIO, "Summary_GrossOutput_IO" = SummaryGrossOutputIO, "Sector_GrossOutput_IO" = SectorGrossOutputIO) - for (data_name in names(ls)) { - # Write data to .rda - writeDatatoRDA(data = ls[[data_name]], data_name = data_name) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = data_name, - year = year_range, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + for (data_name in names(dfs)) { + writeFile(df = dfs[[data_name]], year = year_range, + name = data_name, ls = ls, + schema_year = schema_year) } } -# Get Detail BEA Chain-Type Price Indexes (CPI) (2012 schema) since 2002 -getBEADetailCPI2012Schema <- function() { +#' Get Detail BEA Chain-Type Price Indexes (CPI) +#' @param level, str "Detail", "Summary", or "Sector" +getBEACPI <- function(level) { # Download data files <- getBEAUnderlyingTables()[["files"]] # Prepare file name file <- files[startsWith(files, "GrossOutput")] - FileName <- file.path("inst/extdata/UGdpByInd", file) + FileName <- file.path(dir, "UGdpByInd", file) # Load data content <- na.omit(as.data.frame(readxl::read_excel(FileName, sheet = "Contents", na = ""))) - dataname <- "U.Chain-Type Price Indexes for Gross Output by Industry" - sheet <- paste0(content[content$Title == paste(dataname, "- Detail Level"), "Code"], - "-A") - DetailCPI <- as.data.frame(readxl::read_excel(FileName, sheet = sheet)) + if(level=="Detail"){ + tag = "U.Chain-Type Price Indexes for Gross Output by Industry - Detail Level" + } else { + tag = "U.Chain-Type Price Indexes for Gross Output by Industry" + } + sheet <- paste0(content[content$Title == tag, "Code"], "-A") + CPI <- as.data.frame(readxl::read_excel(FileName, sheet = sheet)) # Trim table, assign column names - DetailCPI <- DetailCPI[!is.na(DetailCPI[, 4]), ] - colnames(DetailCPI) <- DetailCPI[1, ] - Gross_Output_Detail_Industry <- DetailCPI[-1, 2] + CPI <- CPI[!is.na(CPI[, 4]), ] + colnames(CPI) <- CPI[1, ] + sector <- CPI[-1, 2] # Convert all values to numeric, assign row names - DetailCPI <- cbind.data.frame(Gross_Output_Detail_Industry, - lapply(DetailCPI[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2002 - col_2002 <- which(colnames(DetailCPI) == "2002") - DetailCPI <- DetailCPI[, c(1, col_2002:ncol(DetailCPI))] - return(DetailCPI) + CPI <- cbind.data.frame(sector, + lapply(CPI[-1, -c(1:3)], as.numeric)) + return(CPI) } -# Get Summary BEA Chain-Type Price Indexes (CPI) (2012 schema) since 2002 -getBEASummaryCPI2012Schema <- function() { - # Download data - files <- getBEAUnderlyingTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "GrossOutput")] - FileName <- file.path("inst/extdata/UGdpByInd", file) - # Load data - content <- na.omit(as.data.frame(readxl::read_excel(FileName, - sheet = "Contents", - na = ""))) - dataname <- "U.Chain-Type Price Indexes for Gross Output by Industry" - sheet <- paste0(content[content$Title == dataname, "Code"], "-A") - SummaryCPI <- as.data.frame(readxl::read_excel(FileName, sheet = sheet)) - # Trim table, assign column names - SummaryCPI <- SummaryCPI[!is.na(SummaryCPI[, 4]), ] - colnames(SummaryCPI) <- SummaryCPI[1, ] - Gross_Output_Industry <- SummaryCPI[-1, 2] - # Convert all values to numeric, assign row names - SummaryCPI <- cbind.data.frame(Gross_Output_Industry, - lapply(SummaryCPI[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2002 - col_2002 <- which(colnames(SummaryCPI) == "2002") - SummaryCPI <- SummaryCPI[, c(1, col_2002:ncol(SummaryCPI))] - return(SummaryCPI) -} -# Get Sector BEA Chain-Type Price Indexes (CPI) (2012 schema) since 2002 -getBEASectorCPI2012Schema <- function() { - # Download data - files <- getBEAUnderlyingTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "GrossOutput")] - FileName <- file.path("inst/extdata/UGdpByInd", file) - # Load data - content <- na.omit(as.data.frame(readxl::read_excel(FileName, - sheet = "Contents", - na = ""))) - dataname <- "U.Chain-Type Price Indexes for Gross Output by Industry" - sheet <- paste0(content[content$Title == dataname, "Code"], "-A") - SectorCPI <- as.data.frame(readxl::read_excel(FileName, sheet = sheet)) - # Trim table, assign column names - SectorCPI <- SectorCPI[!is.na(SectorCPI[, 4]), ] - colnames(SectorCPI) <- SectorCPI[1, ] - Gross_Output_Industry <- SectorCPI[-1, 2] - # Convert all values to numeric, assign row names - SectorCPI <- cbind.data.frame(Gross_Output_Industry, - lapply(SectorCPI[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2002 - col_2002 <- which(colnames(SectorCPI) == "2002") - SectorCPI <- SectorCPI[, c(1, col_2002:ncol(SectorCPI))] - return(SectorCPI) -} - -# Map CPI from GDP industries to IO industries (2012 schema) at Detail, Summary, and Sector IO levels. -mapBEACPItoIOIndustry2012Schema <- function() { - # Download data - url <- getBEAUnderlyingTables()[["url"]] - date_accessed <- getBEAUnderlyingTables()[["date_accessed"]] - files <- getBEAUnderlyingTables()[["files"]] - FileName <- file.path("inst/extdata/UGdpByInd", - files[startsWith(files, "GrossOutput")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# Map CPI from GDP industries to IO industries at Detail, Summary, and Sector IO levels. +mapBEACPItoIOIndustry <- function(schema_year) { + ls <- getBEAUnderlyingTables() + FileName <- file.path(dir, "UGdpByInd", + ls[["files"]][startsWith(ls[["files"]], "GrossOutput")]) + ls["date_last_modified"] <- as.character(as.Date(file.mtime(FileName))) ### Detail ### - DetailCPI <- getBEADetailCPI2012Schema() - DetailCPI$Gross_Output_Detail_Industry <- sub("’", "'", - DetailCPI$Gross_Output_Detail_Industry) + DetailCPI <- getBEACPI(level="Detail") + DetailCPI$sector <- sub("’", "'", DetailCPI$sector) # Determine year range year_range <- colnames(DetailCPI)[2:ncol(DetailCPI)] # Map BEA Detail industry code to IO code Detail_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_DetailGDPIndustrytoIO2012Schema.csv", + "Crosswalk_DetailGDPIndustrytoIO.csv", package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE, quote = "\"") Detail_mapping$Gross_Output_Detail_Industry <- sub("’", "'", Detail_mapping$Gross_Output_Detail_Industry) + Detail_mapping <- Detail_mapping[,c("Gross_Output_Detail_Industry", + paste0("BEA_", schema_year, "_Detail_Code"))] + colnames(Detail_mapping) <- c("sector", "BEA_Detail_Code") DetailCPIIO <- merge(Detail_mapping, DetailCPI, - by = "Gross_Output_Detail_Industry", all.y = TRUE) + by = "sector", all.y = TRUE) + if(sum(is.na(DetailCPIIO$BEA_Detail_Code)) > 0){ + print('ERROR: missing mappings') + DetailCPIIO$BEA_Detail_Code[is.na(DetailCPIIO$BEA_Detail_Code)] <- "missing" + } # Adjust (weighted average) CPI based on DetailGrossOutput # DetailGrossOutput - DetailGrossOutput <- getBEADetailGrossOutput2012Schema() + DetailGrossOutput <- getBEAGrossOutput(level="Detail") # Merge CPI with GrossOutput - DetailCPIIO <- merge(DetailCPIIO, DetailGrossOutput, by = "Gross_Output_Detail_Industry") + DetailCPIIO <- merge(DetailCPIIO, DetailGrossOutput, by = "sector") # Calculate weighted average of CPI - for (code in unique(DetailCPIIO[, "BEA_2012_Detail_Code"])) { - for (year in year_range) { - row <- DetailCPIIO$BEA_2012_Detail_Code == code - DetailCPIIO[row, year] <- stats::weighted.mean(DetailCPIIO[row, paste(year, "x", sep = ".")], - DetailCPIIO[row, paste(year, "y", sep = ".")]) + for (code in unique(DetailCPIIO[, "BEA_Detail_Code"])) { + for (y in year_range) { + row <- DetailCPIIO$BEA_Detail_Code == code + DetailCPIIO[row, y] <- stats::weighted.mean(DetailCPIIO[row, paste(y, "x", sep = ".")], + DetailCPIIO[row, paste(y, "y", sep = ".")]) } } - # Aggregate CPI by BEA_2012_Detail_Code + # Aggregate CPI by BEA_Detail_Code DetailCPIIO <- stats::aggregate(DetailCPIIO[, year_range], - by = list(DetailCPIIO$BEA_2012_Detail_Code), + by = list(DetailCPIIO$BEA_Detail_Code), mean) # Assign sector code to row names rownames(DetailCPIIO) <- DetailCPIIO[, 1] DetailCPIIO[, 1] <- NULL ### Summary ### - SummaryCPI <- getBEASummaryCPI2012Schema() + SummaryCPI <- getBEACPI(level="Summary") # Map BEA Summary industry code to IO code Summary_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_SummaryGDPIndustrytoIO2012Schema.csv", + paste0("Crosswalk_SummaryGDPIndustrytoIO", 2012,"Schema.csv"), package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(Summary_mapping) <- c("sector", "BEA_Summary_Code") + ## TODO can update crosswalk file for 2017, 2017 summary schema is same as 2012 ^^ SummaryCPIIO <- cbind(Summary_mapping, SummaryCPI) # Keep Summary rows - SummaryCPIIO <- SummaryCPIIO[!SummaryCPIIO$BEA_2012_Summary_Code == "", - c("BEA_2012_Summary_Code", year_range)] + SummaryCPIIO <- SummaryCPIIO[!SummaryCPIIO$BEA_Summary_Code == "", + c("BEA_Summary_Code", year_range)] # Assign sector code to row names rownames(SummaryCPIIO) <- SummaryCPIIO[, 1] SummaryCPIIO[, 1] <- NULL ### Sector ### - SectorCPI <- getBEASectorCPI2012Schema() + SectorCPI <- getBEACPI(level="Sector") # Map BEA Sector industry code to IO code Sector_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_SectorGDPIndustrytoIO2012Schema.csv", + paste0("Crosswalk_SectorGDPIndustrytoIO", 2012,"Schema.csv"), package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(Sector_mapping) <- c("sector", "BEA_Sector_Code") + ## TODO can update crosswalk file for 2017, 2017 sector schema is same as 2012 ^^ SectorCPIIO <- cbind(Sector_mapping, SectorCPI) # Keep Sector rows - SectorCPIIO <- SectorCPIIO[!SectorCPIIO$BEA_2012_Sector_Code == "", - c("BEA_2012_Sector_Code", year_range)] + SectorCPIIO <- SectorCPIIO[!SectorCPIIO$BEA_Sector_Code == "", + c("BEA_Sector_Code", year_range)] # Assign sector code to row names rownames(SectorCPIIO) <- SectorCPIIO[, 1] SectorCPIIO[, 1] <- NULL ### Save and Document data - ls <- list("Detail_CPI_IO" = DetailCPIIO, + dfs <- list("Detail_CPI_IO" = DetailCPIIO, "Summary_CPI_IO" = SummaryCPIIO, "Sector_CPI_IO" = SectorCPIIO) - for (data_name in names(ls)) { - # Write data to .rda - writeDatatoRDA(data = ls[[data_name]], data_name = data_name) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = data_name, - year = year_range, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + for (data_name in names(dfs)) { + writeFile(df = dfs[[data_name]], year = year_range, + name = data_name, ls = ls, + schema_year = schema_year) } } -#' Get Summary BEA Value Added (2012 schema) since 2007 -getBEASummaryValueAdded2012Schema <- function() { +#' Get Summary BEA Value Added +getBEASummaryValueAdded <- function() { # Download data files <- getBEAUnderlyingTables()[["files"]] # Prepare file name file <- files[startsWith(files, "ValueAdded")] - FileName <- file.path("inst/extdata/UGdpByInd", file) + FileName <- file.path(dir, "UGdpByInd", file) # Load data content <- na.omit(as.data.frame(readxl::read_excel(FileName, sheet = "Contents", @@ -1169,97 +819,62 @@ getBEASummaryValueAdded2012Schema <- function() { SummaryValueAdded <- cbind.data.frame(Industry, lapply(SummaryValueAdded[-1, -c(1:3)], as.numeric)) - # Keep columns since 2007 - col_2007 <- which(colnames(SummaryValueAdded) == "2007") - SummaryValueAdded <- SummaryValueAdded[, c(1, col_2007:ncol(SummaryValueAdded))] return(SummaryValueAdded) } -#' Get Sector BEA Value Added (2012 schema) since 2007 -getBEASectorValueAdded2012Schema <- function() { - # Download data - files <- getBEAUnderlyingTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "ValueAdded")] - FileName <- file.path("inst/extdata/UGdpByInd", file) - # Load data - content <- na.omit(as.data.frame(readxl::read_excel(FileName, - sheet = "Contents", - na = ""))) - dataname <- "U.Value Added by Industry" - sheet <- paste0(content[content$Title == dataname, "Code"], "-A") - SectorValueAdded <- as.data.frame(readxl::read_excel(FileName, sheet = sheet)) - # Trim table, assign column names - SectorValueAdded <- SectorValueAdded[!is.na(SectorValueAdded[, 4]), ] - colnames(SectorValueAdded) <- SectorValueAdded[1, ] - Industry <- SectorValueAdded[-1, 2] - # Convert all values to numeric, assign row names - SectorValueAdded <- cbind.data.frame(Industry, - lapply(SectorValueAdded[-1, -c(1:3)], - as.numeric)) - # Keep columns since 2007 - col_2007 <- which(colnames(SectorValueAdded) == "2007") - SectorValueAdded <- SectorValueAdded[, c(1, col_2007:ncol(SectorValueAdded))] - return(SectorValueAdded) -} -#' Map Value Added ($) from GDP industries to IO industries (2012 schema) -#' since 2007 at Summary and Sector IO levels -mapBEAValueAddedtoIOIndustry2012Schema <- function() { +#' Map Value Added ($) from GDP industries to IO industries +#' at Summary and Sector IO levels +mapBEAValueAddedtoIOIndustry <- function(schema_year) { # Download data - url <- getBEAUnderlyingTables()[["url"]] - date_accessed <- getBEAUnderlyingTables()[["date_accessed"]] - files <- getBEAUnderlyingTables()[["files"]] - FileName <- file.path("inst/extdata/UGdpByInd", - files[startsWith(files, "ValueAdded")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) + ls <- getBEAUnderlyingTables() + FileName <- file.path(dir, "UGdpByInd", + ls[["files"]][startsWith(ls[["files"]], "ValueAdded")]) + ls["date_last_modified"] <- as.character(as.Date(file.mtime(FileName))) ### Summary ### - SummaryValueAdded <- getBEASummaryValueAdded2012Schema() + SummaryValueAdded <- getBEASummaryValueAdded() # Determine year range year_range <- colnames(SummaryValueAdded)[2:ncol(SummaryValueAdded)] # Map BEA Summary industry code to IO code Summary_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_SummaryGDPIndustrytoIO2012Schema.csv", + paste0("Crosswalk_SummaryGDPIndustrytoIO", 2012,"Schema.csv"), package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(Summary_mapping) <- c("Gross_Output_Industry","BEA_Summary_Code") + ## TODO can update crosswalk file for 2017, 2017 summary schema is same as 2012 ^^ SummaryValueAddedIO <- cbind(Summary_mapping, SummaryValueAdded) # Keep Summary rows - SummaryValueAddedIO <- SummaryValueAddedIO[!SummaryValueAddedIO$BEA_2012_Summary_Code == "", - c("BEA_2012_Summary_Code", year_range)] + SummaryValueAddedIO <- SummaryValueAddedIO[!SummaryValueAddedIO$BEA_Summary_Code == "", + c("BEA_Summary_Code", year_range)] # Assign sector code to row names rownames(SummaryValueAddedIO) <- SummaryValueAddedIO[, 1] SummaryValueAddedIO[, 1] <- NULL ### Sector ### - SectorValueAdded <- getBEASectorValueAdded2012Schema() + SectorValueAdded <- getBEASummaryValueAdded() # Map BEA Sector industry code to IO code Sector_mapping <- utils::read.table(system.file("extdata", - "Crosswalk_SectorGDPIndustrytoIO2012Schema.csv", + paste0("Crosswalk_SectorGDPIndustrytoIO", 2012,"Schema.csv"), package = "useeior"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(Sector_mapping) <- c("Gross_Output_Industry","BEA_Sector_Code") + ## TODO can update crosswalk file for 2017, 2017 sector schema is same as 2012 ^^ SectorValueAddedIO <- cbind(Sector_mapping, SectorValueAdded) # Keep Sector rows - SectorValueAddedIO <- SectorValueAddedIO[!SectorValueAddedIO$BEA_2012_Sector_Code == "", - c("BEA_2012_Sector_Code", year_range)] + SectorValueAddedIO <- SectorValueAddedIO[!SectorValueAddedIO$BEA_Sector_Code == "", + c("BEA_Sector_Code", year_range)] # Assign sector code to row names rownames(SectorValueAddedIO) <- SectorValueAddedIO[, 1] SectorValueAddedIO[, 1] <- NULL ### Save and Document data - ls <- list("Summary_ValueAdded_IO" = SummaryValueAddedIO, + dfs <- list("Summary_ValueAdded_IO" = SummaryValueAddedIO, "Sector_ValueAdded_IO" = SectorValueAddedIO) - for (data_name in names(ls)) { - # Write data to .rda - writeDatatoRDA(data = ls[[data_name]], data_name = data_name) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = data_name, - year = year_range, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + for (data_name in names(dfs)) { + writeFile(df = dfs[[data_name]], year = year_range, + name = data_name, ls = ls, + schema_year = schema_year) } } @@ -1284,68 +899,93 @@ cleanSectorNames <- function(df) { return(df) } -# Get BEA (Detail/Summary/Sector) Code and Name under 2012 schema -getBEACodeName2012Schema <- function() { +# Get BEA (Detail/Summary/Sector) Code and Name +getBEACodeName <- function(schema_year) { # Download data + # Get the data from AllTablesIO url <- getBEAIOTables()[["url"]] date_accessed <- getBEAIOTables()[["date_accessed"]] files <- getBEAIOTables()[["files"]] - ### Detail ### - # Load data - FileName <- file.path("inst/extdata/AllTablesIO", + FileName <- file.path(dir, "AllTableIO", files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & - endsWith(files, "Detail.xlsx")]) + endsWith(files, "Detail.xlsx")]) + + # Get the data from AllTablesSUP + # url <- getBEASupplyUseTables()[["url"]] + # date_accessed <- getBEASupplyUseTables()[["date_accessed"]] + # files <- getBEASupplyUseTables()[["files"]] + # FileName <- file.path(dir, "AllTablesSUP", + # files[startsWith(files, paste0("Use_SUT_Framework_",schema_year,"_DET.xlsx"))]) + date_last_modified <- as.character(as.Date(file.mtime(FileName))) - BEADetail <- as.data.frame(readxl::read_excel(FileName, sheet = "2012")) + + ### Detail ### + # Load data + BEADetail <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(schema_year))) ## Commodity & Value Added DetailCommVA <- BEADetail[!is.na(BEADetail[, 2]), c(1:2)][-1, ] commodity_range <- c(1:(which(DetailCommVA[, 1] == "T005") - 1)) + # value added range in MUT Use table va_range <- c((length(commodity_range) + 2):(which(DetailCommVA[, 1] == "T006") - 1)) + # Value added range from SUT + # va_range <- c((length(commodity_range) + 2):(which(DetailCommVA[, 1] == "VABAS") - 1)) + # va_range <- append(va_range,c((max(va_range) + 3):(which(DetailCommVA[, 1] == "VAPRO") - 1))) + # Commodity BEADetailCommodityCodeName <- DetailCommVA[commodity_range, ] - colnames(BEADetailCommodityCodeName) <- c("BEA_2012_Detail_Commodity_Code", - "BEA_2012_Detail_Commodity_Name") + colnames(BEADetailCommodityCodeName) <- c(paste0("BEA_",schema_year,"_Detail_Commodity_Code"), + paste0("BEA_",schema_year,"_Detail_Commodity_Name")) rownames(BEADetailCommodityCodeName) <- NULL # Value Added BEADetailValueAddedCodeName <- DetailCommVA[va_range, ] - colnames(BEADetailValueAddedCodeName) <- c("BEA_2012_Detail_ValueAdded_Code", - "BEA_2012_Detail_ValueAdded_Name") + colnames(BEADetailValueAddedCodeName) <- c(paste0("BEA_",schema_year,"_Detail_ValueAdded_Code"), + paste0("BEA_",schema_year,"_Detail_ValueAdded_Name")) rownames(BEADetailValueAddedCodeName) <- NULL ## Industry & Final Demand DetailIndFD <- as.data.frame(t(BEADetail[!is.na(BEADetail[, 3]), ][2:1, -c(1:2)])) industry_range <- c(1:(which(DetailIndFD[, 1] == "T001") - 1)) - fd_range <- c((length(industry_range) + 2):(which(DetailIndFD[, 1] == "T004") - 1)) + + # FD range from MUT Use + fd_range <- c((length(industry_range) + 2):(which(DetailIndFD[, 2] == "Total Final Uses (GDP)") - 1)) + + # FD range from SUT Use + # fd_range <- c((length(industry_range) + 2):(which(DetailIndFD[, 1] == "T019") - 1)) + # Industry BEADetailIndustryCodeName <- DetailIndFD[industry_range, ] - colnames(BEADetailIndustryCodeName) <- c("BEA_2012_Detail_Industry_Code", - "BEA_2012_Detail_Industry_Name") + colnames(BEADetailIndustryCodeName) <- c(paste0("BEA_",schema_year,"_Detail_Industry_Code"), + paste0("BEA_",schema_year,"_Detail_Industry_Name")) rownames(BEADetailIndustryCodeName) <- NULL # Final Demand BEADetailFinalDemandCodeName <- DetailIndFD[fd_range, ] - colnames(BEADetailFinalDemandCodeName) <- c("BEA_2012_Detail_FinalDemand_Code", - "BEA_2012_Detail_FinalDemand_Name") + colnames(BEADetailFinalDemandCodeName) <- c(paste0("BEA_",schema_year,"_Detail_FinalDemand_Code"), + paste0("BEA_",schema_year,"_Detail_FinalDemand_Name")) rownames(BEADetailFinalDemandCodeName) <- NULL ### Summary ### # Load data - FileName <- file.path("inst/extdata/AllTablesIO", + FileName <- file.path(dir, "AllTableIO", files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & - endsWith(files, "Summary.xlsx")]) + endsWith(files, "Summary.xlsx")]) + # FileName <- file.path(dir, "AllTablesSUP", + # files[startsWith(files, "Use_Tables") & + # endsWith(files, "Summary.xlsx")]) + date_last_modified <- as.character(as.Date(file.mtime(FileName))) - BEASummary <- as.data.frame(readxl::read_excel(FileName, sheet = "2012")) + BEASummary <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(schema_year))) ## Commodity & Value Added SummaryCommVA <- BEASummary[!is.na(BEASummary[, 2]), c(1:2)][-c(1:2), ] commodity_range <- c(1:(which(SummaryCommVA[, 2] == "Total Intermediate") - 1)) va_range <- c((length(commodity_range) + 2):(which(SummaryCommVA[, 2] == "Total Value Added") - 1)) # Commodity BEASummaryCommodityCodeName <- SummaryCommVA[commodity_range, ] - colnames(BEASummaryCommodityCodeName) <- c("BEA_2012_Summary_Commodity_Code", - "BEA_2012_Summary_Commodity_Name") + colnames(BEASummaryCommodityCodeName) <- c(paste0("BEA_",schema_year, "_Summary_Commodity_Code"), + paste0("BEA_",schema_year, "_Summary_Commodity_Name")) rownames(BEASummaryCommodityCodeName) <- NULL # Value Added BEASummaryValueAddedCodeName <- SummaryCommVA[va_range, ] - colnames(BEASummaryValueAddedCodeName) <- c("BEA_2012_Summary_ValueAdded_Code", - "BEA_2012_Summary_ValueAdded_Name") + colnames(BEASummaryValueAddedCodeName) <- c(paste0("BEA_",schema_year, "_Summary_ValueAdded_Code"), + paste0("BEA_",schema_year, "_Summary_ValueAdded_Name")) rownames(BEASummaryValueAddedCodeName) <- NULL ## Industry & Final Demand SummaryIndFD <- as.data.frame(t(BEASummary[!is.na(BEASummary[, 3]), ][1:2, -c(1:2)])) @@ -1353,35 +993,35 @@ getBEACodeName2012Schema <- function() { fd_range <- c((length(industry_range) + 2):(which(SummaryIndFD[, 2] == "Total Final Uses (GDP)") - 1)) # Industry BEASummaryIndustryCodeName <- SummaryIndFD[industry_range, ] - colnames(BEASummaryIndustryCodeName) <- c("BEA_2012_Summary_Industry_Code", - "BEA_2012_Summary_Industry_Name") + colnames(BEASummaryIndustryCodeName) <- c(paste0("BEA_",schema_year, "_Summary_Industry_Code"), + paste0("BEA_",schema_year, "_Summary_Industry_Name")) rownames(BEASummaryIndustryCodeName) <- NULL # Final Demand BEASummaryFinalDemandCodeName <- SummaryIndFD[fd_range, ] - colnames(BEASummaryFinalDemandCodeName) <- c("BEA_2012_Summary_FinalDemand_Code", - "BEA_2012_Summary_FinalDemand_Name") + colnames(BEASummaryFinalDemandCodeName) <- c(paste0("BEA_",schema_year, "_Summary_FinalDemand_Code"), + paste0("BEA_",schema_year, "_Summary_FinalDemand_Name")) rownames(BEASummaryFinalDemandCodeName) <- NULL ### Sector ### # Load data - FileName <- file.path("inst/extdata/AllTablesIO", + FileName <- file.path(dir, "AllTableIO", files[startsWith(files, "IOUse_Before_Redefinitions_PRO") & - endsWith(files, "Sector.xlsx")]) + endsWith(files, "Sector.xlsx")]) date_last_modified <- as.character(as.Date(file.mtime(FileName))) - BEASector <- as.data.frame(readxl::read_excel(FileName, sheet = "2012")) + BEASector <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(schema_year))) ## Commodity & Value Added SectorCommVA <- BEASector[!is.na(BEASector[, 2]), c(1:2)][-c(1:2), ] commodity_range <- c(1:(which(SectorCommVA[, 2] == "Total Intermediate") - 1)) va_range <- c((length(commodity_range) + 2):(which(SectorCommVA[, 2] == "Total Value Added") - 1)) # Commodity BEASectorCommodityCodeName <- SectorCommVA[commodity_range, ] - colnames(BEASectorCommodityCodeName) <- c("BEA_2012_Sector_Commodity_Code", - "BEA_2012_Sector_Commodity_Name") + colnames(BEASectorCommodityCodeName) <- c(paste0("BEA_",schema_year, "_Sector_Commodity_Code"), + paste0("BEA_",schema_year, "_Sector_Commodity_Name")) rownames(BEASectorCommodityCodeName) <- NULL # Value Added BEASectorValueAddedCodeName <- SectorCommVA[va_range, ] - colnames(BEASectorValueAddedCodeName) <- c("BEA_2012_Sector_ValueAdded_Code", - "BEA_2012_Sector_ValueAdded_Name") + colnames(BEASectorValueAddedCodeName) <- c(paste0("BEA_",schema_year, "_Sector_ValueAdded_Code"), + paste0("BEA_",schema_year, "_Sector_ValueAdded_Name")) rownames(BEASectorValueAddedCodeName) <- NULL ## Industry & Final Demand SectorIndFD <- as.data.frame(t(BEASector[!is.na(BEASector[, 3]), ][1:2, -c(1:2)])) @@ -1389,51 +1029,47 @@ getBEACodeName2012Schema <- function() { fd_range <- c((length(industry_range) + 2):(which(SectorIndFD[, 2] == "Total Final Uses (GDP)") - 1)) # Industry BEASectorIndustryCodeName <- SectorIndFD[industry_range, ] - colnames(BEASectorIndustryCodeName) <- c("BEA_2012_Sector_Industry_Code", - "BEA_2012_Sector_Industry_Name") + colnames(BEASectorIndustryCodeName) <- c(paste0("BEA_",schema_year, "_Sector_Industry_Code"), + paste0("BEA_",schema_year, "_Sector_Industry_Name")) rownames(BEASectorIndustryCodeName) <- NULL # Final Demand BEASectorFinalDemandCodeName <- SectorIndFD[fd_range, ] - colnames(BEASectorFinalDemandCodeName) <- c("BEA_2012_Sector_FinalDemand_Code", - "BEA_2012_Sector_FinalDemand_Name") + colnames(BEASectorFinalDemandCodeName) <- c(paste0("BEA_",schema_year, "_Sector_FinalDemand_Code"), + paste0("BEA_",schema_year, "_Sector_FinalDemand_Name")) rownames(BEASectorFinalDemandCodeName) <- NULL ### Put the data.frames in a list - BEACodeNameList <- list("Detail_IndustryCodeName_2012" = BEADetailIndustryCodeName, - "Detail_CommodityCodeName_2012" = BEADetailCommodityCodeName, - "Detail_ValueAddedCodeName_2012" = BEADetailValueAddedCodeName, - "Detail_FinalDemandCodeName_2012" = BEADetailFinalDemandCodeName, - "Summary_IndustryCodeName_2012" = BEASummaryIndustryCodeName, - "Summary_CommodityCodeName_2012" = BEASummaryCommodityCodeName, - "Summary_ValueAddedCodeName_2012" = BEASummaryValueAddedCodeName, - "Summary_FinalDemandCodeName_2012" = BEASummaryFinalDemandCodeName, - "Sector_IndustryCodeName_2012" = BEASectorIndustryCodeName, - "Sector_CommodityCodeName_2012" = BEASectorCommodityCodeName, - "Sector_ValueAddedCodeName_2012" = BEASectorValueAddedCodeName, - "Sector_FinalDemandCodeName_2012" = BEASectorFinalDemandCodeName) + BEACodeNameList <- list("Detail_IndustryCodeName" = BEADetailIndustryCodeName, + "Detail_CommodityCodeName" = BEADetailCommodityCodeName, + "Detail_ValueAddedCodeName" = BEADetailValueAddedCodeName, + "Detail_FinalDemandCodeName" = BEADetailFinalDemandCodeName, + "Summary_IndustryCodeName" = BEASummaryIndustryCodeName, + "Summary_CommodityCodeName" = BEASummaryCommodityCodeName, + "Summary_ValueAddedCodeName" = BEASummaryValueAddedCodeName, + "Summary_FinalDemandCodeName" = BEASummaryFinalDemandCodeName, + "Sector_IndustryCodeName" = BEASectorIndustryCodeName, + "Sector_CommodityCodeName" = BEASectorCommodityCodeName, + "Sector_ValueAddedCodeName" = BEASectorValueAddedCodeName, + "Sector_FinalDemandCodeName" = BEASectorFinalDemandCodeName) BEACodeNameList <- lapply(BEACodeNameList, cleanSectorNames) BEACodeNameList <- lapply(BEACodeNameList, cleanSectorCodes) ### Save and Document data + ls <- list("url" = url, + "date_last_modified" = date_last_modified, + "date_accessed" = date_accessed) for (data_name in names(BEACodeNameList)) { - # Write data to .rda - writeDatatoRDA(data = BEACodeNameList[[data_name]], data_name = data_name) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = data_name, - year = 2012, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + writeFile(df = BEACodeNameList[[data_name]], year = schema_year, + name = paste0(data_name, "_", schema_year), ls = ls, + schema_year = NULL) } } -# Get Detail Margins (Before Redefinition, 2012 schema) table from BEA static URL -getBEADetailMarginsBeforeRedef2012Schema <- function(year) { +# Get Detail Margins (Before Redefinition) table from BEA static URL +getBEADetailMarginsBeforeRedef <- function(year) { # Download data - file <- "Margins_Before_Redefinitions_2007_2012_DET.xlsx" - url <- file.path("https://apps.bea.gov/industry/xls/underlying-estimates", file) - FileName <- file.path("inst/extdata", file) + file <- "Margins_Before_Redefinitions_2017_DET.xlsx" + url <- file.path(url_ls["margins"], file) + FileName <- file.path(dir, file) if (!file.exists(FileName)) { utils::download.file(url, FileName, mode = "wb") } @@ -1450,304 +1086,177 @@ getBEADetailMarginsBeforeRedef2012Schema <- function(year) { Margins[, 5:ncol(Margins)] <- as.data.frame(lapply(Margins[, 5:ncol(Margins)], as.numeric), check.names = FALSE) - # Write data to .rda - writeDatatoRDA(data = Margins, - data_name = paste0("Detail_Margins_", year, "_BeforeRedef")) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Margins_", year, "_BeforeRedef"), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = "2022-03-04", # page last modified - date_accessed = as.character(as.Date(file.mtime(FileName)))) -} - - -# Download all Supply and Use tables from BEA iTable -getBEASupplyUseTables <- function() { - # Create the placeholder file - AllTablesSUP <- "inst/extdata/AllTablesIOSUP.zip" - # Download all BEA IO tables into the placeholder file - url <- "https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip" - if (!file.exists(AllTablesSUP)) { - utils::download.file(url, AllTablesSUP, mode = "wb") - } - # Get the name of all files in the zip archive - files <- unzip(AllTablesSUP, list = TRUE) - fname <- files[files$Length > 0, ]$Name - if (all(fname == basename(fname))) { - exdir <- "inst/extdata/AllTablesSUP" - } else { - exdir <- "inst/extdata/" - } - # Unzip the file to the designated directory - unzip(AllTablesSUP, files = fname, exdir = exdir, - overwrite = TRUE, setTimes = TRUE) - # Create output ls <- list("url" = url, - "date_accessed" = as.character(as.Date(file.mtime(AllTablesSUP))), - "files" = basename(fname)) - return(ls) + "date_accessed" = as.character(as.Date(file.mtime(FileName))), + "date_last_modified" = "2024-02-01") # page last modified + writeFile(df = Margins, year = year, + name = paste0("Detail_Margins_", year, "_BeforeRedef"), ls = ls, + schema_year = year) } -# Get BEA Detail Supply (2012 schema) table from static Excel -getBEADetailSupply2012Schema <- function(year) { - # Download data - url <- getBEASupplyUseTables()[["url"]] - date_accessed <- getBEASupplyUseTables()[["date_accessed"]] - files <- getBEASupplyUseTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesSUP", - files[startsWith(files, "Supply") & - endsWith(files, "DET.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) + +# Get BEA Detail Supply table from static Excel +getBEADetailSupply <- function(year) { + ls <- getBEASupplyUseTables() + FileName <- file.path(dir, "AllTablesSUP", + ls[["files"]][startsWith(ls[["files"]], "Supply") & + endsWith(ls[["files"]], "DET.xlsx")]) + ls["date_last_modified"] <- "2024-02-01" # page last modified DetailSupply <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(year))) - # Assign row and column names - DetailSupply <- DetailSupply[!is.na(DetailSupply[, 2]), ] - colnames(DetailSupply) <- DetailSupply[1, ] - rownames(DetailSupply) <- DetailSupply$Code - # Trim table, convert all values to numeric, assign row names - DetailSupply <- as.data.frame(lapply(DetailSupply[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailSupply[-1, 1]) - # Replace NA with zero - DetailSupply[is.na(DetailSupply)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailSupply, - data_name = paste0("Detail_Supply_", year)) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Supply_", year), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + DetailSupply <- processDetailMatrix(DetailSupply) + writeFile(df = DetailSupply, year = year, + name = paste0("Detail_Supply_", year), ls = ls, + schema_year = year) } -# Get BEA Detail Use (under the Supply-Use framework, 2012 schema) table from static Excel -getBEADetailUseSUT2012Schema <- function(year) { - # Download data - url <- getBEASupplyUseTables()[["url"]] - date_accessed <- getBEASupplyUseTables()[["date_accessed"]] - files <- getBEASupplyUseTables()[["files"]] - # Load data - FileName <- file.path("inst/extdata/AllTablesSUP", - files[startsWith(files, "Use") & - endsWith(files, "DET.xlsx")]) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# Get BEA Detail Use (under the Supply-Use framework schema) table from static Excel +getBEADetailUseSUT <- function(year) { + ls <- getBEASupplyUseTables() + FileName <- file.path(dir, "AllTablesSUP", + ls[["files"]][startsWith(ls[["files"]], "Use") & + endsWith(ls[["files"]], "DET.xlsx")]) + ls["date_last_modified"] = "2024-02-01" # page last modified DetailUse <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(year))) - # Assign row and column names - DetailUse <- DetailUse[!is.na(DetailUse[, 2]), ] - colnames(DetailUse) <- DetailUse[1, ] - rownames(DetailUse) <- DetailUse$Code - # Trim table, convert all values to numeric, assign row names - DetailUse <- as.data.frame(lapply(DetailUse[-1, -c(1:2)], as.numeric), - check.names = FALSE, - row.names = DetailUse[-1, 1]) - # Replace NA with zero - DetailUse[is.na(DetailUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = DetailUse, - data_name = paste0("Detail_Use_SUT_", year)) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Detail_Use_SUT_", year), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + DetailUse <- processDetailMatrix(DetailUse) + writeFile(df = DetailUse, year = year, + name = paste0("Detail_Use_SUT_", year), ls = ls, + schema_year = year) } -# Get BEA Summary Supply (2012 schema) table from static Excel -getBEASummarySupply2012Schema <- function() { - # Download data - url <- getBEASupplyUseTables()[["url"]] - date_accessed <- getBEASupplyUseTables()[["date_accessed"]] - files <- getBEASupplyUseTables()[["files"]] +# Get BEA Summary Supply table from static Excel +getBEASummarySupply <- function(year) { + ls <- getBEASupplyUseTables() # Prepare file name - file <- files[startsWith(files, "Supply") & endsWith(files, "SUM.xlsx")] - FileName <- file.path("inst/extdata/AllTablesSUP", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) + file <- ls[["files"]][startsWith(ls[["files"]], "Supply") & + endsWith(ls[["files"]], "Summary.xlsx")] + FileName <- file.path(dir, "AllTablesSUP", file) + end_year <- 2022 # Load data - for (year in 2010:end_year) { + for (y in 2017:end_year) { SummarySupply <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SummarySupply <- SummarySupply[!is.na(SummarySupply[, 2]), ] - colnames(SummarySupply) <- SummarySupply[1, ] - colname_check <- is.na(colnames(SummarySupply)) - colnames(SummarySupply)[colname_check] <- SummarySupply[2, colname_check] - # Fill NA in code column with corresponding name - SummarySupply[is.na(SummarySupply[, 1]), 1] <- SummarySupply[is.na(SummarySupply[, 1]), 2] - # Convert all values to numeric, assign row names - SummarySupply <- as.data.frame(lapply(SummarySupply[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummarySupply[-c(1:2), 1]) - # Replace NA with zero - SummarySupply[is.na(SummarySupply)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummarySupply, - data_name = paste0("Summary_Supply_", year)) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Supply_", year), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + sheet = as.character(y))) + SummarySupply <- processSummaryMatrix(SummarySupply) + writeFile(df = SummarySupply, year = y, + name = paste0("Summary_Supply_", y), ls = ls, + schema_year = year) } } -# Get BEA Summary Use (under the Supply-Use framework, 2012 schema) table from static Excel -getBEASummaryUseSUT2012Schema <- function() { - # Download data - url <- getBEASupplyUseTables()[["url"]] - date_accessed <- getBEASupplyUseTables()[["date_accessed"]] - files <- getBEASupplyUseTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "Use") & endsWith(files, "Sum.xlsx")] - FileName <- file.path("inst/extdata/AllTablesSUP", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) +# Get BEA Summary Use under the Supply-Use framework from static Excel +getBEASummaryUseSUT <- function(year) { + ls <- getBEASupplyUseTables() + file <- ls[["files"]][startsWith(ls[["files"]], "Use") & + endsWith(ls[["files"]], "Summary.xlsx")] + FileName <- file.path(dir, "AllTablesSUP", file) + end_year <- 2022 # Load data - for (year in 2010:end_year) { + for (y in 2017:end_year) { SummaryUse <- as.data.frame(readxl::read_excel(FileName, sheet = as.character(year))) - # Trim table, assign column names - SummaryUse <- SummaryUse[!is.na(SummaryUse[, 2]), ] - colnames(SummaryUse) <- SummaryUse[1, ] - colname_check <- is.na(colnames(SummaryUse)) - colnames(SummaryUse)[colname_check] <- SummaryUse[2, colname_check] - # Fill NA in code column with corresponding name - SummaryUse[is.na(SummaryUse[, 1]), 1] <- SummaryUse[is.na(SummaryUse[, 1]), 2] - # Convert all values to numeric, assign row names - SummaryUse <- as.data.frame(lapply(SummaryUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SummaryUse[-c(1:2), 1]) - # Replace NA with zero - SummaryUse[is.na(SummaryUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SummaryUse, - data_name = paste0("Summary_Use_SUT_", year)) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Summary_Use_SUT_", year), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) + SummaryUse <- processSummaryMatrix(SummaryUse) + writeFile(df = SummaryUse, year = y, + name = paste0("Summary_Use_SUT_", y), ls = ls, + schema_year = year) } } -# Get BEA Sector Supply (2012 schema) table from static Excel -getBEASectorSupply2012Schema <- function() { - # Download data - url <- getBEASupplyUseTables()[["url"]] - date_accessed <- getBEASupplyUseTables()[["date_accessed"]] - files <- getBEASupplyUseTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "Supply") & endsWith(files, "SEC.xlsx")] - FileName <- file.path("inst/extdata/AllTablesSUP", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SectorSupply <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorSupply <- SectorSupply[!is.na(SectorSupply[, 2]), ] - colnames(SectorSupply) <- SectorSupply[1, ] - colname_check <- is.na(colnames(SectorSupply)) - colnames(SectorSupply)[colname_check] <- SectorSupply[2, colname_check] - # Assign T017 to Total industry supply if not provided - if (is.na(SectorSupply[SectorSupply$`Commodities/Industries` == "Total industry supply", 1])) { - SectorSupply[SectorSupply$`Commodities/Industries` == "Total industry supply", 1] <- "T017" - } - # Fill NA in code column with corresponding name - SectorSupply[is.na(SectorSupply[, 1]), 1] <- SectorSupply[is.na(SectorSupply[, 1]), 2] - # Convert all values to numeric, assign row names - SectorSupply <- as.data.frame(lapply(SectorSupply[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorSupply[-c(1:2), 1]) - # Replace NA with zero - SectorSupply[is.na(SectorSupply)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorSupply, - data_name = paste0("Sector_Supply_", year)) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Supply_", year), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) - } -} - - -# Get BEA Sector Use (under the Supply-Use framework, 2012 schema) table from static Excel -getBEASectorUseSUT2012Schema <- function() { - # Download data - url <- getBEASupplyUseTables()[["url"]] - date_accessed <- getBEASupplyUseTables()[["date_accessed"]] - files <- getBEASupplyUseTables()[["files"]] - # Prepare file name - file <- files[startsWith(files, "Use") & endsWith(files, "SECT.xlsx")] - FileName <- file.path("inst/extdata/AllTablesSUP", file) - date_last_modified <- as.character(as.Date(file.mtime(FileName))) - # Find latest data year - file_split <- unlist(stringr::str_split(file, pattern = "_")) - year_range <- file_split[length(file_split) - 1] - end_year <- sub(".*-", "", year_range) - # Load data - for (year in 2010:end_year) { - SectorUse <- as.data.frame(readxl::read_excel(FileName, - sheet = as.character(year))) - # Trim table, assign column names - SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] - colnames(SectorUse) <- SectorUse[1, ] - colname_check <- is.na(colnames(SectorUse)) - colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] - # Fill NA in code column with corresponding name - SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] - # Convert all values to numeric, assign row names - SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), - check.names = FALSE, - row.names = SectorUse[-c(1:2), 1]) - # Replace NA with zero - SectorUse[is.na(SectorUse)] <- 0 - # Write data to .rda - writeDatatoRDA(data = SectorUse, - data_name = paste0("Sector_Use_SUT_", year)) - # Write metadata to JSON - writeMetadatatoJSON(package = "useeior", - name = paste0("Sector_Use_SUT_", year), - year = year, - source = "US Bureau of Economic Analysis", - url = url, - date_last_modified = date_last_modified, - date_accessed = date_accessed) - } -} +# # Get BEA Sector Supply table from static Excel +# getBEASectorSupply <- function() { +# # Download data +# url <- getBEASupplyUseTables()[["url"]] +# date_accessed <- getBEASupplyUseTables()[["date_accessed"]] +# files <- getBEASupplyUseTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "Supply") & endsWith(files, "SEC.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesSUP", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Find latest data year +# file_split <- unlist(stringr::str_split(file, pattern = "_")) +# year_range <- file_split[length(file_split) - 1] +# end_year <- sub(".*-", "", year_range) +# # Load data +# for (year in 2010:end_year) { +# SectorSupply <- as.data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorSupply <- SectorSupply[!is.na(SectorSupply[, 2]), ] +# colnames(SectorSupply) <- SectorSupply[1, ] +# colname_check <- is.na(colnames(SectorSupply)) +# colnames(SectorSupply)[colname_check] <- SectorSupply[2, colname_check] +# # Assign T017 to Total industry supply if not provided +# if (is.na(SectorSupply[SectorSupply$`Commodities/Industries` == "Total industry supply", 1])) { +# SectorSupply[SectorSupply$`Commodities/Industries` == "Total industry supply", 1] <- "T017" +# } +# # Fill NA in code column with corresponding name +# SectorSupply[is.na(SectorSupply[, 1]), 1] <- SectorSupply[is.na(SectorSupply[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorSupply <- as.data.frame(lapply(SectorSupply[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorSupply[-c(1:2), 1]) +# # Replace NA with zero +# SectorSupply[is.na(SectorSupply)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorSupply, +# data_name = paste0("Sector_Supply_", year)) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Supply_", year), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# } +# +# +# # Get BEA Sector Use (under the Supply-Use framework, 2012 schema) table from static Excel +# getBEASectorUseSUT2012Schema <- function() { +# # Download data +# url <- getBEASupplyUseTables()[["url"]] +# date_accessed <- getBEASupplyUseTables()[["date_accessed"]] +# files <- getBEASupplyUseTables()[["files"]] +# # Prepare file name +# file <- files[startsWith(files, "Use") & endsWith(files, "SECT.xlsx")] +# FileName <- file.path("inst/extdata/AllTablesSUP", file) +# date_last_modified <- as.character(as.Date(file.mtime(FileName))) +# # Find latest data year +# file_split <- unlist(stringr::str_split(file, pattern = "_")) +# year_range <- file_split[length(file_split) - 1] +# end_year <- sub(".*-", "", year_range) +# # Load data +# for (year in 2010:end_year) { +# SectorUse <- as.data.frame(readxl::read_excel(FileName, +# sheet = as.character(year))) +# # Trim table, assign column names +# SectorUse <- SectorUse[!is.na(SectorUse[, 2]), ] +# colnames(SectorUse) <- SectorUse[1, ] +# colname_check <- is.na(colnames(SectorUse)) +# colnames(SectorUse)[colname_check] <- SectorUse[2, colname_check] +# # Fill NA in code column with corresponding name +# SectorUse[is.na(SectorUse[, 1]), 1] <- SectorUse[is.na(SectorUse[, 1]), 2] +# # Convert all values to numeric, assign row names +# SectorUse <- as.data.frame(lapply(SectorUse[-c(1:2), -c(1:2)], as.numeric), +# check.names = FALSE, +# row.names = SectorUse[-c(1:2), 1]) +# # Replace NA with zero +# SectorUse[is.na(SectorUse)] <- 0 +# # Write data to .rda +# writeDatatoRDA(data = SectorUse, +# data_name = paste0("Sector_Use_SUT_", year)) +# # Write metadata to JSON +# writeMetadatatoJSON(package = "useeior", +# name = paste0("Sector_Use_SUT_", year), +# year = year, +# source = "US Bureau of Economic Analysis", +# url = url, +# date_last_modified = date_last_modified, +# date_accessed = date_accessed) +# } +# } diff --git a/data-raw/BEAData_Detail.R b/data-raw/BEAData_Detail.R index bdb31c12..c2680cc5 100644 --- a/data-raw/BEAData_Detail.R +++ b/data-raw/BEAData_Detail.R @@ -1,45 +1,43 @@ source("data-raw/BEAData.R") +source("R/UtilityFunctions.R") -schema_year <- 2012 +schema_year <- 2017 -# Download, save and document 2012 BEA Detail Make (Before Redef, 2012 schema) -getBEADetailMakeBeforeRedef2012Schema(schema_year) -# Download, save and document 2012 BEA Detail Use (PRO, Before Redef, 2012 schema) -getBEADetailUsePROBeforeRedef2012Schema(schema_year) +# Download, save and document BEA Detail Make (Before Redef) +getBEADetailMakeBeforeRedef(schema_year) -# Download, save and document 2012 BEA Detail Use (PUR, Before Redef, 2012 schema) -getBEADetailUsePURBeforeRedef2012Schema(schema_year) +# Download, save and document BEA Detail Use (PRO, Before Redef) +getBEADetailUsePROBeforeRedef(schema_year) -# Download, save and document 2012 BEA Detail Make (After Redef, 2012 schema) -getBEADetailMakeAfterRedef2012Schema(schema_year) +# Download, save and document BEA Detail Use (PUR, Before Redef) +getBEADetailUsePURBeforeRedef(schema_year) -# Download, save and document 2012 BEA Detail Use (PRO, After Redef, 2012 schema) -getBEADetailUsePROAfterRedef2012Schema(schema_year) +# Download, save and document BEA Detail Make (After Redef) +getBEADetailMakeAfterRedef(schema_year) -# Download, save and document 2012 BEA Detail Use (PUR, After Redef, 2012 schema) -getBEADetailUsePURAfterRedef2012Schema(schema_year) +# Download, save and document BEA Detail Use (PRO, After Redef) +getBEADetailUsePROAfterRedef(schema_year) +# Download, save and document BEA Detail Use (PUR, After Redef) +getBEADetailUsePURAfterRedef(schema_year) -# Download, save and document 2012 BEA Summary Use (PUR, Before Redef, 2012 schema) -getBEASummaryUsePURBeforeRedef2012Schema(schema_year) +# Download, save and document BEA Summary Use (PUR, Before Redef) +getBEASummaryUsePURBeforeRedef(schema_year) -# Download, save and document 2012 BEA Sector Use (PUR, Before Redef, 2012 schema) -getBEASectorUsePURBeforeRedef2012Schema(schema_year) +# Download, save and document BEA Detail Import matrix +getBEADetailImportBeforeRedef(schema_year) -# Download, save and document 2012 BEA Detail Import matrix -getBEADetailImportBeforeRedef2012Schema(schema_year) +# Download, save and document BEA Detail, Summary, and Sector Code and Name +getBEACodeName(schema_year) -# Download, save and document BEA Detail, Summary, and Sector Code and Name (2012 schema) -getBEACodeName2012Schema() - -# Download, save and document 2012 BEA Detail Margins table -getBEADetailMarginsBeforeRedef2012Schema(schema_year) +# Download, save and document BEA Detail Margins table +getBEADetailMarginsBeforeRedef(schema_year) ## Supply and Use Tables -# Download, save and document 2012 BEA Detail Supply (2012 schema) -getBEADetailSupply2012Schema(schema_year) +# Download, save and document BEA Detail Supply +getBEADetailSupply(schema_year) -# Download, save and document 2012 BEA Detail Supply (2012 schema) -getBEADetailUseSUT2012Schema(schema_year) +# Download, save and document BEA Detail Use +getBEADetailUseSUT(schema_year) diff --git a/data-raw/BEAData_Support.R b/data-raw/BEAData_Support.R index 9552b49c..e56fe5b8 100644 --- a/data-raw/BEAData_Support.R +++ b/data-raw/BEAData_Support.R @@ -1,55 +1,39 @@ source("data-raw/BEAData.R") +source("R/UtilityFunctions.R") -## Annual Summary Make and Use -# Download, save and document 2010-2020 BEA Summary Make (Before Redef, 2012 schema) -getBEASummaryMakeBeforeRedef2012Schema() - -# Download, save and document 2010-2020 BEA Summary Use (PRO, Before Redef, 2012 schema) -getBEASummaryUsePROBeforeRedef2012Schema() - -# Download, save and document 2010-2020 BEA Summary Make (After Redef, 2012 schema) -getBEASummaryMakeAfterRedef2012Schema() - -# Download, save and document 2010-2020 BEA Summary Use (PRO, After Redef, 2012 schema) -getBEASummaryUsePROAfterRedef2012Schema() +schema_year <- 2017 +# 2017 - 2022 tables -## Annual Sector Make and Use -# Download, save and document 2010-2020 BEA Sector Make (Before Redef, 2012 schema) -getBEASectorMakeBeforeRedef2012Schema() - -# Download, save and document 2010-2020 BEA Sector Use (PRO, Before Redef, 2012 schema) -getBEASectorUsePROBeforeRedef2012Schema() +## Annual Summary Make and Use +# Download, save and document BEA Summary Make (Before Redef) +getBEASummaryMakeBeforeRedef(schema_year) -# Download, save and document 2010-2020 BEA Sector Make (After Redef, 2012 schema) -getBEASectorMakeAfterRedef2012Schema() +# Download, save and document BEA Summary Use (PRO, Before Redef) +getBEASummaryUsePROBeforeRedef(schema_year) -# Download, save and document 2010-2018 BEA Sector Use (PRO, After Redef, 2012 schema) -getBEASectorUsePROAfterRedef2012Schema() +# Download, save and document BEA Summary Make (After Redef) +getBEASummaryMakeAfterRedef(schema_year) +# Download, save and document BEA Summary Use (PRO, After Redef) +getBEASummaryUsePROAfterRedef(schema_year) ## Supporting Data -# Download, save and document 2010-2020 BEA Summary Import matrix -getBEASummaryImportBeforeRedef2012Schema() +# Download, save and document BEA Summary Import matrix +getBEASummaryImportBeforeRedef(schema_year) # Download, save and document BEA Detail, Summary, and Sector Gross Output tables -mapBEAGrossOutputtoIOIndustry2012Schema() +mapBEAGrossOutputtoIOIndustry(schema_year) -# Download, save and document BEA Detail, Summary, and Sector CPI tables since 2002 -mapBEACPItoIOIndustry2012Schema() +# Download, save and document BEA Detail, Summary, and Sector CPI tables +mapBEACPItoIOIndustry(schema_year) -# Download, save and document BEA Summary and Sector Value Added tables since 2002 -mapBEAValueAddedtoIOIndustry2012Schema() +# Download, save and document BEA Summary and Sector Value Added tables +mapBEAValueAddedtoIOIndustry(schema_year) ## Supply and Use Tables -# Download, save and document 2010-2020 BEA Summary Supply (2012 schema) -getBEASummarySupply2012Schema() - -# Download, save and document 2010-2020 BEA Summary Use (2012 schema) -getBEASummaryUseSUT2012Schema() - -# Download, save and document 2010-2020 BEA Sector Supply (2012 schema) -getBEASectorSupply2012Schema() +# Download, save and document BEA Summary Supply +getBEASummarySupply(schema_year) -# Download, save and document 2010-2020 BEA Sector Supply (2012 schema) -getBEASectorUseSUT2012Schema() +# Download, save and document BEA Summary Use +getBEASummaryUseSUT(schema_year) diff --git a/data-raw/MasterCrosswalk.R b/data-raw/MasterCrosswalk.R index b13733fd..2f773f48 100644 --- a/data-raw/MasterCrosswalk.R +++ b/data-raw/MasterCrosswalk.R @@ -1,24 +1,35 @@ +source("data-raw/BEAData.R") +source("R/CrosswalkFunctions.R") + +getReferenceFileName <- function () { + files <- getBEASupplyUseTables()[["files"]] + fileName <- file.path(rappdirs::user_data_dir(), "USEEIO-input", "AllTablesSUP", + files[startsWith(files, "Use") & + endsWith(files, "DET.xlsx")]) + return(fileName) +} + +# Get schema year of current data +getSchemaYearfromFileName <- function (FileName) { + #get year from filename + year <- substr(FileName,unlist(gregexpr(pattern ='k_',FileName))+2,unlist(gregexpr(pattern ='_D',FileName))-1) + year <- as.integer(year) + return(year) +} + # Extract existing BEA-NAICS mapping from BEA IO table -extractBEAtoNAICSfromIOTable <- function (year) { # year = 2012 or 2007 - if (year == 2012) { - # Download the IO table - FileName <- "inst/extdata/IOUse_Before_Redefinitions_PRO_2007_2012_Detail.xlsx" - if(!file.exists(FileName)) { - utils::download.file("https://apps.bea.gov/industry/xls/io-annual/IOUse_Before_Redefinitions_PRO_DET.xlsx", - FileName, mode = "wb") - } - # Load desired excel file - BEAtable <- as.data.frame(readxl::read_excel(FileName, sheet = "NAICS Codes", col_names = FALSE)) - # Split to BEA and BEAtoNAICS - BEA <- BEAtable[-c(1:5), c(1:2, 4:5)] - BEAtoNAICS <- BEAtable[-c(1:5), c(4:5, 7)] - } else { #year = 2007 - BEAtable <- as.data.frame(readxl::read_excel("inst/extdata/IOUse_Before_Redefinitions_PRO_2007_Detail.xlsx", - sheet = "NAICS codes", col_names = FALSE)) - # Split to BEA and BEAtoNAICS - BEA <- BEAtable[-c(1:4), 1:4] - BEAtoNAICS <- BEAtable[-c(1:4), c(3:4, 6)] - } +extractBEAtoNAICSfromIOTable <- function () { + + FileName <- getReferenceFileName() + #get year from filename + year <- getSchemaYearfromFileName(FileName) + + # Load desired excel file + BEAtable <- as.data.frame(readxl::read_excel(FileName, sheet = "NAICS Codes", col_names = FALSE)) + # Split to BEA and BEAtoNAICS + BEA <- BEAtable[-c(1:5), c(1:2, 4:5)] + BEAtoNAICS <- BEAtable[-c(1:5), c(4:5, 7)] + # Extract BEA (Sector, Summary, Detail) Code and Name # BEA only @@ -40,7 +51,7 @@ extractBEAtoNAICSfromIOTable <- function (year) { # year = 2012 or 2007 # Split the NAICS column by comma (,) BEAtoNAICS <- cbind(BEAtoNAICS, do.call("rbind", strsplit(BEAtoNAICS$NAICS, ","))) BEAtoNAICS$NAICS <- NULL - # Reshape and drop duplicats + # Reshape and drop duplicates BEAtoNAICSlong <- reshape2::melt(BEAtoNAICS, id.vars = c("BEA_Detail_Code", "BEA_Detail_Name")) BEAtoNAICSlong$variable <- NULL BEAtoNAICSlong <- unique(BEAtoNAICSlong) @@ -58,16 +69,11 @@ extractBEAtoNAICSfromIOTable <- function (year) { # year = 2012 or 2007 BEAtoNAICSlongDash <- unique(BEAtoNAICSlongDash) # The NAICS codes are "n.a." # The NAICS codes without dash (-) - if (year==2012) { - BEAtoNAICSlongNA <- BEAtoNAICSlong[BEAtoNAICSlong$value == "n.a.", ] - BEAtoNAICSlongSubset <- BEAtoNAICSlong[!rownames(BEAtoNAICSlong) %in% grep("-", BEAtoNAICSlong$value, value = FALSE) & !BEAtoNAICSlong$value == "n.a.", ] - BEAtoNAICSlongSubset <- do.call("cbind.data.frame", lapply(BEAtoNAICSlongSubset, gsub, pattern="*", replacement="")) - BEAtoNAICSlongSubset$value <- gsub("[*]", "", BEAtoNAICSlongSubset$value) - } else { - BEAtoNAICSlongNA <- BEAtoNAICSlong[BEAtoNAICSlong$value == "n/a", ] - BEAtoNAICSlongSubset <- BEAtoNAICSlong[!rownames(BEAtoNAICSlong) %in% grep("-", BEAtoNAICSlong$value, value = FALSE) & !BEAtoNAICSlong$value == "n/a", ] - BEAtoNAICSlongSubset <- do.call("cbind.data.frame", lapply(BEAtoNAICSlongSubset, gsub, pattern="*", replacement="")) - } + BEAtoNAICSlongNA <- BEAtoNAICSlong[BEAtoNAICSlong$value == "n.a.", ] + BEAtoNAICSlongSubset <- BEAtoNAICSlong[!rownames(BEAtoNAICSlong) %in% grep("-", BEAtoNAICSlong$value, value = FALSE) & !BEAtoNAICSlong$value == "n.a.", ] + BEAtoNAICSlongSubset <- do.call("cbind.data.frame", lapply(BEAtoNAICSlongSubset, gsub, pattern="*", replacement="")) + BEAtoNAICSlongSubset$value <- gsub("[*]", "", BEAtoNAICSlongSubset$value) + # Assemble all chunks together BEAtoNAICS <- rbind(BEAtoNAICSlongDash, BEAtoNAICSlongNA, BEAtoNAICSlongSubset) @@ -78,7 +84,7 @@ extractBEAtoNAICSfromIOTable <- function (year) { # year = 2012 or 2007 BEAtoNAICS <- merge(BEAtoNAICS, BEA, by = c("BEA_Detail_Code", "BEA_Detail_Name"), all.x = TRUE) BEAtoNAICS <- BEAtoNAICS[, c(colnames(BEA), "NAICS_Code")] BEAtoNAICS$NAICS_Code <- as.integer(BEAtoNAICS$NAICS_Code) - BEAtoNAICS[BEAtoNAICS$BEA_Detail_Code=="517A00" & BEAtoNAICS$NAICS_Code=="5719", "NAICS_Code"] <- as.integer(5179) + # Add year into column names colnames(BEAtoNAICS)[1:6] <- gsub("BEA_", paste("BEA_", year, "_", sep = ""), colnames(BEAtoNAICS)[1:6]) colnames(BEAtoNAICS)[7] <- gsub("NAICS_", paste("NAICS_", year, "_", sep = ""), colnames(BEAtoNAICS)[7]) @@ -95,7 +101,8 @@ getBEAtoNAICS <- function (year) { NAICSyearCode.y <- paste("NAICS_", year, "_Code.y", sep = "") # Generate BEAtoNAICS table from IO table - BEAtoNAICS <- extractBEAtoNAICSfromIOTable(year) + #Note only returns current year + BEAtoNAICS <- extractBEAtoNAICSfromIOTable() # Generate complete NAICSwide table from NAICS list from Census NAICSwide <- getNAICS2to6Digits(year) @@ -142,7 +149,7 @@ getBEAtoNAICS <- function (year) { # Create mapping between BEA and USEEIO code getBEAtoUSEEIO <- function (year) { # Prepare a base BEAtoUSEEIO table from IO table - BEAtoUSEEIO <- extractBEAtoNAICSfromIOTable(year) + BEAtoUSEEIO <- extractBEAtoNAICSfromIOTable() BEAyearDetail <- c(paste("BEA_", year, "_Detail_Code", sep = ""), paste("BEA_", year, "_Detail_Name", sep = "")) # Add USEEIO columns if (year==2007) { @@ -177,6 +184,9 @@ getMasterCrosswalk <- function (year) { BEAtoUSEEIOtoNAICS <- BEAtoUSEEIOtoNAICS[!BEAtoUSEEIOtoNAICS[, BEAyearSectorCode] %in% c("23", "G"), ] BEAtoUSEEIOtoNAICS <- BEAtoUSEEIOtoNAICS[!BEAtoUSEEIOtoNAICS[, BEAyearSummaryCode] %in% c("HS", "ORE", "531"), ] # Load pre-created tables for 23, G, F, and V sectors + Columns <- c(paste0(rep("BEA_", 6), year, rep(c("_Sector", "_Summary", "_Detail"), each = 2), rep(c("_Code", "_Name"), 3)), + paste0(rep("USEEIO", 2), c("_Code", "_Industry")), + paste0(rep("NAICS_", 2), year, c("_Code", "_Name"))) # 23 Crosswalk23 <- utils::read.table(paste0("inst/extdata/23_BEAtoUSEEIOtoNAICS_", year, ".csv"), sep = ",", header = TRUE, stringsAsFactors = FALSE) # HS&ORE @@ -184,16 +194,19 @@ getMasterCrosswalk <- function (year) { # G CrosswalkG <- utils::read.table(paste0("inst/extdata/G_BEAtoUSEEIOtoNAICS_", year, ".csv"), sep = ",", header = TRUE, stringsAsFactors = FALSE) # F - CrosswalkF <- utils::read.table(paste0("inst/extdata/F_BEAtoUSEEIOtoNAICS_", year, ".csv"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + CrosswalkF <- utils::read.table("inst/extdata/F_BEAtoUSEEIOtoNAICS.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(CrosswalkF) <- Columns # V - CrosswalkV <- utils::read.table(paste0("inst/extdata/V_BEAtoUSEEIOtoNAICS_", year, ".csv"), sep = ",", header = TRUE, stringsAsFactors = FALSE) + CrosswalkV <- utils::read.table("inst/extdata/V_BEAtoUSEEIOtoNAICS.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE) + colnames(CrosswalkV) <- Columns # Attach the pre-created 23, G, F, and V sectors to BEAtoUSEEIOtoNAICS BEAtoUSEEIOtoNAICS <- rbind(BEAtoUSEEIOtoNAICS, Crosswalk23, CrosswalkHSandORE, CrosswalkG, CrosswalkF, CrosswalkV) # Add USEEIO_Commodity columns - SectortoCommodity <- utils::read.table(paste0("inst/extdata/Crosswalk_DetailIndustrytoCommodityName", year, "Schema.csv"), + SectortoCommodity <- utils::read.table("inst/extdata/Crosswalk_DetailIndustrytoCommodityNameSchema.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE, quote = "\"") + colnames(SectortoCommodity) <- c(paste0("BEA_", year, "_Detail_Code"), paste0("BEA_", year, "_Detail_Name"), "USEEIO_Name") BEAtoUSEEIOtoNAICS <- merge(BEAtoUSEEIOtoNAICS, SectortoCommodity[, -2], by = paste("BEA_", year, "_Detail_Code", sep = ""), all.x = TRUE) # Keep wanted columns @@ -232,7 +245,7 @@ getMasterCrosswalk <- function (year) { if (year==2007) { MasterCrosswalk <- merge(BEAtoUSEEIOtoNAICS, NAICS2012to2007to2017all, by = "NAICS_2007_Code", all = TRUE) MasterCrosswalk <- MasterCrosswalk[, c(colnames(BEAtoUSEEIOtoNAICS), "NAICS_2012_Code")] - } else { + } else if (year==2012) { MasterCrosswalk <- merge(BEAtoUSEEIOtoNAICS, NAICS2012to2007to2017all, by = "NAICS_2012_Code", all = TRUE) MasterCrosswalk <- MasterCrosswalk[, c(colnames(BEAtoUSEEIOtoNAICS), "NAICS_2007_Code", "NAICS_2017_Code")] # Include 7-, 8-, and 10-digit NAICS (from Census for manufacturing and mining sectors) @@ -247,6 +260,14 @@ getMasterCrosswalk <- function (year) { MasterCrosswalk <- merge(MasterCrosswalk, BEA_Sector_CodeName_Mapping, by = c("BEA_2012_Sector_Code", "BEA_2012_Sector_Name"), all.x = TRUE) MasterCrosswalk[, c("BEA_2012_Sector_Code", "BEA_2012_Sector_Name")] <- MasterCrosswalk[, c("BEA_2012_Sector_Code_agg", "BEA_2012_Sector_Name_agg")] MasterCrosswalk[, c("BEA_2012_Sector_Code_agg", "BEA_2012_Sector_Name_agg")] <- NULL + } else if (year==2017) { + MasterCrosswalk <- merge(BEAtoUSEEIOtoNAICS, NAICS2012to2007to2017all, by = "NAICS_2017_Code", all = TRUE) + MasterCrosswalk <- MasterCrosswalk[, c(colnames(BEAtoUSEEIOtoNAICS), "NAICS_2007_Code", "NAICS_2012_Code")] + # Replace Code and Name for BEA_2012_Sector + BEA_Sector_CodeName_Mapping <- utils::read.table("inst/extdata/BEA_2017_Sector_CodeName_mapping.csv", sep = ",", header = TRUE, stringsAsFactors = FALSE) + MasterCrosswalk <- merge(MasterCrosswalk, BEA_Sector_CodeName_Mapping, by = c("BEA_2017_Sector_Code", "BEA_2017_Sector_Name"), all.x = TRUE) + MasterCrosswalk[, c("BEA_2017_Sector_Code", "BEA_2017_Sector_Name")] <- MasterCrosswalk[, c("BEA_2017_Sector_Code_agg", "BEA_2017_Sector_Name_agg")] + MasterCrosswalk[, c("BEA_2017_Sector_Code_agg", "BEA_2017_Sector_Name_agg")] <- NULL } # Order by NAICS and USEEIO code columns MasterCrosswalk[MasterCrosswalk==""] <- NA @@ -256,12 +277,14 @@ getMasterCrosswalk <- function (year) { return(MasterCrosswalk) } -MasterCrosswalk2012 <- getMasterCrosswalk(2012) -MasterCrosswalk2012 <- MasterCrosswalk2012[, c(paste("BEA_2012", c("Sector", "Summary", "Detail"), "Code", sep = "_"), - paste("NAICS", c(2012, 2007, 2017), "Code", sep = "_"))] -usethis::use_data(MasterCrosswalk2012, overwrite = T) +year <- getSchemaYearfromFileName(getReferenceFileName()) +MasterCrosswalk <- getMasterCrosswalk(year) +diff1 <- dplyr::anti_join(MasterCrosswalk, useeior::MasterCrosswalk) +usethis::use_data(MasterCrosswalk, overwrite = T) -MasterCrosswalk2007 <- getMasterCrosswalk(2007) -MasterCrosswalk2007 <- MasterCrosswalk2007[, 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a/data/Summary_ValueAdded_IO.rda b/data/Summary_ValueAdded_IO_12sch.rda similarity index 100% rename from data/Summary_ValueAdded_IO.rda rename to data/Summary_ValueAdded_IO_12sch.rda diff --git a/data/Summary_ValueAdded_IO_17sch.rda b/data/Summary_ValueAdded_IO_17sch.rda new file mode 100644 index 00000000..5312dc41 Binary files /dev/null and b/data/Summary_ValueAdded_IO_17sch.rda differ diff --git a/inst/extdata/2017_Detail_Schema_Info.csv b/inst/extdata/2017_Detail_Schema_Info.csv new file mode 100644 index 00000000..5718188b --- /dev/null +++ b/inst/extdata/2017_Detail_Schema_Info.csv @@ -0,0 +1,445 @@ +Code,Commodity,Industry,Scrap,UsedGoods,NonComparableImport,RoWAdjustment,ValueAdded,CommodityTotalOutput,IndustryTotalOutput,CommodityIntermediateOutput,HouseholdDemand,InvestmentDemand,ChangeInventories,Export,Import,GovernmentDemand,NaturalGas,Water,Electricity,Petroleum,PersonalTransportRelated,Wholesale,Retail,Transportation,InternationalTradeAdjustment,TaxLessSubsidies 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+23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2372,Land Subdivision +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,2372,Land Subdivision +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,2372,Land Subdivision +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,2372,Land Subdivision +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23721,Land Subdivision +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23721,Land Subdivision +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23721,Land Subdivision +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23721,Land Subdivision +23,Construction,23,Construction,2332C0,Transportation structures and highways and streets,2332C0,Transportation structures and highways and streets,23721,Land Subdivision +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23721,Land Subdivision +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23721,Land Subdivision +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23721,Land Subdivision +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23721,Land Subdivision +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23721,Land Subdivision +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,237210,Land Subdivision +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,237210,Land Subdivision +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,237210,Land Subdivision +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,237210,Land Subdivision +23,Construction,23,Construction,2332C0,Transportation structures and highways and streets,2332C0,Transportation structures and highways and streets,237210,Land Subdivision +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",237210,Land Subdivision +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,237210,Land Subdivision +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,237210,Land Subdivision +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,237210,Land Subdivision +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,237210,Land Subdivision +23,Construction,23,Construction,2332C0,Transportation structures and highways and streets,2332C0,Transportation structures and highways and streets,2373,"Highway, Street, and Bridge Construction" +23,Construction,23,Construction,2332C0,Transportation structures and highways and streets,2332C0,Transportation structures and highways and streets,23731,"Highway, Street, and Bridge Construction" +23,Construction,23,Construction,2332C0,Transportation structures and highways and streets,2332C0,Transportation structures and highways and streets,237310,"Highway, Street, and Bridge Construction " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2379,Other Heavy and Civil Engineering Construction +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23799,Other Heavy and Civil Engineering Construction +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,237990,Other Heavy and Civil Engineering Construction +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238,Specialty Trade Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238,Specialty Trade Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238,Specialty Trade Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238,Specialty Trade Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238,Specialty Trade Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238,Specialty Trade Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238,Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238,Specialty Trade Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238,Specialty Trade Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238,Specialty Trade Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238,Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238,Specialty Trade Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2381,"Foundation, Structure, and Building Exterior Contractors" +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23811,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238110,Poured Concrete Foundation and Structure Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23812,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238120,Structural Steel and Precast Concrete Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23813,Framing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23813,Framing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23813,Framing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23813,Framing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23813,Framing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23813,Framing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23813,Framing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23813,Framing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23813,Framing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23813,Framing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23813,Framing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23813,Framing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238130,Framing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238130,Framing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238130,Framing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238130,Framing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238130,Framing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238130,Framing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238130,Framing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238130,Framing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238130,Framing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238130,Framing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238130,Framing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238130,Framing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23814,Masonry Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23814,Masonry Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23814,Masonry Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23814,Masonry Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23814,Masonry Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23814,Masonry Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23814,Masonry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23814,Masonry Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23814,Masonry Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23814,Masonry Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23814,Masonry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23814,Masonry Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238140,Masonry Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238140,Masonry Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238140,Masonry Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238140,Masonry Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238140,Masonry Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238140,Masonry Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238140,Masonry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238140,Masonry Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238140,Masonry Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238140,Masonry Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238140,Masonry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238140,Masonry Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23815,Glass and Glazing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23815,Glass and Glazing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23815,Glass and Glazing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23815,Glass and Glazing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238150,Glass and Glazing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238150,Glass and Glazing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238150,Glass and Glazing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238150,Glass and Glazing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23816,Roofing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23816,Roofing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23816,Roofing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23816,Roofing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23816,Roofing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23816,Roofing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23816,Roofing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23816,Roofing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23816,Roofing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23816,Roofing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23816,Roofing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23816,Roofing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238160,Roofing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238160,Roofing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238160,Roofing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238160,Roofing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238160,Roofing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238160,Roofing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238160,Roofing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238160,Roofing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238160,Roofing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238160,Roofing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238160,Roofing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238160,Roofing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23817,Siding Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23817,Siding Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23817,Siding Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23817,Siding Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23817,Siding Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23817,Siding Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23817,Siding Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23817,Siding Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23817,Siding Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23817,Siding Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23817,Siding Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23817,Siding Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238170,Siding Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238170,Siding Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238170,Siding Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238170,Siding Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238170,Siding Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238170,Siding Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238170,Siding Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238170,Siding Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238170,Siding Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238170,Siding Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238170,Siding Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238170,Siding Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23819,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238190,"Other Foundation, Structure, and Building Exterior Contractors " +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,2382,Building Equipment Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,2382,Building Equipment Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,2382,Building Equipment Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,2382,Building Equipment Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,2382,Building Equipment Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,2382,Building Equipment Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",2382,Building Equipment Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2382,Building Equipment Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,2382,Building Equipment Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,2382,Building Equipment Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,2382,Building Equipment Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2382,Building Equipment Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23821,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238210,Electrical Contractors and Other Wiring Installation Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23822,"Plumbing, Heating, and Air-Conditioning Contractors" +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238220,"Plumbing, Heating, and Air-Conditioning Contractors " +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23829,Other Building Equipment Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23829,Other Building Equipment Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23829,Other Building Equipment Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23829,Other Building Equipment Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238290,Other Building Equipment Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238290,Other Building Equipment Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238290,Other Building Equipment Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238290,Other Building Equipment Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,2383,Building Finishing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,2383,Building Finishing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,2383,Building Finishing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,2383,Building Finishing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,2383,Building Finishing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,2383,Building Finishing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",2383,Building Finishing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2383,Building Finishing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,2383,Building Finishing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,2383,Building Finishing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,2383,Building Finishing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2383,Building Finishing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23831,Drywall and Insulation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23831,Drywall and Insulation Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238310,Drywall and Insulation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238310,Drywall and Insulation Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23832,Painting and Wall Covering Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238320,Painting and Wall Covering Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23833,Flooring Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23833,Flooring Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23833,Flooring Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23833,Flooring Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23833,Flooring Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23833,Flooring Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23833,Flooring Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23833,Flooring Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23833,Flooring Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23833,Flooring Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23833,Flooring Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23833,Flooring Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238330,Flooring Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238330,Flooring Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238330,Flooring Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238330,Flooring Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238330,Flooring Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238330,Flooring Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238330,Flooring Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238330,Flooring Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238330,Flooring Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238330,Flooring Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238330,Flooring Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238330,Flooring Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23834,Tile and Terrazzo Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238340,Tile and Terrazzo Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23835,Finish Carpentry Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23835,Finish Carpentry Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23835,Finish Carpentry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23835,Finish Carpentry Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238350,Finish Carpentry Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238350,Finish Carpentry Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238350,Finish Carpentry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238350,Finish Carpentry Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23839,Other Building Finishing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23839,Other Building Finishing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23839,Other Building Finishing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23839,Other Building Finishing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238390,Other Building Finishing Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238390,Other Building Finishing Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238390,Other Building Finishing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238390,Other Building Finishing Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",2389,Other Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,2389,Other Specialty Trade Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23891,Site Preparation Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23891,Site Preparation Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23891,Site Preparation Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23891,Site Preparation Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23891,Site Preparation Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23891,Site Preparation Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23891,Site Preparation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23891,Site Preparation Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23891,Site Preparation Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23891,Site Preparation Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23891,Site Preparation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23891,Site Preparation Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238910,Site Preparation Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238910,Site Preparation Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238910,Site Preparation Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238910,Site Preparation Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238910,Site Preparation Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238910,Site Preparation Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238910,Site Preparation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238910,Site Preparation Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238910,Site Preparation Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238910,Site Preparation Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238910,Site Preparation Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238910,Site Preparation Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,23899,All Other Specialty Trade Contractors +23,Construction,23,Construction,230301,Nonresidential maintenance and repair,230301,Nonresidential maintenance and repair,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,230302,Residential maintenance and repair,230302,Residential maintenance and repair,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,233210,Health care structures,233210,Health care structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,233230,Manufacturing structures,233230,Manufacturing structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,233240,Power and communication structures,233240,Power and communication structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,233262,Educational and vocational structures,233262,Educational and vocational structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,2332A0,"Commercial structures, including farm structures",2332A0,"Commercial structures, including farm structures",238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,233411,Single-family residential structures,233411,Single-family residential structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,233412,Multifamily residential structures,233412,Multifamily residential structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,2334A0,Other residential structures,2334A0,Other residential structures,238990,All Other Specialty Trade Contractors +23,Construction,23,Construction,2332D0,Other nonresidential structures,2332D0,Other nonresidential structures,238990,All Other Specialty Trade Contractors diff --git a/inst/extdata/BEA_2017_Sector_CodeName_mapping.csv b/inst/extdata/BEA_2017_Sector_CodeName_mapping.csv new file mode 100644 index 00000000..273e463f --- /dev/null +++ b/inst/extdata/BEA_2017_Sector_CodeName_mapping.csv @@ -0,0 +1,33 @@ +BEA_2017_Sector_Code,BEA_2017_Sector_Name,BEA_2017_Sector_Code_agg,BEA_2017_Sector_Name_agg +11,"AGRICULTURE, FORESTRY, FISHING, AND HUNTING",11,"Agriculture, forestry, fishing, and hunting" +21,MINING,21,Mining +22,UTILITIES,22,Utilities +23,Construction,23,Construction +31ND,NONDURABLE GOODS,31G,Manufacturing +33DG,DURABLE GOODS,31G,Manufacturing +42,WHOLESALE TRADE,42,Wholesale trade +44RT,RETAIL TRADE,44RT,Retail trade +48TW,"TRANSPORTATION AND WAREHOUSING, EXCLUDING POSTAL SERVICE",48TW,Transportation and warehousing +G,Government,G,Government +51,INFORMATION,51,Information +52,FINANCE AND INSURANCE,FIRE,"Finance, insurance, real estate, rental, and leasing" +53,REAL ESTATE AND RENTAL AND LEASING,FIRE,"Finance, insurance, real estate, rental, and leasing" +54,PROFESSIONAL AND TECHNICAL SERVICES,PROF,Professional and business services +55,MANAGEMENT OF COMPANIES AND ENTREPRISES,PROF,Professional and business services +56,ADMINISTRATIVE AND WASTE SERVICES,PROF,Professional and business services +61,EDUCATIONAL SERVICES,6,"Educational services, health care, and social assistance" +62,HEALTH CARE AND SOCIAL ASSISTANCE,6,"Educational services, health care, and social assistance" +71,"ARTS, ENTERTAINMENT, AND RECREATION",7,"Arts, entertainment, recreation, accommodation, and food services" +72,ACCOMMODATION AND FOOD SERVICES,7,"Arts, entertainment, recreation, accommodation, and food services" +81,"OTHER SERVICES, EXCEPT GOVERNMENT",81,"Other services, except government" +Used,"SCRAP, USED AND SECONDHAND GOODS",Used,"Scrap, used and secondhand goods" +Other,NONCOMPARABLE IMPORTS AND REST-OF-THE-WORLD ADJUSTMENT,Other,Noncomparable imports and rest-of-the-world adjustment +F010,Personal consumption expenditures,F010,Personal consumption expenditures +F020,Private fixed investment,F020,Private fixed investment +F030,Change in private inventories,F030,Change in private inventories +F040,Exports of goods and services,F040,Exports of goods and services +F050,Imports of goods and services,F050,Imports of goods and services +F100,Government consumption expenditures and gross investment,F100,Government consumption expenditures and gross investment +V001,Compensation of employees,V001,Compensation of employees +V002,"Taxes on production and imports, less subsidies",V002,"Taxes on production and imports, less subsidies" +V003,Gross operating surplus,V003,Gross operating surplus diff --git a/inst/extdata/Crosswalk_DetailGDPIndustrytoIO.csv b/inst/extdata/Crosswalk_DetailGDPIndustrytoIO.csv new file mode 100644 index 00000000..75c9f954 --- /dev/null +++ b/inst/extdata/Crosswalk_DetailGDPIndustrytoIO.csv @@ -0,0 +1,431 @@ +Gross_Output_Detail_Industry,BEA_2012_Detail_Code,BEA_2017_Detail_Code +Oilseed farming,1111A0,1111A0 +Grain farming,1111B0,1111B0 +Vegetable and melon farming,111200,111200 +Fruit and tree nut farming,111300,111300 +"Greenhouse, nursery, and floriculture production",111400,111400 +Other crop farming,111900,111900 +Dairy cattle and milk production,112120,112120 +"Beef cattle ranching and farming, including feedlots and dual-purpose ranching and farming",1121A0,1121A0 +Poultry and egg production,112300,112300 +"Animal production, except cattle and poultry and eggs",112A00,112A00 +Forestry and logging,113000,113000 +"Fishing, hunting and trapping",114000,114000 +Support activities for agriculture and forestry,115000,115000 +Oil and gas extraction,211000,211000 +Coal mining,212100,212100 +"Copper, nickel, lead, and zinc mining",212230,212230 +"Iron, gold, silver, and other metal ore mining",2122A0,2122A0 +Stone mining and quarrying,212310,212310 +Other nonmetallic mineral mining and quarrying,2123A0,2123A0 +Drilling oil and gas wells,213111,213111 +Other support activities for mining,21311A,21311A +"Electric power generation, transmission, and distribution",221100, +Natural gas distribution,221200,221200 +"Water, sewage and other systems",221300,221300 +Nonresidential maintenance and repair,230301,230301 +Residential maintenance and repair,230302,230302 +Health care structures,233210,233210 +Manufacturing structures,233230,233230 +Power and communication structures,233240,233240 +Educational and vocational structures,233262,233262 +Office and commercial structures,2332A0,2332A0 +Transportation structures and highways and streets,2332C0,2332C0 +Other nonresidential structures,2332D0,2332D0 +Single-family residential structures,233411,233411 +Multifamily residential structures,233412,233412 +Other residential structures,2334A0,2334A0 +Dog and cat food manufacturing,311111,311111 +Other animal food manufacturing,311119,311119 +Flour milling and malt manufacturing,311210,311210 +Wet corn milling,311221,311221 +Soybean and other oilseed processing,311224,311224 +Fats and oils refining and blending,311225,311225 +Breakfast cereal manufacturing,311230,311230 +Sugar and confectionery product manufacturing,311300,311300 +Frozen food manufacturing,311410,311410 +"Fruit and vegetable canning, pickling, and drying",311420,311420 +Cheese manufacturing,311513,311513 +"Dry, condensed, and evaporated dairy product manufacturing",311514,311514 +Fluid milk and butter manufacturing,31151A,31151A +Ice cream and frozen dessert manufacturing,311520,311520 +Poultry processing,311615,311615 +"Animal (except poultry) slaughtering, rendering, and processing",31161A,31161A +Seafood product preparation and packaging,311700,311700 +Bread and bakery product manufacturing,311810,311810 +"Cookie, cracker, pasta, and tortilla manufacturing",3118A0,3118A0 +Snack food manufacturing,311910,311910 +Coffee and tea manufacturing,311920,311920 +Flavoring syrup and concentrate manufacturing,311930,311930 +Seasoning and dressing manufacturing,311940,311940 +All other food manufacturing,311990,311990 +Soft drink and ice manufacturing,312110,312110 +Breweries,312120,312120 +Wineries,312130,312130 +Distilleries,312140,312140 +Tobacco manufacturing,,312200 +Tobacco product manufacturing,312200, +"Fiber, yarn, and thread mills",313100,313100 +Fabric mills,313200,313200 +Textile and fabric finishing and fabric coating mills,313300,313300 +Carpet and rug mills,314110,314110 +Curtain and linen mills,314120,314120 +Other textile product mills,314900,314900 +Apparel manufacturing,315000,315000 +Leather and allied product manufacturing,316000,316000 +Sawmills and wood preservation,321100,321100 +"Veneer, plywood, and engineered wood product manufacturing",321200,321200 +Millwork,321910,321910 +All other wood product manufacturing,3219A0,3219A0 +Pulp mills,322110,322110 +Paper mills,322120,322120 +Paperboard mills,322130,322130 +Paperboard container manufacturing,322210,322210 +Paper Bag and Coated and Treated Paper Manufacturing,322220, +Paper bag and coated and treated paper manufacturing,,322220 +Stationery product manufacturing,322230,322230 +Sanitary paper product manufacturing,322291,322291 +All other converted paper product manufacturing,322299,322299 +Printing,323110,323110 +Support activities for printing,323120,323120 +Petroleum refineries,324110,324110 +Asphalt paving mixture and block manufacturing,324121,324121 +Asphalt shingle and coating materials manufacturing,324122,324122 +Other petroleum and coal products manufacturing,324190,324190 +Petrochemical manufacturing,325110,325110 +Industrial gas manufacturing,325120,325120 +Synthetic dye and pigment manufacturing,325130,325130 +Other Basic Inorganic Chemical Manufacturing,325180, +Other basic inorganic chemical manufacturing,,325180 +Other basic organic chemical manufacturing,325190,325190 +Plastics material and resin manufacturing,325211,325211 +Synthetic rubber and artificial and synthetic fibers and filaments manufacturing,3252A0,3252A0 +Fertilizer manufacturing,325310,325310 +Pesticide and other agricultural chemical manufacturing,325320,325320 +Medicinal and botanical manufacturing,325411,325411 +Pharmaceutical preparation manufacturing,325412,325412 +In-vitro diagnostic substance manufacturing,325413,325413 +Biological product (except diagnostic) manufacturing,325414,325414 +Paint and coating manufacturing,325510,325510 +Adhesive manufacturing,325520,325520 +Soap and cleaning compound manufacturing,325610,325610 +Toilet preparation manufacturing,325620,325620 +Printing ink manufacturing,325910,325910 +All other chemical product and preparation manufacturing,3259A0,3259A0 +Plastics packaging materials and unlaminated film and sheet manufacturing,326110,326110 +"Plastics pipe, pipe fitting, and unlaminated profile shape manufacturing",326120,326120 +"Laminated plastics plate, sheet (except packaging), and shape manufacturing",326130,326130 +Polystyrene foam product manufacturing,326140,326140 +Urethane and other foam product (except polystyrene) manufacturing,326150,326150 +Plastics bottle manufacturing,326160,326160 +Other plastics product manufacturing,326190,326190 +Tire manufacturing,326210,326210 +Rubber and plastics hoses and belting manufacturing,326220,326220 +Other rubber product manufacturing,326290,326290 +Clay product and refractory manufacturing,327100,327100 +Glass and glass product manufacturing,327200,327200 +Cement manufacturing,327310,327310 +Ready-mix concrete manufacturing,327320,327320 +"Concrete pipe, brick, and block manufacturing",327330,327330 +Other concrete product manufacturing,327390,327390 +Lime and gypsum product manufacturing,327400,327400 +Abrasive product manufacturing,327910,327910 +Cut stone and stone product manufacturing,327991,327991 +Ground or treated mineral and earth manufacturing,327992,327992 +Mineral wool manufacturing,327993,327993 +Miscellaneous nonmetallic mineral products,327999,327999 +Iron and steel mills and ferroalloy manufacturing,331110,331110 +Steel product manufacturing from purchased steel,331200,331200 +Alumina refining and primary aluminum production,331313,331313 +Secondary smelting and alloying of aluminum,331314,331314 +Aluminum product manufacturing from purchased aluminum,33131B,33131B +Nonferrous Metal (except Aluminum) Smelting and Refining,331410, +Nonferrous metal (except aluminum) smelting and refining,,331410 +"Copper rolling, drawing, extruding and alloying",331420,331420 +"Nonferrous metal (except copper and aluminum) rolling, drawing, extruding and alloying",331490,331490 +Ferrous metal foundries,331510,331510 +Nonferrous metal foundries,331520,331520 +Custom roll forming,332114,332114 +"Metal crown, closure, and other metal stamping (except automotive)",332119,332119 +"All other forging, stamping, and sintering",33211A,33211A +Cutlery and handtool manufacturing,332200,332200 +Plate work and fabricated structural product manufacturing,332310,332310 +Ornamental and architectural metal products manufacturing,332320,332320 +Power boiler and heat exchanger manufacturing,332410,332410 +Metal tank (heavy gauge) manufacturing,332420,332420 +"Metal can, box, and other metal container (light gauge) manufacturing",332430,332430 +Hardware manufacturing,332500,332500 +Spring and wire product manufacturing,332600,332600 +Machine shops,332710,332710 +"Turned product and screw, nut, and bolt manufacturing",332720,332720 +"Coating, engraving, heat treating and allied activities",332800,332800 +Plumbing fixture fitting and trim manufacturing,332913,332913 +Valve and fittings other than plumbing,33291A,33291A +Ball and roller bearing manufacturing,332991,332991 +Fabricated pipe and pipe fitting manufacturing,332996,332996 +Other fabricated metal manufacturing,332999,332999 +"Ammunition, arms, ordnance, and accessories manufacturing",33299A,33299A +Farm machinery and equipment manufacturing,333111,333111 +Lawn and garden equipment manufacturing,333112,333112 +Construction machinery manufacturing,333120,333120 +Mining and oil and gas field machinery manufacturing,333130,333130 +Semiconductor machinery manufacturing,333242,333242 +Other industrial machinery manufacturing,33329A,33329A +Optical instrument and lens manufacturing,333314,333314 +Photographic and photocopying equipment manufacturing,333316,333316 +Other commercial and service industry machinery manufacturing,333318,333318 +Industrial and commercial fan and blower and air purification equipment manufacturing,333413,333413 +Heating equipment (except warm air furnaces) manufacturing,333414,333414 +"Air conditioning, refrigeration, and warm air heating equipment manufacturing",333415,333415 +Industrial mold manufacturing,333511,333511 +"Special tool, die, jig, and fixture manufacturing",333514,333514 +Machine tool manufacturing,333517,333517 +"Cutting and machine tool accessory, rolling mill, and other metalworking machinery manufacturing",33351B,33351B +Turbine and turbine generator set units manufacturing,333611,333611 +"Speed changer, industrial high-speed drive, and gear manufacturing",333612,333612 +Mechanical power transmission equipment manufacturing,333613,333613 +Other engine equipment manufacturing,333618,333618 +Air and gas compressor manufacturing,333912,333912 +"Measuring, dispensing, and other pumping equipment manufacturing",,333914 +Pump and pumping equipment manufacturing,33391A, +Material handling equipment manufacturing,333920,333920 +Power-driven handtool manufacturing,333991,333991 +Packaging machinery manufacturing,333993,333993 +Industrial process furnace and oven manufacturing,333994,333994 +Other general purpose machinery manufacturing,33399A,33399A +Fluid power process machinery,33399B,33399B +Electronic computer manufacturing,334111,334111 +Computer storage device manufacturing,334112,334112 +Computer terminals and other computer peripheral equipment manufacturing,334118,334118 +Telephone apparatus manufacturing,334210,334210 +Broadcast and wireless communications equipment,334220,334220 +Other communications equipment manufacturing,334290,334290 +Audio and video equipment manufacturing,334300,334300 +Semiconductor and related device manufacturing,334413,334413 +Printed circuit assembly (electronic assembly) manufacturing,334418,334418 +Other electronic component manufacturing,33441A,33441A +Electromedical and electrotherapeutic apparatus manufacturing,334510,334510 +"Search, detection, and navigation instruments manufacturing",334511,334511 +Automatic environmental control manufacturing,334512,334512 +Industrial process variable instruments manufacturing,334513,334513 +Totalizing fluid meter and counting device manufacturing,334514,334514 +Electricity and signal testing instruments manufacturing,334515,334515 +Analytical laboratory instrument manufacturing,334516,334516 +Irradiation apparatus manufacturing,334517,334517 +"Watch, clock, and other measuring and controlling device manufacturing",33451A,33451A +Manufacturing and reproducing magnetic and optical media,334610,334610 +Electric lamp bulb and part manufacturing,335110,335110 +Lighting fixture manufacturing,335120,335120 +Small electrical appliance manufacturing,335210,335210 +Major household appliance manufacturing,,335220 +Household cooking appliance manufacturing,335221, +Household refrigerator and home freezer manufacturing,335222, +Household laundry equipment manufacturing,335224, +Other major household appliance manufacturing,335228, +"Power, distribution, and specialty transformer manufacturing",335311,335311 +Motor and generator manufacturing,335312,335312 +Switchgear and switchboard apparatus manufacturing,335313,335313 +Relay and industrial control manufacturing,335314,335314 +Storage battery manufacturing,335911,335911 +Primary battery manufacturing,335912,335912 +Communication and energy wire and cable manufacturing,335920,335920 +Wiring device manufacturing,335930,335930 +Carbon and graphite product manufacturing,335991,335991 +All other miscellaneous electrical equipment and component manufacturing,335999,335999 +Automobile manufacturing,336111,336111 +Light truck and utility vehicle manufacturing,336112,336112 +Heavy duty truck manufacturing,336120,336120 +Motor vehicle body manufacturing,336211,336211 +Truck trailer manufacturing,336212,336212 +Motor home manufacturing,336213,336213 +Travel trailer and camper manufacturing,336214,336214 +Motor vehicle gasoline engine and engine parts manufacturing,336310,336310 +Motor vehicle electrical and electronic equipment manufacturing,336320,336320 +Motor vehicle transmission and power train parts manufacturing,336350,336350 +Motor vehicle seating and interior trim manufacturing,336360,336360 +Motor vehicle metal stamping,336370,336370 +Other Motor Vehicle Parts Manufacturing,336390, +Other motor vehicle parts manufacturing,,336390 +"Motor vehicle steering, suspension component (except spring), and brake systems manufacturing",3363A0,3363A0 +Aircraft manufacturing,336411,336411 +Aircraft engine and engine parts manufacturing,336412,336412 +Other aircraft parts and auxiliary equipment manufacturing,336413,336413 +Guided missile and space vehicle manufacturing,336414,336414 +Propulsion units and parts for space vehicles and guided missiles,33641A,33641A +Railroad rolling stock manufacturing,336500,336500 +Ship building and repairing,336611,336611 +Boat building,336612,336612 +"Motorcycle, bicycle, and parts manufacturing",336991,336991 +"Military armored vehicle, tank, and tank component manufacturing",336992,336992 +All other transportation equipment manufacturing,336999,336999 +Wood kitchen cabinet and countertop manufacturing,337110,337110 +Upholstered household furniture manufacturing,337121,337121 +Nonupholstered wood household furniture manufacturing,337122,337122 +Institutional furniture manufacturing,337127,337127 +Other household nonupholstered furniture,33712N,33712N +"Showcase, partition, shelving, and locker manufacturing",337215,337215 +Office furniture and custom architectural woodwork and millwork manufacturing,33721A,33721A +Other furniture related product manufacturing,337900,337900 +Surgical and medical instrument manufacturing,339112,339112 +Surgical appliance and supplies manufacturing,339113,339113 +Dental equipment and supplies manufacturing,339114,339114 +Ophthalmic goods manufacturing,339115,339115 +Dental laboratories,339116,339116 +Jewelry and silverware manufacturing,339910,339910 +Sporting and athletic goods manufacturing,339920,339920 +"Doll, toy, and game manufacturing",339930,339930 +Office supplies (except paper) manufacturing,339940,339940 +Sign manufacturing,339950,339950 +All other miscellaneous manufacturing,339990,339990 +Customs duties,4200ID,4200ID +Motor vehicle and motor vehicle parts and supplies,423100,423100 +Professional and commercial equipment and supplies,423400,423400 +Household appliances and electrical and electronic goods,423600,423600 +"Machinery, equipment, and supplies",423800,423800 +Other durable goods merchant wholesalers,423A00,423A00 +Drugs and druggists' sundries,424200,424200 +Grocery and related product wholesalers,424400,424400 +Petroleum and petroleum products,424700,424700 +Other nondurable goods merchant wholesalers,424A00,424A00 +Wholesale electronic markets and agents and brokers,425000,425000 +Motor vehicle and parts dealers,441000,441000 +Building material and garden equipment and supplies dealers,444000,444000 +Food and beverage stores,445000,445000 +Health and personal care stores,446000,446000 +Gasoline stations,447000,447000 +Clothing and clothing accessories stores,448000,448000 +General merchandise stores,452000,452000 +Nonstore retailers,454000,454000 +Air transportation,481000,481000 +Rail transportation,482000,482000 +Water transportation,483000,483000 +Truck transportation,484000,484000 +Transit and ground passenger transportation,485000,485000 +Pipeline transportation,486000,486000 +Scenic and sightseeing transportation and support activities for transportation,48A000,48A000 +Postal service,491000,491000 +Couriers and messengers,492000,492000 +Warehousing and storage,493000,493000 +All other retail,4B0000,4B0000 +Newspaper publishers,511110,511110 +Periodical Publishers,511120,511120 +Book publishers,511130,511130 +"Directory, mailing list, and other publishers",5111A0,5111A0 +Software publishers,511200,511200 +Motion picture and video industries,512100,512100 +Sound recording industries,512200,512200 +Radio and television broadcasting,515100,515100 +Cable and other subscription programming,515200,515200 +Wired telecommunications carriers,517110,517110 +Wireless telecommunications carriers (except satellite),517210,517210 +"Satellite, telecommunications resellers, and all other telecommunications",517A00,517A00 +"Data processing, hosting, and related services",518200,518200 +Internet publishing and broadcasting and Web search portals,519130,519130 +"News syndicates, libraries, archives and all other information services",5191A0,5191A0 +Nondepository credit intermediation and related activities,522A00,522A00 +Other financial investment activities,523900,523900 +Securities and commodity contracts intermediation and brokerage,523A00,523A00 +Direct life insurance carriers,524113,524113 +"Insurance carriers, except direct life",5241XX, +"Insurance carriers, except direct life insurance",5241XX,5241XX +"Insurance agencies, brokerages, and related activities",524200,524200 +"Funds, trusts, and other financial vehicles",525000,525000 +Monetary authorities and depository credit intermediation,52A000,52A000 +Owner-occupied housing,531HSO,531HSO +Tenant-occupied housing,531HST,531HST +Other real estate,531ORE,531ORE +Automotive equipment rental and leasing,532100,532100 +Commercial and industrial machinery and equipment rental and leasing,532400,532400 +General and consumer goods rental,532A00,532A00 +Lessors of nonfinancial intangible assets,533000,533000 +Legal services,541100,541100 +"Accounting, tax preparation, bookkeeping, and payroll services",541200,541200 +"Architectural, engineering, and related services",541300,541300 +Specialized design services,541400,541400 +Custom computer programming services,541511,541511 +Computer systems design services,541512,541512 +"Other computer related services, including facilities management",54151A,54151A +Management consulting services,541610,541610 +Environmental and other technical consulting services,5416A0,5416A0 +Scientific research and development services,541700,541700 +"Advertising, public relations, and related services",541800,541800 +Photographic services,541920,541920 +Veterinary services,541940,541940 +"All other miscellaneous professional, scientific, and technical services",5419A0,5419A0 +Management of companies and enterprises,550000,550000 +Office administrative services,561100,561100 +Facilities support services,561200,561200 +Employment services,561300,561300 +Business support services,561400,561400 +Travel arrangement and reservation services,561500,561500 +Investigation and security services,561600,561600 +Services to buildings and dwellings,561700,561700 +Other support services,561900,561900 +Waste management and remediation services,562000,562000 +Elementary and secondary schools,611100,611100 +"Junior colleges, colleges, universities, and professional schools",611A00,611A00 +Other educational services,611B00,611B00 +Offices of physicians,621100,621100 +Offices of dentists,621200,621200 +Offices of other health practitioners,621300,621300 +Outpatient care centers,621400,621400 +Medical and diagnostic laboratories,621500,621500 +Home health care services,621600,621600 +Other ambulatory health care services,621900,621900 +Hospitals,622000,622000 +Nursing and community care facilities,623A00,623A00 +"Residential mental health, substance abuse, and other residential care facilities",623B00,623B00 +Individual and family services,624100,624100 +Child day care services,624400,624400 +"Community food, housing, and other relief services, including rehabilitation services",624A00,624A00 +Performing arts companies,711100,711100 +Spectator sports,711200,711200 +"Independent artists, writers, and performers",711500,711500 +Promoters of performing arts and sports and agents for public figures,711A00,711A00 +"Museums, historical sites, zoos, and parks",712000,712000 +Amusement parks and arcades,713100,713100 +Gambling industries (except casino hotels),713200,713200 +Other amusement and recreation industries,713900,713900 +Accommodation,721000,721000 +Full-service restaurants,722110,722110 +Limited-service restaurants,722211,722211 +All other food and drinking places,722A00,722A00 +Automotive repair and maintenance,811100,811100 +Electronic and precision equipment repair and maintenance,811200,811200 +Commercial and industrial machinery and equipment repair and maintenance,811300,811300 +Personal and household goods repair and maintenance,811400,811400 +Personal care services,812100,812100 +Death care services,812200,812200 +Dry-cleaning and laundry services,812300,812300 +Other personal services,812900,812900 +Religious organizations,813100,813100 +"Grantmaking, giving, and social advocacy organizations",813A00,813A00 +"Civic, social, professional, and similar organizations",813B00,813B00 +Private households,814000,814000 +State and local government educational services,GSLGE, +State and local government hospitals and health services,GSLGH, +State and local government other services,GSLGO, +State and local government (educational services),,GSLGE +State and local government (hospitals and health services),,GSLGH +State and local government (other services),,GSLGO +Federal electric utilities,S00101,S00101 +Other federal government enterprises,S00102,S00102 +State and local government passenger transit,S00201,S00201 +State and local government electric utilities,S00202,S00202 +Other state and local government enterprises,S00203,S00203 +Federal general government (defense),S00500,S00500 +Federal general government (nondefense),S00600,S00600 +Geothermal electric power generation,221100,221100 +Biomass electric power generation,221100,221100 +Other electric power generation,221100,221100 +Electric bulk power transmission and control,221100,221100 +Furniture and home furnishings stores,4B0000,4B0000 +Electronics and appliance stores,4B0000,4B0000 +"Sporting goods, hobby, book, and music stores",4B0000,4B0000 +Miscellaneous store retailers,4B0000,4B0000 +Hydroelectric power generation,221100,221100 +Fossil fuel electric power generation,221100,221100 +Nuclear electric power generation,221100,221100 +Solar electric power generation,221100,221100 +Wind electric power generation,221100,221100 +Electric power distribution,221100,221100 diff --git a/inst/extdata/Crosswalk_DetailGDPIndustrytoIO2012Schema.csv b/inst/extdata/Crosswalk_DetailGDPIndustrytoIO2012Schema.csv deleted file mode 100644 index d53cb859..00000000 --- a/inst/extdata/Crosswalk_DetailGDPIndustrytoIO2012Schema.csv +++ /dev/null @@ -1,421 +0,0 @@ -Gross_Output_Detail_Industry,BEA_2012_Detail_Code -Oilseed farming,1111A0 -Grain farming,1111B0 -Vegetable and melon farming,111200 -Fruit and tree nut farming,111300 -"Greenhouse, nursery, and floriculture production",111400 -Other crop farming,111900 -Dairy cattle and milk production,112120 -"Beef cattle ranching and farming, including feedlots and dual-purpose ranching and farming",1121A0 -Poultry and egg production,112300 -"Animal production, except cattle and poultry and eggs",112A00 -Forestry and logging,113000 -"Fishing, hunting and trapping",114000 -Support activities for agriculture and forestry,115000 -Oil and gas extraction,211000 -Coal mining,212100 -"Copper, nickel, lead, and zinc mining",212230 -"Iron, gold, silver, and other metal ore mining",2122A0 -Stone mining and quarrying,212310 -Other nonmetallic mineral mining and quarrying,2123A0 -Drilling oil and gas wells,213111 -Other support activities for mining,21311A -"Electric power generation, transmission, and distribution",221100 -Natural gas distribution,221200 -"Water, sewage and other systems",221300 -Nonresidential maintenance and repair,230301 -Residential maintenance and repair,230302 -Health care structures,233210 -Manufacturing structures,233230 -Power and communication structures,233240 -Educational and vocational structures,233262 -Office and commercial structures,2332A0 -Transportation structures and highways and streets,2332C0 -Other nonresidential structures,2332D0 -Single-family residential structures,233411 -Multifamily residential structures,233412 -Other residential structures,2334A0 -Dog and cat food manufacturing,311111 -Other animal food manufacturing,311119 -Flour milling and malt manufacturing,311210 -Wet corn milling,311221 -Soybean and other oilseed processing,311224 -Fats and oils refining and blending,311225 -Breakfast cereal manufacturing,311230 -Sugar and confectionery product manufacturing,311300 -Frozen food manufacturing,311410 -"Fruit and vegetable canning, pickling, and drying",311420 -Cheese manufacturing,311513 -"Dry, condensed, and evaporated dairy product manufacturing",311514 -Fluid milk and butter manufacturing,31151A -Ice cream and frozen dessert manufacturing,311520 -Poultry processing,311615 -"Animal (except poultry) slaughtering, rendering, and processing",31161A -Seafood product preparation and packaging,311700 -Bread and bakery product manufacturing,311810 -"Cookie, cracker, pasta, and tortilla manufacturing",3118A0 -Snack food manufacturing,311910 -Coffee and tea manufacturing,311920 -Flavoring syrup and concentrate manufacturing,311930 -Seasoning and dressing manufacturing,311940 -All other food manufacturing,311990 -Soft drink and ice manufacturing,312110 -Breweries,312120 -Wineries,312130 -Distilleries,312140 -Tobacco product manufacturing,312200 -"Fiber, yarn, and thread mills",313100 -Fabric mills,313200 -Textile and fabric finishing and fabric coating mills,313300 -Carpet and rug mills,314110 -Curtain and linen mills,314120 -Other textile product mills,314900 -Apparel manufacturing,315000 -Leather and allied product manufacturing,316000 -Sawmills and wood preservation,321100 -"Veneer, plywood, and engineered wood product manufacturing",321200 -Millwork,321910 -All other wood product manufacturing,3219A0 -Pulp mills,322110 -Paper mills,322120 -Paperboard mills,322130 -Paperboard container manufacturing,322210 -Paper Bag and Coated and Treated Paper Manufacturing,322220 -Stationery product manufacturing,322230 -Sanitary paper product manufacturing,322291 -All other converted paper product manufacturing,322299 -Printing,323110 -Support activities for printing,323120 -Petroleum refineries,324110 -Asphalt paving mixture and block manufacturing,324121 -Asphalt shingle and coating materials manufacturing,324122 -Other petroleum and coal products manufacturing,324190 -Petrochemical manufacturing,325110 -Industrial gas manufacturing,325120 -Synthetic dye and pigment manufacturing,325130 -Other Basic Inorganic Chemical Manufacturing,325180 -Other basic organic chemical manufacturing,325190 -Plastics material and resin manufacturing,325211 -Synthetic rubber and artificial and synthetic fibers and filaments manufacturing,3252A0 -Fertilizer manufacturing,325310 -Pesticide and other agricultural chemical manufacturing,325320 -Medicinal and botanical manufacturing,325411 -Pharmaceutical preparation manufacturing,325412 -In-vitro diagnostic substance manufacturing,325413 -Biological product (except diagnostic) manufacturing,325414 -Paint and coating manufacturing,325510 -Adhesive manufacturing,325520 -Soap and cleaning compound manufacturing,325610 -Toilet preparation manufacturing,325620 -Printing ink manufacturing,325910 -All other chemical product and preparation manufacturing,3259A0 -Plastics packaging materials and unlaminated film and sheet manufacturing,326110 -"Plastics pipe, pipe fitting, and unlaminated profile shape manufacturing",326120 -"Laminated plastics plate, sheet (except packaging), and shape manufacturing",326130 -Polystyrene foam product manufacturing,326140 -Urethane and other foam product (except polystyrene) manufacturing,326150 -Plastics bottle manufacturing,326160 -Other plastics product manufacturing,326190 -Tire manufacturing,326210 -Rubber and plastics hoses and belting manufacturing,326220 -Other rubber product manufacturing,326290 -Clay product and refractory manufacturing,327100 -Glass and glass product manufacturing,327200 -Cement manufacturing,327310 -Ready-mix concrete manufacturing,327320 -"Concrete pipe, brick, and block manufacturing",327330 -Other concrete product manufacturing,327390 -Lime and gypsum product manufacturing,327400 -Abrasive product manufacturing,327910 -Cut stone and stone product manufacturing,327991 -Ground or treated mineral and earth manufacturing,327992 -Mineral wool manufacturing,327993 -Miscellaneous nonmetallic mineral products,327999 -Iron and steel mills and ferroalloy manufacturing,331110 -Steel product manufacturing from purchased steel,331200 -Alumina refining and primary aluminum production,331313 -Secondary smelting and alloying of aluminum,331314 -Aluminum product manufacturing from purchased aluminum,33131B -Nonferrous Metal (except Aluminum) Smelting and Refining,331410 -"Copper rolling, drawing, extruding and alloying",331420 -"Nonferrous metal (except copper and aluminum) rolling, drawing, extruding and alloying",331490 -Ferrous metal foundries,331510 -Nonferrous metal foundries,331520 -Custom roll forming,332114 -"Metal crown, closure, and other metal stamping (except automotive)",332119 -"All other forging, stamping, and sintering",33211A -Cutlery and handtool manufacturing,332200 -Plate work and fabricated structural product manufacturing,332310 -Ornamental and architectural metal products manufacturing,332320 -Power boiler and heat exchanger manufacturing,332410 -Metal tank (heavy gauge) manufacturing,332420 -"Metal can, box, and other metal container (light gauge) manufacturing",332430 -Hardware manufacturing,332500 -Spring and wire product manufacturing,332600 -Machine shops,332710 -"Turned product and screw, nut, and bolt manufacturing",332720 -"Coating, engraving, heat treating and allied activities",332800 -Plumbing fixture fitting and trim manufacturing,332913 -Valve and fittings other than plumbing,33291A -Ball and roller bearing manufacturing,332991 -Fabricated pipe and pipe fitting manufacturing,332996 -Other fabricated metal manufacturing,332999 -"Ammunition, arms, ordnance, and accessories manufacturing",33299A -Farm machinery and equipment manufacturing,333111 -Lawn and garden equipment manufacturing,333112 -Construction machinery manufacturing,333120 -Mining and oil and gas field machinery manufacturing,333130 -Semiconductor machinery manufacturing,333242 -Other industrial machinery manufacturing,33329A -Optical instrument and lens manufacturing,333314 -Photographic and photocopying equipment manufacturing,333316 -Other commercial and service industry machinery manufacturing,333318 -Industrial and commercial fan and blower and air purification equipment manufacturing,333413 -Heating equipment (except warm air furnaces) manufacturing,333414 -"Air conditioning, refrigeration, and warm air heating equipment manufacturing",333415 -Industrial mold manufacturing,333511 -"Special tool, die, jig, and fixture manufacturing",333514 -Machine tool manufacturing,333517 -"Cutting and machine tool accessory, rolling mill, and other metalworking machinery manufacturing",33351B -Turbine and turbine generator set units manufacturing,333611 -"Speed changer, industrial high-speed drive, and gear manufacturing",333612 -Mechanical power transmission equipment manufacturing,333613 -Other engine equipment manufacturing,333618 -Air and gas compressor manufacturing,333912 -Pump and pumping equipment manufacturing,33391A -Material handling equipment manufacturing,333920 -Power-driven handtool manufacturing,333991 -Packaging machinery manufacturing,333993 -Industrial process furnace and oven manufacturing,333994 -Other general purpose machinery manufacturing,33399A -Fluid power process machinery,33399B -Electronic computer manufacturing,334111 -Computer storage device manufacturing,334112 -Computer terminals and other computer peripheral equipment manufacturing,334118 -Telephone apparatus manufacturing,334210 -Broadcast and wireless communications equipment,334220 -Other communications equipment manufacturing,334290 -Audio and video equipment manufacturing,334300 -Semiconductor and related device manufacturing,334413 -Printed circuit assembly (electronic assembly) manufacturing,334418 -Other electronic component manufacturing,33441A -Electromedical and electrotherapeutic apparatus manufacturing,334510 -"Search, detection, and navigation instruments manufacturing",334511 -Automatic environmental control manufacturing,334512 -Industrial process variable instruments manufacturing,334513 -Totalizing fluid meter and counting device manufacturing,334514 -Electricity and signal testing instruments manufacturing,334515 -Analytical laboratory instrument manufacturing,334516 -Irradiation apparatus manufacturing,334517 -"Watch, clock, and other measuring and controlling device manufacturing",33451A -Manufacturing and reproducing magnetic and optical media,334610 -Electric lamp bulb and part manufacturing,335110 -Lighting fixture manufacturing,335120 -Small electrical appliance manufacturing,335210 -Household cooking appliance manufacturing,335221 -Household refrigerator and home freezer manufacturing,335222 -Household laundry equipment manufacturing,335224 -Other major household appliance manufacturing,335228 -"Power, distribution, and specialty transformer manufacturing",335311 -Motor and generator manufacturing,335312 -Switchgear and switchboard apparatus manufacturing,335313 -Relay and industrial control manufacturing,335314 -Storage battery manufacturing,335911 -Primary battery manufacturing,335912 -Communication and energy wire and cable manufacturing,335920 -Wiring device manufacturing,335930 -Carbon and graphite product manufacturing,335991 -All other miscellaneous electrical equipment and component manufacturing,335999 -Automobile manufacturing,336111 -Light truck and utility vehicle manufacturing,336112 -Heavy duty truck manufacturing,336120 -Motor vehicle body manufacturing,336211 -Truck trailer manufacturing,336212 -Motor home manufacturing,336213 -Travel trailer and camper manufacturing,336214 -Motor vehicle gasoline engine and engine parts manufacturing,336310 -Motor vehicle electrical and electronic equipment manufacturing,336320 -Motor vehicle transmission and power train parts manufacturing,336350 -Motor vehicle seating and interior trim manufacturing,336360 -Motor vehicle metal stamping,336370 -Other Motor Vehicle Parts Manufacturing,336390 -"Motor vehicle steering, suspension component (except spring), and brake systems manufacturing",3363A0 -Aircraft manufacturing,336411 -Aircraft engine and engine parts manufacturing,336412 -Other aircraft parts and auxiliary equipment manufacturing,336413 -Guided missile and space vehicle manufacturing,336414 -Propulsion units and parts for space vehicles and guided missiles,33641A -Railroad rolling stock manufacturing,336500 -Ship building and repairing,336611 -Boat building,336612 -"Motorcycle, bicycle, and parts manufacturing",336991 -"Military armored vehicle, tank, and tank component manufacturing",336992 -All other transportation equipment manufacturing,336999 -Wood kitchen cabinet and countertop manufacturing,337110 -Upholstered household furniture manufacturing,337121 -Nonupholstered wood household furniture manufacturing,337122 -Institutional furniture manufacturing,337127 -Other household nonupholstered furniture,33712N -"Showcase, partition, shelving, and locker manufacturing",337215 -Office furniture and custom architectural woodwork and millwork manufacturing,33721A -Other furniture related product manufacturing,337900 -Surgical and medical instrument manufacturing,339112 -Surgical appliance and supplies manufacturing,339113 -Dental equipment and supplies manufacturing,339114 -Ophthalmic goods manufacturing,339115 -Dental laboratories,339116 -Jewelry and silverware manufacturing,339910 -Sporting and athletic goods manufacturing,339920 -"Doll, toy, and game manufacturing",339930 -Office supplies (except paper) manufacturing,339940 -Sign manufacturing,339950 -All other miscellaneous manufacturing,339990 -Customs duties,4200ID -Motor vehicle and motor vehicle parts and supplies,423100 -Professional and commercial equipment and supplies,423400 -Household appliances and electrical and electronic goods,423600 -"Machinery, equipment, and supplies",423800 -Other durable goods merchant wholesalers,423A00 -Drugs and druggists' sundries,424200 -Grocery and related product wholesalers,424400 -Petroleum and petroleum products,424700 -Other nondurable goods merchant wholesalers,424A00 -Wholesale electronic markets and agents and brokers,425000 -Motor vehicle and parts dealers,441000 -Building material and garden equipment and supplies dealers,444000 -Food and beverage stores,445000 -Health and personal care stores,446000 -Gasoline stations,447000 -Clothing and clothing accessories stores,448000 -General merchandise stores,452000 -Nonstore retailers,454000 -Air transportation,481000 -Rail transportation,482000 -Water transportation,483000 -Truck transportation,484000 -Transit and ground passenger transportation,485000 -Pipeline transportation,486000 -Scenic and sightseeing transportation and support activities for transportation,48A000 -Postal service,491000 -Couriers and messengers,492000 -Warehousing and storage,493000 -All other retail,4B0000 -Newspaper publishers,511110 -Periodical Publishers,511120 -Book publishers,511130 -"Directory, mailing list, and other publishers",5111A0 -Software publishers,511200 -Motion picture and video industries,512100 -Sound recording industries,512200 -Radio and television broadcasting,515100 -Cable and other subscription programming,515200 -Wired telecommunications carriers,517110 -Wireless telecommunications carriers (except satellite),517210 -"Satellite, telecommunications resellers, and all other telecommunications",517A00 -"Data processing, hosting, and related services",518200 -Internet publishing and broadcasting and Web search portals,519130 -"News syndicates, libraries, archives and all other information services",5191A0 -Nondepository credit intermediation and related activities,522A00 -Other financial investment activities,523900 -Securities and commodity contracts intermediation and brokerage,523A00 -Direct life insurance carriers,524113 -"Insurance carriers, except direct life",5241XX -"Insurance carriers, except direct life insurance",5241XX -"Insurance agencies, brokerages, and related activities",524200 -"Funds, trusts, and other financial vehicles",525000 -Monetary authorities and depository credit intermediation,52A000 -Owner-occupied housing,531HSO -Tenant-occupied housing,531HST -Other real estate,531ORE -Automotive equipment rental and leasing,532100 -Commercial and industrial machinery and equipment rental and leasing,532400 -General and consumer goods rental,532A00 -Lessors of nonfinancial intangible assets,533000 -Legal services,541100 -"Accounting, tax preparation, bookkeeping, and payroll services",541200 -"Architectural, engineering, and related services",541300 -Specialized design services,541400 -Custom computer programming services,541511 -Computer systems design services,541512 -"Other computer related services, including facilities management",54151A -Management consulting services,541610 -Environmental and other technical consulting services,5416A0 -Scientific research and development services,541700 -"Advertising, public relations, and related services",541800 -Photographic services,541920 -Veterinary services,541940 -"All other miscellaneous professional, scientific, and technical services",5419A0 -Management of companies and enterprises,550000 -Office administrative services,561100 -Facilities support services,561200 -Employment services,561300 -Business support services,561400 -Travel arrangement and reservation services,561500 -Investigation and security services,561600 -Services to buildings and dwellings,561700 -Other support services,561900 -Waste management and remediation services,562000 -Elementary and secondary schools,611100 -"Junior colleges, colleges, universities, and professional schools",611A00 -Other educational services,611B00 -Offices of physicians,621100 -Offices of dentists,621200 -Offices of other health practitioners,621300 -Outpatient care centers,621400 -Medical and diagnostic laboratories,621500 -Home health care services,621600 -Other ambulatory health care services,621900 -Hospitals,622000 -Nursing and community care facilities,623A00 -"Residential mental health, substance abuse, and other residential care facilities",623B00 -Individual and family services,624100 -Child day care services,624400 -"Community food, housing, and other relief services, including rehabilitation services",624A00 -Performing arts companies,711100 -Spectator sports,711200 -"Independent artists, writers, and performers",711500 -Promoters of performing arts and sports and agents for public figures,711A00 -"Museums, historical sites, zoos, and parks",712000 -Amusement parks and arcades,713100 -Gambling industries (except casino hotels),713200 -Other amusement and recreation industries,713900 -Accommodation,721000 -Full-service restaurants,722110 -Limited-service restaurants,722211 -All other food and drinking places,722A00 -Automotive repair and maintenance,811100 -Electronic and precision equipment repair and maintenance,811200 -Commercial and industrial machinery and equipment repair and maintenance,811300 -Personal and household goods repair and maintenance,811400 -Personal care services,812100 -Death care services,812200 -Dry-cleaning and laundry services,812300 -Other personal services,812900 -Religious organizations,813100 -"Grantmaking, giving, and social advocacy organizations",813A00 -"Civic, social, professional, and similar organizations",813B00 -Private households,814000 -State and local government educational services,GSLGE -State and local government hospitals and health services,GSLGH -State and local government other services,GSLGO -Federal electric utilities,S00101 -Other federal government enterprises,S00102 -State and local government passenger transit,S00201 -State and local government electric utilities,S00202 -Other state and local government enterprises,S00203 -Federal general government (defense),S00500 -Federal general government (nondefense),S00600 -Geothermal electric power generation,221100 -Biomass electric power generation,221100 -Other electric power generation,221100 -Electric bulk power transmission and control,221100 -Furniture and home furnishings stores,4B0000 -Electronics and appliance stores,4B0000 -"Sporting goods, hobby, book, and music stores",4B0000 -Miscellaneous store retailers,4B0000 -Hydroelectric power generation,221100 -Fossil fuel electric power generation,221100 -Nuclear electric power generation,221100 -Solar electric power generation,221100 -Wind electric power generation,221100 -Electric power distribution,221100 \ No newline at end of file diff --git a/inst/extdata/Crosswalk_DetailIndustrytoCommodityName2012Schema.csv b/inst/extdata/Crosswalk_DetailIndustrytoCommodityNameSchema.csv similarity index 99% rename from inst/extdata/Crosswalk_DetailIndustrytoCommodityName2012Schema.csv rename to inst/extdata/Crosswalk_DetailIndustrytoCommodityNameSchema.csv index 6f307519..1666dbed 100644 --- a/inst/extdata/Crosswalk_DetailIndustrytoCommodityName2012Schema.csv +++ b/inst/extdata/Crosswalk_DetailIndustrytoCommodityNameSchema.csv @@ -1,4 +1,4 @@ -BEA_2012_Detail_Code,BEA_2012_Detail_Name,USEEIO_Name +BEA_Detail_Code,BEA_Detail_Name,USEEIO_Name 1111A0,Oilseed farming,"Fresh soybeans, canola, flaxseeds, and other oilseeds" 1111B0,Grain farming,"Fresh wheat, corn, rice, and other grains" 111200,Vegetable and melon farming,"Fresh vegetables, melons, and potatoes" @@ -183,6 +183,7 @@ BEA_2012_Detail_Code,BEA_2012_Detail_Name,USEEIO_Name 333618,Other engine equipment manufacturing,Other engine equipment 333912,Air and gas compressor manufacturing,Air and gas compressors 33391A,Pump and pumping equipment manufacturing,Pumps and pumping equipment +333914,Pump and pumping equipment manufacturing,Pumps and pumping equipment 333920,Material handling equipment manufacturing,Material handling equipment 333991,Power-driven handtool manufacturing,Power tools 333993,Packaging machinery manufacturing,Packaging machinery @@ -212,6 +213,7 @@ BEA_2012_Detail_Code,BEA_2012_Detail_Name,USEEIO_Name 335110,Electric lamp bulb and part manufacturing,Light bulbs 335120,Lighting fixture manufacturing,Light fixtures 335210,Small electrical appliance manufacturing,Small electrical appliances +335220,Major household appliance manufacturing,Household appliances 335221,Household cooking appliance manufacturing,Home cooking appliances 335222,Household refrigerator and home freezer manufacturing,Home refrigerators and freezers 335224,Household laundry equipment manufacturing,Home laundry machines @@ -407,4 +409,4 @@ S00401,Scrap, S00402,Used and secondhand goods,Used and secondhand goods S00500,Federal general government (defense),Federal government (defense) S00600,Federal general government (nondefense),Federal government (nondefense) -S00900,Rest of the world adjustment,Rest of the world adjustment \ No newline at end of file +S00900,Rest of the world adjustment,Rest of the world adjustment diff --git a/inst/extdata/F_BEAtoUSEEIOtoNAICS_2012.csv b/inst/extdata/F_BEAtoUSEEIOtoNAICS.csv similarity index 94% rename from inst/extdata/F_BEAtoUSEEIOtoNAICS_2012.csv rename to inst/extdata/F_BEAtoUSEEIOtoNAICS.csv index 1ae6b023..36e566cb 100644 --- a/inst/extdata/F_BEAtoUSEEIOtoNAICS_2012.csv +++ b/inst/extdata/F_BEAtoUSEEIOtoNAICS.csv @@ -1,22 +1,22 @@ -BEA_2012_Sector_Code,BEA_2012_Sector_Name,BEA_2012_Summary_Code,BEA_2012_Summary_Name,BEA_2012_Detail_Code,BEA_2012_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_2012_Code,NAICS_2012_Name -F010,Personal consumption expenditures,F010,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Households -F010,Personal consumption expenditures,F010,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Personal consumption expenditures,F010,Households -F020,Private fixed investment,F02E,Nonresidential private fixed investment in structures,F02E00,Nonresidential private fixed investment in equipment,F02E00,Nonresidential private fixed investment in equipment,, -F020,Private fixed investment,F02N,Nonresidential private fixed investment in equipment,F02N00,Nonresidential private fixed investment in intellectual property products,F02N00,Nonresidential private fixed investment in intellectual property products,, -F020,Private fixed investment,F02R,Nonresidential private fixed investment in intellectual property products,F02R00,Residential private fixed investment,F02R00,Residential private fixed investment,, -F020,Private fixed investment,F02S,Residential private fixed investment,F02S00,Nonresidential private fixed investment in structures,F02S00,Nonresidential private fixed investment in structures,, -F030,Change in private inventories,F030,Change in private inventories,F03000,Change in private inventories,F03000,Change in private inventories,, -F040,Exports of goods and services,F040,Exports of goods and services,F04000,Exports of goods and services,F04000,Exports of goods and services,, -F050,Imports of goods and services,F050,Imports of goods and services,F05000,Imports of goods and services,F05000,Imports of goods and services,, -F100,Government consumption expenditures and gross investment,F06C,Federal national defense: Consumption expenditures,F06C00,Federal Government defense: Consumption expenditures,F06C00,Federal Government defense: Consumption expenditures,, -F100,Government consumption expenditures and gross investment,F06E,Federal national defense: Gross investment in structures,F06E00,Federal national defense: Gross investment in equipment,F06E00,Federal national defense: Gross investment in equipment,, -F100,Government consumption expenditures and gross investment,F06N,Federal national defense: Gross investment in equipment,F06N00,Federal national defense: Gross investment in intellectual property products,F06N00,Federal national defense: Gross investment in intellectual property products,, -F100,Government consumption expenditures and gross investment,F06S,Federal national defense: Gross investment in intellectual property products,F06S00,Federal national defense: Gross investment in structures,F06S00,Federal national defense: Gross investment in structures,, -F100,Government consumption expenditures and gross investment,F07C,Federal national nondefense: Consumption expenditures,F07C00,Federal Government nondefense: Consumption expenditures,F07C00,Federal Government nondefense: Consumption expenditures,, -F100,Government consumption expenditures and gross investment,F07E,Federal national nondefense: Gross investment in structures,F07E00,Federal nondefense: Gross investment in equipment,F07E00,Federal nondefense: Gross investment in equipment,, -F100,Government consumption expenditures and gross investment,F07N,Federal national nondefense: Gross investment in equipment,F07N00,Federal nondefense: Gross investment in intellectual property products,F07N00,Federal nondefense: Gross investment in intellectual property products,, -F100,Government consumption expenditures and gross investment,F07S,Federal national nondefense: Gross investment in intellectual property products,F07S00,Federal nondefense: Gross investment in structures,F07S00,Federal nondefense: Gross investment in structures,, -F100,Government consumption expenditures and gross investment,F10C,State and local: Consumption expenditures,F10C00,State and local government consumption expenditures,F10C00,State and local government consumption expenditures,, -F100,Government consumption expenditures and gross investment,F10E,State and local: Gross investment in structures,F10E00,State and local: Gross investment in equipment,F10E00,State and local: Gross investment in equipment,, -F100,Government consumption expenditures and gross investment,F10N,State and local: Gross investment in equipment,F10N00,State and local: Gross investment in intellectual property products,F10N00,State and local: Gross investment in intellectual property products,, -F100,Government consumption expenditures and gross investment,F10S,State and local: Gross investment in intellectual property products,F10S00,State and local: Gross investment in structures,F10S00,State and local: Gross investment in structures,, \ No newline at end of file +BEA_Sector_Code,BEA_Sector_Name,BEA_Summary_Code,BEA_Summary_Name,BEA_Detail_Code,BEA_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_Code,NAICS_Name +F010,Personal consumption expenditures,F010,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Households +F010,Personal consumption expenditures,F010,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Personal consumption expenditures,F010,Households +F020,Private fixed investment,F02E,Nonresidential private fixed investment in structures,F02E00,Nonresidential private fixed investment in equipment,F02E00,Nonresidential private fixed investment in equipment,, +F020,Private fixed investment,F02N,Nonresidential private fixed investment in equipment,F02N00,Nonresidential private fixed investment in intellectual property products,F02N00,Nonresidential private fixed investment in intellectual property products,, +F020,Private fixed investment,F02R,Nonresidential private fixed investment in intellectual property products,F02R00,Residential private fixed investment,F02R00,Residential private fixed investment,, +F020,Private fixed investment,F02S,Residential private fixed investment,F02S00,Nonresidential private fixed investment in structures,F02S00,Nonresidential private fixed investment in structures,, +F030,Change in private inventories,F030,Change in private inventories,F03000,Change in private inventories,F03000,Change in private inventories,, +F040,Exports of goods and services,F040,Exports of goods and services,F04000,Exports of goods and services,F04000,Exports of goods and services,, +F050,Imports of goods and services,F050,Imports of goods and services,F05000,Imports of goods and services,F05000,Imports of goods and services,, +F100,Government consumption expenditures and gross investment,F06C,Federal national defense: Consumption expenditures,F06C00,Federal Government defense: Consumption expenditures,F06C00,Federal Government defense: Consumption expenditures,, +F100,Government consumption expenditures and gross investment,F06E,Federal national defense: Gross investment in structures,F06E00,Federal national defense: Gross investment in equipment,F06E00,Federal national defense: Gross investment in equipment,, +F100,Government consumption expenditures and gross investment,F06N,Federal national defense: Gross investment in equipment,F06N00,Federal national defense: Gross investment in intellectual property products,F06N00,Federal national defense: Gross investment in intellectual property products,, +F100,Government consumption expenditures and gross investment,F06S,Federal national defense: Gross investment in intellectual property products,F06S00,Federal national defense: Gross investment in structures,F06S00,Federal national defense: Gross investment in structures,, +F100,Government consumption expenditures and gross investment,F07C,Federal national nondefense: Consumption expenditures,F07C00,Federal Government nondefense: Consumption expenditures,F07C00,Federal Government nondefense: Consumption expenditures,, +F100,Government consumption expenditures and gross investment,F07E,Federal national nondefense: Gross investment in structures,F07E00,Federal nondefense: Gross investment in equipment,F07E00,Federal nondefense: Gross investment in equipment,, +F100,Government consumption expenditures and gross investment,F07N,Federal national nondefense: Gross investment in equipment,F07N00,Federal nondefense: Gross investment in intellectual property products,F07N00,Federal nondefense: Gross investment in intellectual property products,, +F100,Government consumption expenditures and gross investment,F07S,Federal national nondefense: Gross investment in intellectual property products,F07S00,Federal nondefense: Gross investment in structures,F07S00,Federal nondefense: Gross investment in structures,, +F100,Government consumption expenditures and gross investment,F10C,State and local: Consumption expenditures,F10C00,State and local government consumption expenditures,F10C00,State and local government consumption expenditures,, +F100,Government consumption expenditures and gross investment,F10E,State and local: Gross investment in structures,F10E00,State and local: Gross investment in equipment,F10E00,State and local: Gross investment in equipment,, +F100,Government consumption expenditures and gross investment,F10N,State and local: Gross investment in equipment,F10N00,State and local: Gross investment in intellectual property products,F10N00,State and local: Gross investment in intellectual property products,, +F100,Government consumption expenditures and gross investment,F10S,State and local: Gross investment in intellectual property products,F10S00,State and local: Gross investment in structures,F10S00,State and local: Gross investment in structures,, diff --git a/inst/extdata/F_BEAtoUSEEIOtoNAICS_2007.csv b/inst/extdata/F_BEAtoUSEEIOtoNAICS_2007.csv deleted file mode 100644 index b751808d..00000000 --- a/inst/extdata/F_BEAtoUSEEIOtoNAICS_2007.csv +++ /dev/null @@ -1,21 +0,0 @@ -BEA_2007_Sector_Code,BEA_2007_Sector_Name,BEA_2007_Summary_Code,BEA_2007_Summary_Name,BEA_2007_Detail_Code,BEA_2007_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_2007_Code,NAICS_2007_Name -F010,Personal consumption expenditures,F010,Personal consumption expenditures,F01000,Personal consumption expenditures,F01000,Personal consumption expenditures,, -F020,Private fixed investment,F02E,Nonresidential private fixed investment in structures,F02E00,Nonresidential private fixed investment in equipment,F02E00,Nonresidential private fixed investment in equipment,, -F020,Private fixed investment,F02N,Nonresidential private fixed investment in equipment,F02N00,Nonresidential private fixed investment in intellectual property products,F02N00,Nonresidential private fixed investment in intellectual property products,, -F020,Private fixed investment,F02R,Nonresidential private fixed investment in intellectual property products,F02R00,Residential private fixed investment,F02R00,Residential private fixed investment,, -F020,Private fixed investment,F02S,Residential private fixed investment,F02S00,Nonresidential private fixed investment in structures,F02S00,Nonresidential private fixed investment in structures,, -F030,Change in private inventories,F030,Change in private inventories,F03000,Change in private inventories,F03000,Change in private inventories,, -F040,Exports of goods and services,F040,Exports of goods and services,F04000,Exports of goods and services,F04000,Exports of goods and services,, -F050,Imports of goods and services,F050,Imports of goods and services,F05000,Imports of goods and services,F05000,Imports of goods and services,, -F100,Government consumption expenditures and gross investment,F06C,Federal national defense: Consumption expenditures,F06C00,Federal Government defense: Consumption expenditures,F06C00,Federal Government defense: Consumption expenditures,, -F100,Government consumption expenditures and gross investment,F06E,Federal national defense: Gross investment in structures,F06E00,Federal national defense: Gross investment in equipment,F06E00,Federal national defense: Gross investment in equipment,, -F100,Government consumption expenditures and gross investment,F06N,Federal national defense: Gross investment in equipment,F06N00,Federal national defense: Gross investment in intellectual property products,F06N00,Federal national defense: Gross investment in intellectual property products,, -F100,Government consumption expenditures and gross investment,F06S,Federal national defense: Gross investment in intellectual property products,F06S00,Federal national defense: Gross investment in structures,F06S00,Federal national defense: Gross investment in structures,, -F100,Government consumption expenditures and gross investment,F07C,Federal national nondefense: Consumption expenditures,F07C00,Federal Government nondefense: Consumption expenditures,F07C00,Federal Government nondefense: Consumption expenditures,, -F100,Government consumption expenditures and gross investment,F07E,Federal national nondefense: Gross investment in structures,F07E00,Federal nondefense: Gross investment in equipment,F07E00,Federal nondefense: Gross investment in equipment,, -F100,Government consumption expenditures and gross investment,F07N,Federal national nondefense: Gross investment in equipment,F07N00,Federal nondefense: Gross investment in intellectual property products,F07N00,Federal nondefense: Gross investment in intellectual property products,, -F100,Government consumption expenditures and gross investment,F07S,Federal national nondefense: Gross investment in intellectual property products,F07S00,Federal nondefense: Gross investment in structures,F07S00,Federal nondefense: Gross investment in structures,, -F100,Government consumption expenditures and gross investment,F10C,State and local: Consumption expenditures,F10C00,State and local government consumption expenditures,F10C00,State and local government consumption expenditures,, -F100,Government consumption expenditures and gross investment,F10E,State and local: Gross investment in structures,F10E00,State and local: Gross investment in equipment,F10E00,State and local: Gross investment in equipment,, -F100,Government consumption expenditures and gross investment,F10N,State and local: Gross investment in equipment,F10N00,State and local: Gross investment in intellectual property products,F10N00,State and local: Gross investment in intellectual property products,, -F100,Government consumption expenditures and gross investment,F10S,State and local: Gross investment in intellectual property products,F10S00,State and local: Gross investment in structures,F10S00,State and local: Gross investment in structures,, \ No newline at end of file diff --git a/inst/extdata/G_BEAtoUSEEIOtoNAICS_2017.csv b/inst/extdata/G_BEAtoUSEEIOtoNAICS_2017.csv new file mode 100644 index 00000000..fc57f867 --- /dev/null +++ b/inst/extdata/G_BEAtoUSEEIOtoNAICS_2017.csv @@ -0,0 +1,169 @@ +BEA_2017_Sector_Code,BEA_2017_Sector_Name,BEA_2017_Summary_Code,BEA_2017_Summary_Name,BEA_2017_Detail_Code,BEA_2017_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_2017_Code,NAICS_2017_Name +G,Government,GFE,Federal government enterprises,491000,Postal service,491000,Postal service,49,Transportation and Warehousing 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Commercial Sectors " +G,Government,GFE,Federal government enterprises,S00102,Other federal government enterprises,S00102,Other federal government enterprises,927,Space Research and Technology +G,Government,GFE,Federal government enterprises,S00102,Other federal government enterprises,S00102,Other federal government enterprises,9271,Space Research and Technology +G,Government,GFE,Federal government enterprises,S00102,Other federal government enterprises,S00102,Other federal government enterprises,92711,Space Research and Technology +G,Government,GFE,Federal government enterprises,S00102,Other federal government enterprises,S00102,Other federal government enterprises,927110,Space Research and Technology +G,Government,GFGN,Federal general government,S00600,Federal general government (nondefense),S00600,Federal general government (nondefense),928,National Security and International Affairs +G,Government,GFGD,Federal general government,S00500,Federal general government (defense),S00500,Federal general government (defense),928,National Security and International Affairs +G,Government,GFGN,Federal general government,S00600,Federal general government (nondefense),S00600,Federal general government (nondefense),9281,National Security and International Affairs +G,Government,GFGD,Federal general government,S00500,Federal general government (defense),S00500,Federal general government (defense),9281,National Security and International Affairs +G,Government,GFGD,Federal general government,S00500,Federal general government (defense),S00500,Federal general government (defense),92811,National Security +G,Government,GFGD,Federal general government,S00500,Federal general government (defense),S00500,Federal general government (defense),928110,National Security +G,Government,GFGN,Federal general government,S00600,Federal general government (nondefense),S00600,Federal general government (nondefense),92812,International Affairs +G,Government,GFGN,Federal general government,S00600,Federal general government (nondefense),S00600,Federal general government (nondefense),928120,International Affairs +G,Government,GFE,Federal government enterprises,S00101,Federal electric utilities,S00101,Federal electric utilities,S00101,Federal electric utilities +G,Government,GSLE,State and local government enterprises,S00201,State and local government passenger transit,S00201,State and local government passenger transit,S00201,State and local government passenger transit +G,Government,GSLE,State and local government enterprises,S00202,State and local government electric utilities,S00202,State and local government electric utilities,S00202,State and local government electric utilities diff --git a/inst/extdata/HS&ORE_BEAtoUSEEIOtoNAICS_2017.csv b/inst/extdata/HS&ORE_BEAtoUSEEIOtoNAICS_2017.csv new file mode 100644 index 00000000..c8ee2010 --- /dev/null +++ b/inst/extdata/HS&ORE_BEAtoUSEEIOtoNAICS_2017.csv @@ -0,0 +1,31 @@ +BEA_2017_Sector_Code,BEA_2017_Sector_Name,BEA_2017_Summary_Code,BEA_2017_Summary_Name,BEA_2017_Detail_Code,BEA_2017_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_2017_Code,NAICS_2017_Name +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HSO,Owner-occupied housing,531HSO,Owner-occupied housing,53,Real Estate and Rental and Leasing +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HST,Tenant-occupied housing,531HST,Tenant-occupied housing,53,Real Estate and Rental and Leasing +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HSO,Owner-occupied housing,531HSO,Owner-occupied housing,531,Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HST,Tenant-occupied housing,531HST,Tenant-occupied housing,531,Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HSO,Owner-occupied housing,531HSO,Owner-occupied housing,5311,Lessors of Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HST,Tenant-occupied housing,531HST,Tenant-occupied housing,5311,Lessors of Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HSO,Owner-occupied housing,531HSO,Owner-occupied housing,53111,Lessors of Residential Buildings and Dwellings +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HST,Tenant-occupied housing,531HST,Tenant-occupied housing,53111,Lessors of Residential Buildings and Dwellings +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HSO,Owner-occupied housing,531HSO,Owner-occupied housing,531110,Lessors of Residential Buildings and Dwellings +53,REAL ESTATE AND RENTAL AND LEASING,HS,Housing,531HST,Tenant-occupied housing,531HST,Tenant-occupied housing,531110,Lessors of Residential Buildings and Dwellings +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53,Real Estate and Rental and Leasing +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531,Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,5311,Lessors of Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,5312,Offices of Real Estate Agents and Brokers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,5313,Activities Related to Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53112,Lessors of Nonresidential Buildings (except Miniwarehouses) +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53113,Lessors of Miniwarehouses and Self-Storage Units +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53119,Lessors of Other Real Estate Property +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53121,Offices of Real Estate Agents and Brokers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53131,Real Estate Property Managers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53132,Offices of Real Estate Appraisers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,53139,Other Activities Related to Real Estate +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531120,Lessors of Nonresidential Buildings (except Miniwarehouses) +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531130,Lessors of Miniwarehouses and Self-Storage Units +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531190,Lessors of Other Real Estate Property +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531210,Offices of Real Estate Agents and Brokers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531311,Residential Property Managers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531312,Nonresidential Property Managers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531320,Offices of Real Estate Appraisers +53,REAL ESTATE AND RENTAL AND LEASING,ORE,Other real estate,531ORE,Other real estate,531ORE,Other real estate,531390,Other Activities Related to Real Estate diff --git a/inst/extdata/USEEIO_Commodity_Meta.csv b/inst/extdata/USEEIO_Commodity_Meta.csv index 5b846ba3..4f0f7c27 100644 --- a/inst/extdata/USEEIO_Commodity_Meta.csv +++ b/inst/extdata/USEEIO_Commodity_Meta.csv @@ -520,3 +520,5 @@ G,Government,,, 2332B0,,23: Construction,2362: Nonresidential Building Construction,BEA Code & Name is '2332B0:Other nonresidential structures'. This industry comprises construction of other nonresidential structures Related NAICS codes are: 23 333295,,31-33: Manufacturing,3332: Industrial Machinery Manufacturing,"BEA Code & Name is '333295:Semiconductor machinery manufacturing'. This U.S. industry comprises establishments primarily engaged in manufacturing wafer processing equipment, semiconductor assembly and packaging equipment, and other semiconductor making machinery." 333315,,31-33: Manufacturing,3333: Commercial and Service Industry Machinery Manufacturing,"BEA Code & Name is '333315:Photographic and photocopying equipment manufacturing'. This U.S. industry comprises establishments primarily engaged in manufacturing photographic and photocopying equipment, such as cameras (except television, video and digital) projectors, film developing equipment, photocopying equipment, and microfilm equipment." +333914,Pumps and pumping equipment,31-33: Manufacturing,3339: Other General Purpose Machinery Manufacturing,"BEA Code & Name is '333914:Measuring, dispensing, and other pumping equipment manufacturing'. This U.S. industry comprises establishments primarily engaged in (1) manufacturing measuring and dispensing pumps, such as gasoline pumps and lubricating oil measuring and dispensing pumps and/or (2) manufacturing general purpose pumps and pumping equipment (except fluid power pumps and motors), such as reciprocating pumps, turbine pumps, centrifugal pumps, rotary pumps, diaphragm pumps, domestic water system pumps, oil well and oil field pumps, and sump pumps." +335220,Major home appliances,31-33: Manufacturing,3352: Household Appliance Manufacturing,"BEA Code & Name is '335220:Major household appliance manufacturing'. This industry comprises establishments primarily engaged in manufacturing household-type cooking appliances, household-type laundry equipment, household-type refrigerators, upright and chest freezers, and other electrical and nonelectrical major household-type appliances, such as dishwashers, water heaters, and garbage disposal units." diff --git a/inst/extdata/V_BEAtoUSEEIOtoNAICS_2007.csv b/inst/extdata/V_BEAtoUSEEIOtoNAICS.csv similarity index 65% rename from inst/extdata/V_BEAtoUSEEIOtoNAICS_2007.csv rename to inst/extdata/V_BEAtoUSEEIOtoNAICS.csv index 2fad5d38..5c90c6d3 100644 --- a/inst/extdata/V_BEAtoUSEEIOtoNAICS_2007.csv +++ b/inst/extdata/V_BEAtoUSEEIOtoNAICS.csv @@ -1,4 +1,4 @@ -BEA_2007_Sector_Code,BEA_2007_Sector_Name,BEA_2007_Summary_Code,BEA_2007_Summary_Name,BEA_2007_Detail_Code,BEA_2007_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_2007_Code,NAICS_2007_Name -V001,Compensation of employees,V001,Compensation of employees,V00100,Compensation of employees,,,, -V002,"Taxes on production and imports, less subsidies",V002,"Taxes on production and imports, less subsidies",V00200,"Taxes on production and imports, less subsidies",,,, +BEA_Sector_Code,BEA_Sector_Name,BEA_Summary_Code,BEA_Summary_Name,BEA_Detail_Code,BEA_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_Code,NAICS_Name +V001,Compensation of employees,V001,Compensation of employees,V00100,Compensation of employees,,,, +V002,"Taxes on production and imports, less subsidies",V002,"Taxes on production and imports, less subsidies",V00200,"Taxes on production and imports, less subsidies",,,, V003,Gross operating surplus,V003,Gross operating surplus,V00300,Gross operating surplus,,,, diff --git a/inst/extdata/V_BEAtoUSEEIOtoNAICS_2012.csv b/inst/extdata/V_BEAtoUSEEIOtoNAICS_2012.csv deleted file mode 100644 index cf148452..00000000 --- a/inst/extdata/V_BEAtoUSEEIOtoNAICS_2012.csv +++ /dev/null @@ -1,4 +0,0 @@ -BEA_2012_Sector_Code,BEA_2012_Sector_Name,BEA_2012_Summary_Code,BEA_2012_Summary_Name,BEA_2012_Detail_Code,BEA_2012_Detail_Name,USEEIO_Code,USEEIO_Industry,NAICS_2012_Code,NAICS_2012_Name -V001,Compensation of employees,V001,Compensation of employees,V00100,Compensation of employees,,,, -V002,"Taxes on production and imports, less subsidies",V002,"Taxes on production and imports, less subsidies",V00200,"Taxes on production and imports, less subsidies",,,, -V003,Gross operating surplus,V003,Gross operating surplus,V00300,Gross operating surplus,,,, diff --git a/inst/extdata/metadata/Detail_CPI_IO_metadata.json b/inst/extdata/metadata/Detail_CPI_IO_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_CPI_IO_metadata.json rename to inst/extdata/metadata/Detail_CPI_IO_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_CPI_IO_17sch_metadata.json b/inst/extdata/metadata/Detail_CPI_IO_17sch_metadata.json new file mode 100644 index 00000000..1f6832ad --- /dev/null +++ b/inst/extdata/metadata/Detail_CPI_IO_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_CPI_IO_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-19"], + "data_meta": { + "data_year": ["2017", "2018", "2019", "2020", "2021", "2022"], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip"], + "date_last_modified": ["2023-11-20"], + "date_accessed": ["2024-02-10"] + } +} diff --git a/inst/extdata/metadata/Sector_Use_2017_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Detail_CommodityCodeName_2017_metadata.json similarity index 55% rename from inst/extdata/metadata/Sector_Use_2017_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Detail_CommodityCodeName_2017_metadata.json index 517f6a31..8e0340b8 100644 --- a/inst/extdata/metadata/Sector_Use_2017_PRO_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Detail_CommodityCodeName_2017_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2017_PRO_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Detail_CommodityCodeName_2017"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Sector_Use_2017_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Detail_FinalDemandCodeName_2017_metadata.json similarity index 55% rename from inst/extdata/metadata/Sector_Use_2017_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Detail_FinalDemandCodeName_2017_metadata.json index de92e200..97bcf697 100644 --- a/inst/extdata/metadata/Sector_Use_2017_PRO_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Detail_FinalDemandCodeName_2017_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2017_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Detail_FinalDemandCodeName_2017"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Detail_GrossOutput_IO_metadata.json b/inst/extdata/metadata/Detail_GrossOutput_IO_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_GrossOutput_IO_metadata.json rename to inst/extdata/metadata/Detail_GrossOutput_IO_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_GrossOutput_IO_17sch_metadata.json b/inst/extdata/metadata/Detail_GrossOutput_IO_17sch_metadata.json new file mode 100644 index 00000000..90edb8a6 --- /dev/null +++ b/inst/extdata/metadata/Detail_GrossOutput_IO_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_GrossOutput_IO_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-19"], + "data_meta": { + "data_year": ["2017", "2018", "2019", "2020", "2021", "2022"], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip"], + "date_last_modified": ["2023-11-20"], + "date_accessed": ["2024-02-10"] + } +} diff --git a/inst/extdata/metadata/Detail_Import_2012_BeforeRedef_metadata.json b/inst/extdata/metadata/Detail_Import_2012_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Import_2012_BeforeRedef_metadata.json rename to inst/extdata/metadata/Detail_Import_2012_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Import_2017_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Import_2017_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..7a8415f3 --- /dev/null +++ b/inst/extdata/metadata/Detail_Import_2017_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Import_2017_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_DET_2017.xlsx"], + "date_last_modified": ["unknown"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Sector_Make_2017_AfterRedef_metadata.json b/inst/extdata/metadata/Detail_IndustryCodeName_2017_metadata.json similarity index 55% rename from inst/extdata/metadata/Sector_Make_2017_AfterRedef_metadata.json rename to inst/extdata/metadata/Detail_IndustryCodeName_2017_metadata.json index 5e350917..f9ac7732 100644 --- a/inst/extdata/metadata/Sector_Make_2017_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Detail_IndustryCodeName_2017_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2017_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Detail_IndustryCodeName_2017"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Detail_Make_2012_AfterRedef_metadata.json b/inst/extdata/metadata/Detail_Make_2012_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Make_2012_AfterRedef_metadata.json rename to inst/extdata/metadata/Detail_Make_2012_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Make_2012_BeforeRedef_metadata.json b/inst/extdata/metadata/Detail_Make_2012_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Make_2012_BeforeRedef_metadata.json rename to inst/extdata/metadata/Detail_Make_2012_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Make_2017_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Make_2017_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..2786654f --- /dev/null +++ b/inst/extdata/metadata/Detail_Make_2017_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Make_2017_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-13"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Detail_Make_2017_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Make_2017_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..cbfcaf2e --- /dev/null +++ b/inst/extdata/metadata/Detail_Make_2017_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Make_2017_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2024-01-25"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Detail_Margins_2012_BeforeRedef_metadata.json b/inst/extdata/metadata/Detail_Margins_2012_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Margins_2012_BeforeRedef_metadata.json rename to inst/extdata/metadata/Detail_Margins_2012_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Margins_2017_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Margins_2017_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..37ed9967 --- /dev/null +++ b/inst/extdata/metadata/Detail_Margins_2017_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Margins_2017_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/xls/underlying-estimates/Margins_Before_Redefinitions_2017_DET.xlsx"], + "date_last_modified": ["2024-02-01"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Detail_Supply_2012_metadata.json b/inst/extdata/metadata/Detail_Supply_2012_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Supply_2012_metadata.json rename to inst/extdata/metadata/Detail_Supply_2012_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2017_metadata.json b/inst/extdata/metadata/Detail_Supply_2017_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Summary_Supply_2017_metadata.json rename to inst/extdata/metadata/Detail_Supply_2017_17sch_metadata.json index 64c62856..53b13e1b 100644 --- a/inst/extdata/metadata/Summary_Supply_2017_metadata.json +++ b/inst/extdata/metadata/Detail_Supply_2017_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Summary_Supply_2017"], - "tool_version": ["1.1.1"], + "name_data": ["Detail_Supply_2017_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": ["2024-02-01"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Detail_Use_2012_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Detail_Use_2012_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Use_2012_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Detail_Use_2012_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Use_2012_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Detail_Use_2012_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Use_2012_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Detail_Use_2012_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Use_2012_PUR_AfterRedef_metadata.json b/inst/extdata/metadata/Detail_Use_2012_PUR_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Use_2012_PUR_AfterRedef_metadata.json rename to inst/extdata/metadata/Detail_Use_2012_PUR_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Use_2012_PUR_BeforeRedef_metadata.json b/inst/extdata/metadata/Detail_Use_2012_PUR_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Detail_Use_2012_PUR_BeforeRedef_metadata.json rename to inst/extdata/metadata/Detail_Use_2012_PUR_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Detail_Use_2017_PRO_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Use_2017_PRO_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..7b70d6e2 --- /dev/null +++ b/inst/extdata/metadata/Detail_Use_2017_PRO_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Use_2017_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2024-01-25"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Detail_Use_2017_PRO_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Use_2017_PRO_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..474c0448 --- /dev/null +++ b/inst/extdata/metadata/Detail_Use_2017_PRO_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Use_2017_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2024-01-25"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Detail_Use_2017_PUR_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Use_2017_PUR_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..dc6307ea --- /dev/null +++ b/inst/extdata/metadata/Detail_Use_2017_PUR_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Use_2017_PUR_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2024-01-25"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Detail_Use_2017_PUR_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Detail_Use_2017_PUR_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..ede570ad --- /dev/null +++ b/inst/extdata/metadata/Detail_Use_2017_PUR_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Detail_Use_2017_PUR_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": 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b/inst/extdata/metadata/Detail_Use_SUT_2017_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Summary_Use_SUT_2017"], - "tool_version": ["1.1.1"], + "name_data": ["Detail_Use_SUT_2017_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": ["2024-02-01"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Detail_ValueAddedCodeName_2017_metadata.json b/inst/extdata/metadata/Detail_ValueAddedCodeName_2017_metadata.json new file mode 100644 index 00000000..aa593e8d --- /dev/null +++ b/inst/extdata/metadata/Detail_ValueAddedCodeName_2017_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": 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["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-19"], + "data_meta": { + "data_year": ["2017", "2018", "2019", "2020", "2021", "2022"], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip"], + "date_last_modified": ["2023-11-20"], + "date_accessed": ["2024-02-10"] + } +} diff --git a/inst/extdata/metadata/Sector_CommodityCodeName_2017_metadata.json b/inst/extdata/metadata/Sector_CommodityCodeName_2017_metadata.json new file mode 100644 index 00000000..32ef834a --- /dev/null +++ b/inst/extdata/metadata/Sector_CommodityCodeName_2017_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Sector_CommodityCodeName_2017"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Sector_FinalDemandCodeName_2017_metadata.json b/inst/extdata/metadata/Sector_FinalDemandCodeName_2017_metadata.json new file mode 100644 index 00000000..cc1ad65e --- /dev/null +++ b/inst/extdata/metadata/Sector_FinalDemandCodeName_2017_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Sector_FinalDemandCodeName_2017"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Sector_GrossOutput_IO_metadata.json b/inst/extdata/metadata/Sector_GrossOutput_IO_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Sector_GrossOutput_IO_metadata.json rename to inst/extdata/metadata/Sector_GrossOutput_IO_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_GrossOutput_IO_17sch_metadata.json b/inst/extdata/metadata/Sector_GrossOutput_IO_17sch_metadata.json new file mode 100644 index 00000000..315f54f1 --- /dev/null +++ b/inst/extdata/metadata/Sector_GrossOutput_IO_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Sector_GrossOutput_IO_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-19"], + "data_meta": { + "data_year": ["2017", "2018", "2019", "2020", "2021", "2022"], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip"], + "date_last_modified": ["2023-11-20"], + "date_accessed": ["2024-02-10"] + } +} diff --git a/inst/extdata/metadata/Sector_Make_2017_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_IndustryCodeName_2017_metadata.json similarity index 55% rename from inst/extdata/metadata/Sector_Make_2017_BeforeRedef_metadata.json rename to inst/extdata/metadata/Sector_IndustryCodeName_2017_metadata.json index 609cdf3f..e7a8a08c 100644 --- a/inst/extdata/metadata/Sector_Make_2017_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Sector_IndustryCodeName_2017_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2017_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Sector_IndustryCodeName_2017"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Sector_Make_2010_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Make_2010_AfterRedef_metadata.json deleted file mode 100644 index 44bd47bd..00000000 --- a/inst/extdata/metadata/Sector_Make_2010_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Make_2010_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2010], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Make_2010_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Make_2010_BeforeRedef_metadata.json deleted file mode 100644 index 1f3e3da2..00000000 --- a/inst/extdata/metadata/Sector_Make_2010_BeforeRedef_metadata.json +++ 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b/inst/extdata/metadata/Sector_Make_2012_AfterRedef_metadata.json deleted file mode 100644 index ce9ec741..00000000 --- a/inst/extdata/metadata/Sector_Make_2012_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Make_2012_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2012], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Make_2012_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Make_2012_BeforeRedef_metadata.json deleted file mode 100644 index 69ea27fa..00000000 --- a/inst/extdata/metadata/Sector_Make_2012_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": 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b/inst/extdata/metadata/Sector_Make_2014_AfterRedef_metadata.json deleted file mode 100644 index e5d6ee45..00000000 --- a/inst/extdata/metadata/Sector_Make_2014_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Make_2014_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2014], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Make_2014_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Make_2014_BeforeRedef_metadata.json deleted file mode 100644 index 2e396ea3..00000000 --- a/inst/extdata/metadata/Sector_Make_2014_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": 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b/inst/extdata/metadata/Sector_Make_2016_AfterRedef_metadata.json deleted file mode 100644 index 0618efba..00000000 --- a/inst/extdata/metadata/Sector_Make_2016_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Make_2016_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2016], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Make_2016_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Make_2016_BeforeRedef_metadata.json deleted file mode 100644 index a4ddbb96..00000000 --- a/inst/extdata/metadata/Sector_Make_2016_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": 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["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Supply_2015_metadata.json b/inst/extdata/metadata/Sector_Supply_2015_metadata.json deleted file mode 100644 index 60b8ea96..00000000 --- a/inst/extdata/metadata/Sector_Supply_2015_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Supply_2015"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2015], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Supply_2016_metadata.json b/inst/extdata/metadata/Sector_Supply_2016_metadata.json deleted file mode 100644 index 7db8ee70..00000000 --- a/inst/extdata/metadata/Sector_Supply_2016_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Supply_2016"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2016], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2010_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2010_PRO_AfterRedef_metadata.json deleted file mode 100644 index cf8c93c3..00000000 --- a/inst/extdata/metadata/Sector_Use_2010_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2010_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2010], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2010_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2010_PRO_BeforeRedef_metadata.json deleted file mode 100644 index c308c7d0..00000000 --- a/inst/extdata/metadata/Sector_Use_2010_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2010_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2010], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2011_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2011_PRO_AfterRedef_metadata.json deleted file mode 100644 index 828cbe84..00000000 --- a/inst/extdata/metadata/Sector_Use_2011_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2011_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2011], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2011_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2011_PRO_BeforeRedef_metadata.json deleted file mode 100644 index ed565043..00000000 --- a/inst/extdata/metadata/Sector_Use_2011_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2011_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2011], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2012_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2012_PRO_AfterRedef_metadata.json deleted file mode 100644 index 9e522cf3..00000000 --- a/inst/extdata/metadata/Sector_Use_2012_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2012_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2012], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2012_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2012_PRO_BeforeRedef_metadata.json deleted file mode 100644 index 77c7557d..00000000 --- a/inst/extdata/metadata/Sector_Use_2012_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2012_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2012], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2012_PUR_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2012_PUR_BeforeRedef_metadata.json deleted file mode 100644 index 37a0dbd3..00000000 --- a/inst/extdata/metadata/Sector_Use_2012_PUR_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2012_PUR_BeforeRedef"], - "tool_version": ["1.1.0"], - "ext": ["json"], - "date_created": ["2022-07-27"], - "data_meta": { - "data_year": [2012], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2021-09-29"], - "date_accessed": ["2022-07-27"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2013_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2013_PRO_AfterRedef_metadata.json deleted file mode 100644 index e88cfa21..00000000 --- a/inst/extdata/metadata/Sector_Use_2013_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2013_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2013], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2013_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2013_PRO_BeforeRedef_metadata.json deleted file mode 100644 index a12b8502..00000000 --- a/inst/extdata/metadata/Sector_Use_2013_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2013_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2013], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2014_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2014_PRO_AfterRedef_metadata.json deleted file mode 100644 index d877a824..00000000 --- a/inst/extdata/metadata/Sector_Use_2014_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2014_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2014], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2014_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2014_PRO_BeforeRedef_metadata.json deleted file mode 100644 index e216e74b..00000000 --- a/inst/extdata/metadata/Sector_Use_2014_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2014_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2014], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2015_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2015_PRO_AfterRedef_metadata.json deleted file mode 100644 index c1ae68c1..00000000 --- a/inst/extdata/metadata/Sector_Use_2015_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2015_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2015], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2015_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2015_PRO_BeforeRedef_metadata.json deleted file mode 100644 index 00756aff..00000000 --- a/inst/extdata/metadata/Sector_Use_2015_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2015_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2015], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2016_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2016_PRO_AfterRedef_metadata.json deleted file mode 100644 index dd0bbcb8..00000000 --- a/inst/extdata/metadata/Sector_Use_2016_PRO_AfterRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2016_PRO_AfterRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2016], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_2016_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Sector_Use_2016_PRO_BeforeRedef_metadata.json deleted file mode 100644 index 04798319..00000000 --- a/inst/extdata/metadata/Sector_Use_2016_PRO_BeforeRedef_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_2016_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2023-04-11"], - "data_meta": { - "data_year": [2016], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2010_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2010_metadata.json deleted file mode 100644 index ce2e8614..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2010_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2010"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2010], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2011_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2011_metadata.json deleted file mode 100644 index d758b3c2..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2011_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2011"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2011], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2012_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2012_metadata.json deleted file mode 100644 index 02a958c4..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2012_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2012"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2012], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2013_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2013_metadata.json deleted file mode 100644 index c7451ae6..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2013_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2013"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2013], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2014_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2014_metadata.json deleted file mode 100644 index 1730813f..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2014_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2014"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2014], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2015_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2015_metadata.json deleted file mode 100644 index f36e1e90..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2015_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2015"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2015], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2016_metadata.json b/inst/extdata/metadata/Sector_Use_SUT_2016_metadata.json deleted file mode 100644 index 19c41948..00000000 --- a/inst/extdata/metadata/Sector_Use_SUT_2016_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2016"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2016], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_ValueAddedCodeName_2017_metadata.json b/inst/extdata/metadata/Sector_ValueAddedCodeName_2017_metadata.json new file mode 100644 index 00000000..0ae070a7 --- /dev/null +++ b/inst/extdata/metadata/Sector_ValueAddedCodeName_2017_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Sector_ValueAddedCodeName_2017"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Sector_ValueAdded_IO_metadata.json b/inst/extdata/metadata/Sector_ValueAdded_IO_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Sector_ValueAdded_IO_metadata.json rename to inst/extdata/metadata/Sector_ValueAdded_IO_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_ValueAdded_IO_17sch_metadata.json b/inst/extdata/metadata/Sector_ValueAdded_IO_17sch_metadata.json new file mode 100644 index 00000000..8589cc77 --- /dev/null +++ b/inst/extdata/metadata/Sector_ValueAdded_IO_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Sector_ValueAdded_IO_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": ["2017", "2018", "2019", "2020", "2021", "2022"], + "author": ["US 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similarity index 100% rename from inst/extdata/metadata/Summary_Import_2016_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Import_2016_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Import_2017_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Import_2017_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Import_2017_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Import_2017_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Import_2017_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Import_2017_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..335b8069 --- /dev/null +++ b/inst/extdata/metadata/Summary_Import_2017_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Import_2017_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": 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a/inst/extdata/metadata/Summary_Make_2010_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2010_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2010_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2010_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2010_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2010_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2010_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2010_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2011_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2011_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2011_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2011_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2011_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2011_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2011_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2011_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2012_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2012_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2012_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2012_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2012_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2012_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2012_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2012_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2013_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2013_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2013_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2013_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2013_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2013_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2013_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2013_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2014_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2014_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2014_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2014_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2014_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2014_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2014_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2014_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2015_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2015_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2015_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2015_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2015_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2015_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2015_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2015_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2016_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2016_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2016_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2016_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2016_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2016_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2016_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2016_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2017_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2017_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2017_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2017_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2017_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Make_2017_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..7490ddcc --- /dev/null +++ b/inst/extdata/metadata/Summary_Make_2017_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Make_2017_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Make_2017_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2017_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2017_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2017_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Make_2017_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Make_2017_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..90510b82 --- /dev/null +++ b/inst/extdata/metadata/Summary_Make_2017_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Make_2017_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Make_2018_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2018_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2018_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2018_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2018_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2018_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2018_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2018_AfterRedef_17sch_metadata.json index ef29d20d..9d822263 100644 --- a/inst/extdata/metadata/Sector_Make_2018_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2018_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2018_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2018_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2018], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2018_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2018_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2018_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2018_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2018_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2018_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2018_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2018_BeforeRedef_17sch_metadata.json index 0646d157..0fb43395 100644 --- a/inst/extdata/metadata/Sector_Make_2018_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2018_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2018_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2018_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2018], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2019_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2019_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2019_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2019_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2019_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2019_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2019_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2019_AfterRedef_17sch_metadata.json index 303da7ea..b932f3a5 100644 --- a/inst/extdata/metadata/Sector_Make_2019_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2019_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2019_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2019_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2019], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2019_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2019_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2019_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2019_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2019_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2019_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2019_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2019_BeforeRedef_17sch_metadata.json index ec0a5d31..ca6af76f 100644 --- a/inst/extdata/metadata/Sector_Make_2019_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2019_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2019_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2019_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2019], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2020_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2020_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2020_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2020_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2020_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2020_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2020_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2020_AfterRedef_17sch_metadata.json index 1ccab736..580d01f5 100644 --- a/inst/extdata/metadata/Sector_Make_2020_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2020_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2020_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2020_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2020], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2020_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2020_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2020_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2020_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2020_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2020_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2020_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2020_BeforeRedef_17sch_metadata.json index c9b9685f..e045356d 100644 --- a/inst/extdata/metadata/Sector_Make_2020_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2020_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2020_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2020_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2020], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2021_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2021_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2021_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2021_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2021_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2021_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2021_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2021_AfterRedef_17sch_metadata.json index 2d9ee9a5..2f9d0797 100644 --- a/inst/extdata/metadata/Sector_Make_2021_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2021_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2021_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2021_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2021], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2021_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2021_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Make_2021_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2021_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Make_2021_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Make_2021_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Make_2021_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Make_2021_BeforeRedef_17sch_metadata.json index 15249c80..6cb5e574 100644 --- a/inst/extdata/metadata/Sector_Make_2021_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Make_2021_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Make_2021_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Make_2021_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2021], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Make_2022_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Make_2022_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..415cae77 --- /dev/null +++ b/inst/extdata/metadata/Summary_Make_2022_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Make_2022_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2022], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Make_2022_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Make_2022_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..fc23b333 --- /dev/null +++ b/inst/extdata/metadata/Summary_Make_2022_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Make_2022_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2022], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Supply_2010_metadata.json b/inst/extdata/metadata/Summary_Supply_2010_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2010_metadata.json rename to inst/extdata/metadata/Summary_Supply_2010_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2011_metadata.json b/inst/extdata/metadata/Summary_Supply_2011_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2011_metadata.json rename to inst/extdata/metadata/Summary_Supply_2011_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2012_metadata.json b/inst/extdata/metadata/Summary_Supply_2012_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2012_metadata.json rename to inst/extdata/metadata/Summary_Supply_2012_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2013_metadata.json b/inst/extdata/metadata/Summary_Supply_2013_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2013_metadata.json rename to inst/extdata/metadata/Summary_Supply_2013_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2014_metadata.json b/inst/extdata/metadata/Summary_Supply_2014_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2014_metadata.json rename to inst/extdata/metadata/Summary_Supply_2014_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2015_metadata.json b/inst/extdata/metadata/Summary_Supply_2015_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2015_metadata.json rename to inst/extdata/metadata/Summary_Supply_2015_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Supply_2016_metadata.json b/inst/extdata/metadata/Summary_Supply_2016_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Supply_2016_metadata.json rename to inst/extdata/metadata/Summary_Supply_2016_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Supply_2017_metadata.json b/inst/extdata/metadata/Summary_Supply_2017_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Supply_2017_metadata.json rename to inst/extdata/metadata/Summary_Supply_2017_17sch_metadata.json index dae1aa8e..f5181b86 100644 --- a/inst/extdata/metadata/Sector_Supply_2017_metadata.json +++ b/inst/extdata/metadata/Summary_Supply_2017_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2017"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Supply_2017_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Sector_Supply_2018_metadata.json b/inst/extdata/metadata/Summary_Supply_2018_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Supply_2018_metadata.json rename to inst/extdata/metadata/Summary_Supply_2018_17sch_metadata.json index aec067a9..33f0e64d 100644 --- a/inst/extdata/metadata/Sector_Supply_2018_metadata.json +++ b/inst/extdata/metadata/Summary_Supply_2018_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2018"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Supply_2018_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2018], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Supply_2018_metadata.json b/inst/extdata/metadata/Summary_Supply_2018_metadata.json deleted file mode 100644 index 970d70db..00000000 --- a/inst/extdata/metadata/Summary_Supply_2018_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Summary_Supply_2018"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2018], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Supply_2019_metadata.json b/inst/extdata/metadata/Summary_Supply_2019_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Supply_2019_metadata.json rename to inst/extdata/metadata/Summary_Supply_2019_17sch_metadata.json index 4eeb62fb..1341e0c4 100644 --- a/inst/extdata/metadata/Sector_Supply_2019_metadata.json +++ b/inst/extdata/metadata/Summary_Supply_2019_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2019"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Supply_2019_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2019], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Supply_2019_metadata.json b/inst/extdata/metadata/Summary_Supply_2019_metadata.json deleted file mode 100644 index 382428c1..00000000 --- a/inst/extdata/metadata/Summary_Supply_2019_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Summary_Supply_2019"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2019], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Supply_2020_metadata.json b/inst/extdata/metadata/Summary_Supply_2020_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Supply_2020_metadata.json rename to inst/extdata/metadata/Summary_Supply_2020_17sch_metadata.json index 8df73628..02d4c122 100644 --- a/inst/extdata/metadata/Sector_Supply_2020_metadata.json +++ b/inst/extdata/metadata/Summary_Supply_2020_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2020"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Supply_2020_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2020], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Supply_2020_metadata.json b/inst/extdata/metadata/Summary_Supply_2020_metadata.json deleted file mode 100644 index 1a81f41a..00000000 --- a/inst/extdata/metadata/Summary_Supply_2020_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Summary_Supply_2020"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2020], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Supply_2013_metadata.json b/inst/extdata/metadata/Summary_Supply_2021_17sch_metadata.json similarity index 50% rename from inst/extdata/metadata/Sector_Supply_2013_metadata.json rename to inst/extdata/metadata/Summary_Supply_2021_17sch_metadata.json index 85f4b59e..dca11151 100644 --- a/inst/extdata/metadata/Sector_Supply_2013_metadata.json +++ b/inst/extdata/metadata/Summary_Supply_2021_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2013"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Supply_2021_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { - "data_year": [2013], + "data_year": [2021], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Sector_Supply_2010_metadata.json b/inst/extdata/metadata/Summary_Supply_2022_17sch_metadata.json similarity index 50% rename from inst/extdata/metadata/Sector_Supply_2010_metadata.json rename to inst/extdata/metadata/Summary_Supply_2022_17sch_metadata.json index e351b745..41356e9e 100644 --- a/inst/extdata/metadata/Sector_Supply_2010_metadata.json +++ b/inst/extdata/metadata/Summary_Supply_2022_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2010"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Supply_2022_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { - "data_year": [2010], + "data_year": [2022], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2010_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2010_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2010_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2010_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2010_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2010_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2010_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2010_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2011_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2011_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2011_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2011_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2011_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2011_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2011_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2011_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2012_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2012_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2012_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2012_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2012_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2012_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2012_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2012_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2012_PUR_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2012_PUR_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2012_PUR_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2012_PUR_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2013_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2013_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2013_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2013_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2013_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2013_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2013_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2013_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2014_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2014_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2014_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2014_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2014_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2014_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2014_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2014_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2015_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2015_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2015_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2015_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2015_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2015_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2015_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2015_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2016_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2016_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2016_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2016_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2016_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2016_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2016_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2016_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..6c62be00 --- /dev/null +++ b/inst/extdata/metadata/Summary_Use_2017_PRO_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Use_2017_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..e5972475 --- /dev/null +++ b/inst/extdata/metadata/Summary_Use_2017_PRO_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Use_2017_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Use_2017_PUR_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Use_2017_PUR_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..9510caf6 --- /dev/null +++ b/inst/extdata/metadata/Summary_Use_2017_PUR_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Use_2017_PUR_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2024-01-19"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2018_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2018_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_17sch_metadata.json index 7ab56924..a991340e 100644 --- a/inst/extdata/metadata/Sector_Use_2018_PRO_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2018_PRO_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2018_PRO_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2018_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2018], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2018_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2018_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_17sch_metadata.json index 42d74ddb..3d564333 100644 --- a/inst/extdata/metadata/Sector_Use_2018_PRO_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2018_PRO_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2018_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2018_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2018], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2019_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2019_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_17sch_metadata.json index 71eb9a39..cbc5c270 100644 --- a/inst/extdata/metadata/Sector_Use_2019_PRO_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2019_PRO_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2019_PRO_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2019_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2019], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2019_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2019_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_17sch_metadata.json index 33325b5d..e648be81 100644 --- a/inst/extdata/metadata/Sector_Use_2019_PRO_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2019_PRO_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2019_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2019_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2019], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2020_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2020_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_17sch_metadata.json index 4d68a2f3..67c323f1 100644 --- a/inst/extdata/metadata/Sector_Use_2020_PRO_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2020_PRO_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2020_PRO_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2020_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2020], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2020_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2020_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_17sch_metadata.json index 6b805714..dbd181fe 100644 --- a/inst/extdata/metadata/Sector_Use_2020_PRO_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2020_PRO_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2020_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2020_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2020], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2021_PRO_AfterRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2021_PRO_AfterRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_17sch_metadata.json index 2d5a4e7a..fdaa9169 100644 --- a/inst/extdata/metadata/Sector_Use_2021_PRO_AfterRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2021_PRO_AfterRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2021_PRO_AfterRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2021_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2021], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_2021_PRO_BeforeRedef_metadata.json b/inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_17sch_metadata.json similarity index 54% rename from inst/extdata/metadata/Sector_Use_2021_PRO_BeforeRedef_metadata.json rename to inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_17sch_metadata.json index 30847f7b..767eae61 100644 --- a/inst/extdata/metadata/Sector_Use_2021_PRO_BeforeRedef_metadata.json +++ b/inst/extdata/metadata/Summary_Use_2021_PRO_BeforeRedef_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_2021_PRO_BeforeRedef"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_2021_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2023-04-11"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2021], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], - "date_last_modified": ["2022-09-27"], - "date_accessed": ["2023-04-11"] + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_2022_PRO_AfterRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Use_2022_PRO_AfterRedef_17sch_metadata.json new file mode 100644 index 00000000..d0703d4e --- /dev/null +++ b/inst/extdata/metadata/Summary_Use_2022_PRO_AfterRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Use_2022_PRO_AfterRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2022], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Use_2022_PRO_BeforeRedef_17sch_metadata.json b/inst/extdata/metadata/Summary_Use_2022_PRO_BeforeRedef_17sch_metadata.json new file mode 100644 index 00000000..ccbe6627 --- /dev/null +++ b/inst/extdata/metadata/Summary_Use_2022_PRO_BeforeRedef_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_Use_2022_PRO_BeforeRedef_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2022], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_Use_SUT_2010_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2010_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2010_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2010_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_SUT_2011_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2011_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2011_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2011_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_SUT_2012_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2012_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2012_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2012_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_SUT_2013_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2013_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2013_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2013_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_SUT_2014_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2014_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2014_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2014_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_SUT_2015_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2015_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2015_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2015_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_Use_SUT_2016_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2016_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_Use_SUT_2016_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2016_12sch_metadata.json diff --git a/inst/extdata/metadata/Sector_Use_SUT_2017_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2017_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Use_SUT_2017_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2017_17sch_metadata.json index 2fa9109b..f0b44777 100644 --- a/inst/extdata/metadata/Sector_Use_SUT_2017_metadata.json +++ b/inst/extdata/metadata/Summary_Use_SUT_2017_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2017"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_SUT_2017_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2017], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Sector_Use_SUT_2018_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2018_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Use_SUT_2018_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2018_17sch_metadata.json index e167e3fb..65ca3526 100644 --- a/inst/extdata/metadata/Sector_Use_SUT_2018_metadata.json +++ b/inst/extdata/metadata/Summary_Use_SUT_2018_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2018"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_SUT_2018_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2018], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_SUT_2018_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2018_metadata.json deleted file mode 100644 index e946b283..00000000 --- a/inst/extdata/metadata/Summary_Use_SUT_2018_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Summary_Use_SUT_2018"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2018], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2019_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2019_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Use_SUT_2019_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2019_17sch_metadata.json index 111a7789..9aefb074 100644 --- a/inst/extdata/metadata/Sector_Use_SUT_2019_metadata.json +++ b/inst/extdata/metadata/Summary_Use_SUT_2019_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2019"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_SUT_2019_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2019], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_SUT_2019_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2019_metadata.json deleted file mode 100644 index 4a38c853..00000000 --- a/inst/extdata/metadata/Summary_Use_SUT_2019_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Summary_Use_SUT_2019"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2019], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Use_SUT_2020_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2020_17sch_metadata.json similarity index 56% rename from inst/extdata/metadata/Sector_Use_SUT_2020_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2020_17sch_metadata.json index dccfb258..39d7aada 100644 --- a/inst/extdata/metadata/Sector_Use_SUT_2020_metadata.json +++ b/inst/extdata/metadata/Summary_Use_SUT_2020_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Use_SUT_2020"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_SUT_2020_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { "data_year": [2020], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_Use_SUT_2020_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2020_metadata.json deleted file mode 100644 index e825330a..00000000 --- a/inst/extdata/metadata/Summary_Use_SUT_2020_metadata.json +++ /dev/null @@ -1,14 +0,0 @@ -{ - "tool": ["useeior"], - "name_data": ["Summary_Use_SUT_2020"], - "tool_version": ["1.1.1"], - "ext": ["json"], - "date_created": ["2022-08-23"], - "data_meta": { - "data_year": [2020], - "author": ["US Bureau of Economic Analysis"], - "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] - } -} diff --git a/inst/extdata/metadata/Sector_Supply_2012_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2021_17sch_metadata.json similarity index 50% rename from inst/extdata/metadata/Sector_Supply_2012_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2021_17sch_metadata.json index 48cd4919..a3ee1af1 100644 --- a/inst/extdata/metadata/Sector_Supply_2012_metadata.json +++ b/inst/extdata/metadata/Summary_Use_SUT_2021_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2012"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_SUT_2021_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { - "data_year": [2012], + "data_year": [2021], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Sector_Supply_2011_metadata.json b/inst/extdata/metadata/Summary_Use_SUT_2022_17sch_metadata.json similarity index 50% rename from inst/extdata/metadata/Sector_Supply_2011_metadata.json rename to inst/extdata/metadata/Summary_Use_SUT_2022_17sch_metadata.json index dc7fcc27..f58da592 100644 --- a/inst/extdata/metadata/Sector_Supply_2011_metadata.json +++ b/inst/extdata/metadata/Summary_Use_SUT_2022_17sch_metadata.json @@ -1,14 +1,14 @@ { "tool": ["useeior"], - "name_data": ["Sector_Supply_2011"], - "tool_version": ["1.1.1"], + "name_data": ["Summary_Use_SUT_2022_17sch"], + "tool_version": ["1.4.0"], "ext": ["json"], - "date_created": ["2022-08-23"], + "date_created": ["2024-02-17"], "data_meta": { - "data_year": [2011], + "data_year": [2022], "author": ["US Bureau of Economic Analysis"], "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesSUP.zip"], - "date_last_modified": ["2022-02-08"], - "date_accessed": ["2022-08-23"] + "date_last_modified": {}, + "date_accessed": ["2024-02-17"] } } diff --git a/inst/extdata/metadata/Summary_ValueAddedCodeName_2017_metadata.json b/inst/extdata/metadata/Summary_ValueAddedCodeName_2017_metadata.json new file mode 100644 index 00000000..e82f21b4 --- /dev/null +++ b/inst/extdata/metadata/Summary_ValueAddedCodeName_2017_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_ValueAddedCodeName_2017"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": [2017], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/iTables%20Static%20Files/AllTablesIO.zip"], + "date_last_modified": ["2023-12-07"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/inst/extdata/metadata/Summary_ValueAdded_IO_metadata.json b/inst/extdata/metadata/Summary_ValueAdded_IO_12sch_metadata.json similarity index 100% rename from inst/extdata/metadata/Summary_ValueAdded_IO_metadata.json rename to inst/extdata/metadata/Summary_ValueAdded_IO_12sch_metadata.json diff --git a/inst/extdata/metadata/Summary_ValueAdded_IO_17sch_metadata.json b/inst/extdata/metadata/Summary_ValueAdded_IO_17sch_metadata.json new file mode 100644 index 00000000..565dfc1f --- /dev/null +++ b/inst/extdata/metadata/Summary_ValueAdded_IO_17sch_metadata.json @@ -0,0 +1,14 @@ +{ + "tool": ["useeior"], + "name_data": ["Summary_ValueAdded_IO_17sch"], + "tool_version": ["1.4.0"], + "ext": ["json"], + "date_created": ["2024-02-17"], + "data_meta": { + "data_year": ["2017", "2018", "2019", "2020", "2021", "2022"], + "author": ["US Bureau of Economic Analysis"], + "source_url": ["https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip"], + "date_last_modified": ["2023-11-20"], + "date_accessed": ["2024-02-17"] + } +} diff --git a/man/Detail_CPI_IO_17sch.Rd b/man/Detail_CPI_IO_17sch.Rd new file mode 100644 index 00000000..992d8889 --- /dev/null +++ b/man/Detail_CPI_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_CPI_IO_17sch} +\alias{Detail_CPI_IO_17sch} +\title{Detail 2017-2022 CPI (2017 schema)} +\format{ +A dataframe with 402 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Detail_CPI_IO_17sch +} +\description{ +Detail 2017-2022 CPI (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_CommodityCodeName_2017.Rd b/man/Detail_CommodityCodeName_2017.Rd new file mode 100644 index 00000000..ebff41f6 --- /dev/null +++ b/man/Detail_CommodityCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_CommodityCodeName_2017} +\alias{Detail_CommodityCodeName_2017} +\title{Detail Commodity Code and Name (2017 schema)} +\format{ +A dataframe with 402 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_CommodityCodeName_2017 +} +\description{ +Detail Commodity Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_FinalDemandCodeName_2017.Rd b/man/Detail_FinalDemandCodeName_2017.Rd new file mode 100644 index 00000000..0e753371 --- /dev/null +++ b/man/Detail_FinalDemandCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_FinalDemandCodeName_2017} +\alias{Detail_FinalDemandCodeName_2017} +\title{Detail Final Demand Code and Name (2017 schema)} +\format{ +A dataframe with 20 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_FinalDemandCodeName_2017 +} +\description{ +Detail Final Demand Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_GrossOutput_IO_17sch.Rd b/man/Detail_GrossOutput_IO_17sch.Rd new file mode 100644 index 00000000..f7b0a414 --- /dev/null +++ b/man/Detail_GrossOutput_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_GrossOutput_IO_17sch} +\alias{Detail_GrossOutput_IO_17sch} +\title{Detail 2017-2022 Gross Output (2017 schema)} +\format{ +A dataframe with 402 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Detail_GrossOutput_IO_17sch +} +\description{ +Detail 2017-2022 Gross Output (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Import_2017_BeforeRedef_17sch.Rd b/man/Detail_Import_2017_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..36b3dfdc --- /dev/null +++ b/man/Detail_Import_2017_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Import_2017_BeforeRedef_17sch} +\alias{Detail_Import_2017_BeforeRedef_17sch} +\title{Detail 2017 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 402 obs. and 424 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_DET_2017.xlsx} +} +\usage{ +Detail_Import_2017_BeforeRedef_17sch +} +\description{ +Detail 2017 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_IndustryCodeName_2017.Rd b/man/Detail_IndustryCodeName_2017.Rd new file mode 100644 index 00000000..41618417 --- /dev/null +++ b/man/Detail_IndustryCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_IndustryCodeName_2017} +\alias{Detail_IndustryCodeName_2017} +\title{Detail Industry Code and Name (2017 schema)} +\format{ +A dataframe with 402 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_IndustryCodeName_2017 +} +\description{ +Detail Industry Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Make_2017_AfterRedef_17sch.Rd b/man/Detail_Make_2017_AfterRedef_17sch.Rd new file mode 100644 index 00000000..58d281b0 --- /dev/null +++ b/man/Detail_Make_2017_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Make_2017_AfterRedef_17sch} +\alias{Detail_Make_2017_AfterRedef_17sch} +\title{Detail 2017 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 403 obs. and 403 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_Make_2017_AfterRedef_17sch +} +\description{ +Detail 2017 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Make_2017_BeforeRedef_17sch.Rd b/man/Detail_Make_2017_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..4696e65d --- /dev/null +++ b/man/Detail_Make_2017_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Make_2017_BeforeRedef_17sch} +\alias{Detail_Make_2017_BeforeRedef_17sch} +\title{Detail 2017 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 403 obs. and 403 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_Make_2017_BeforeRedef_17sch +} +\description{ +Detail 2017 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Margins_2017_BeforeRedef_17sch.Rd b/man/Detail_Margins_2017_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..31436bbe --- /dev/null +++ b/man/Detail_Margins_2017_BeforeRedef_17sch.Rd @@ -0,0 +1,30 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Margins_2017_BeforeRedef_17sch} +\alias{Detail_Margins_2017_BeforeRedef_17sch} +\title{Detail Margins (Before Redef) table for 2017 (2017 schema)} +\format{ +A dataframe with 58051 obs. and 9 variables: +\describe{ + \item{NIPACode}{text code} + \item{MarginsCategory}{text category name, like 'Therapeutic medical equipment'} + \item{CommodityCode}{BEA_2017_Detail_Code} + \item{CommodityDescription}{BEA_2017_Detail_Name} + \item{ProducersValue}{USD2017} + \item{Transportation}{USD2017} + \item{Wholesale}{USD2017} + \item{Retail}{USD2017} + \item{PurchasersValue}{USD2017} +} +} +\source{ +\url{https://apps.bea.gov/industry/xls/underlying-estimates/Margins_Before_Redefinitions_2017.xlsx} +} +\usage{ +Detail_Margins_2017_BeforeRedef_17sch +} +\description{ +Detail Margins (Before Redef) table for 2017 (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_Supply_2011.Rd b/man/Detail_Supply_2017_17sch.Rd similarity index 55% rename from man/Sector_Supply_2011.Rd rename to man/Detail_Supply_2017_17sch.Rd index 1101ca15..5a327255 100644 --- a/man/Sector_Supply_2011.Rd +++ b/man/Detail_Supply_2017_17sch.Rd @@ -1,19 +1,19 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Sector_Supply_2011} -\alias{Sector_Supply_2011} -\title{Sector 2011 Supply (2012 schema)} +\name{Detail_Supply_2017_17sch} +\alias{Detail_Supply_2017_17sch} +\title{Detail 2017 Supply (2017 schema)} \format{ -A dataframe with 18 obs. and 27 variables +A dataframe with 403 obs. and 414 variables } \source{ \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Sector_Supply_2011 +Detail_Supply_2017_17sch } \description{ -Sector 2011 Supply (2012 schema) +Detail 2017 Supply (2017 schema) } \keyword{datasets} diff --git a/man/Detail_Use_2017_PRO_AfterRedef_17sch.Rd b/man/Detail_Use_2017_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..a593e50e --- /dev/null +++ b/man/Detail_Use_2017_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Use_2017_PRO_AfterRedef_17sch} +\alias{Detail_Use_2017_PRO_AfterRedef_17sch} +\title{Detail 2017 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 408 obs. and 425 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_Use_2017_PRO_AfterRedef_17sch +} +\description{ +Detail 2017 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Use_2017_PRO_BeforeRedef_17sch.Rd b/man/Detail_Use_2017_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..cfeb1241 --- /dev/null +++ b/man/Detail_Use_2017_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Use_2017_PRO_BeforeRedef_17sch} +\alias{Detail_Use_2017_PRO_BeforeRedef_17sch} +\title{Detail 2017 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 408 obs. and 425 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_Use_2017_PRO_BeforeRedef_17sch +} +\description{ +Detail 2017 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Use_2017_PUR_AfterRedef_17sch.Rd b/man/Detail_Use_2017_PUR_AfterRedef_17sch.Rd new file mode 100644 index 00000000..0952b85d --- /dev/null +++ b/man/Detail_Use_2017_PUR_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Use_2017_PUR_AfterRedef_17sch} +\alias{Detail_Use_2017_PUR_AfterRedef_17sch} +\title{Detail 2017 Use Purchaser's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 400 obs. and 425 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_Use_2017_PUR_AfterRedef_17sch +} +\description{ +Detail 2017 Use Purchaser's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Use_2017_PUR_BeforeRedef_17sch.Rd b/man/Detail_Use_2017_PUR_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..1f188f68 --- /dev/null +++ b/man/Detail_Use_2017_PUR_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Use_2017_PUR_BeforeRedef_17sch} +\alias{Detail_Use_2017_PUR_BeforeRedef_17sch} +\title{Detail 2017 Use Purchaser's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 400 obs. and 425 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_Use_2017_PUR_BeforeRedef_17sch +} +\description{ +Detail 2017 Use Purchaser's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_Use_SUT_2017_17sch.Rd b/man/Detail_Use_SUT_2017_17sch.Rd new file mode 100644 index 00000000..91e66996 --- /dev/null +++ b/man/Detail_Use_SUT_2017_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_Use_SUT_2017_17sch} +\alias{Detail_Use_SUT_2017_17sch} +\title{Detail 2017 Use (under the Supply-Use framework, 2017 schema)} +\format{ +A dataframe with 411 obs. and 423 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +} +\usage{ +Detail_Use_SUT_2017_17sch +} +\description{ +Detail 2017 Use (under the Supply-Use framework, 2017 schema) +} +\keyword{datasets} diff --git a/man/Detail_ValueAddedCodeName_2017.Rd b/man/Detail_ValueAddedCodeName_2017.Rd new file mode 100644 index 00000000..5e1ca924 --- /dev/null +++ b/man/Detail_ValueAddedCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Detail_ValueAddedCodeName_2017} +\alias{Detail_ValueAddedCodeName_2017} +\title{Detail Value Added Code and Name (2017 schema)} +\format{ +A dataframe with 3 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Detail_ValueAddedCodeName_2017 +} +\description{ +Detail Value Added Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/MasterCrosswalk.Rd b/man/MasterCrosswalk.Rd new file mode 100644 index 00000000..80ec0ac1 --- /dev/null +++ b/man/MasterCrosswalk.Rd @@ -0,0 +1,30 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{MasterCrosswalk} +\alias{MasterCrosswalk} +\title{Master Crosswalk table (2017 schema)} +\format{ +A dataframe with 4095 obs. and 12 variables: +\describe{ + \item{BEA_2017_Sector_Code}{text code} + \item{BEA_2017_Sector_Name}{text code} + \item{BEA_2017_Summary_Code}{text code} + \item{BEA_2017_Summary_Name}{text code} + \item{BEA_2017_Detail_Code}{text code} + \item{BEA_2017_Detail_Name}{text code} + \item{USEEIO_Code}{text code} + \item{USEEIO_Name}{text code} + \item{NAICS_2017_Code}{text code} + \item{NAICS_2017_Name}{text code} + \item{NAICS_2012_Code}{text code} + \item{NAICS_2007_Code}{text code} +} +} +\usage{ +MasterCrosswalk +} +\description{ +Master Crosswalk table (2017 schema) +} +\keyword{datasets} diff --git a/man/MasterCrosswalk2017.Rd b/man/MasterCrosswalk2017.Rd new file mode 100644 index 00000000..fd27dfea --- /dev/null +++ b/man/MasterCrosswalk2017.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{MasterCrosswalk2017} +\alias{MasterCrosswalk2017} +\title{Master Crosswalk table (2017 schema)} +\format{ +A dataframe with 4095 obs. and 5 variables: +\describe{ + \item{BEA_2017_Sector_Code}{text code} + \item{BEA_2017_Summary_Code}{text code} + \item{BEA_2017_Detail_Code}{text code} + \item{NAICS_2017_Code}{text code} + \item{NAICS_2012_Code}{text code} +} +} +\usage{ +MasterCrosswalk2017 +} +\description{ +Master Crosswalk table (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_CPI_IO_17sch.Rd b/man/Sector_CPI_IO_17sch.Rd new file mode 100644 index 00000000..9957fb18 --- /dev/null +++ b/man/Sector_CPI_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_CPI_IO_17sch} +\alias{Sector_CPI_IO_17sch} +\title{Sector 2017-2022 CPI (2017 schema)} +\format{ +A dataframe with 15 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Sector_CPI_IO_17sch +} +\description{ +Sector 2017-2022 CPI (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_CommodityCodeName_2017.Rd b/man/Sector_CommodityCodeName_2017.Rd new file mode 100644 index 00000000..5ad5f525 --- /dev/null +++ b/man/Sector_CommodityCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_CommodityCodeName_2017} +\alias{Sector_CommodityCodeName_2017} +\title{Sector Commodity Code and Name (2017 schema)} +\format{ +A dataframe with 17 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Sector_CommodityCodeName_2017 +} +\description{ +Sector Commodity Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_FinalDemandCodeName_2017.Rd b/man/Sector_FinalDemandCodeName_2017.Rd new file mode 100644 index 00000000..8b1624f6 --- /dev/null +++ b/man/Sector_FinalDemandCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_FinalDemandCodeName_2017} +\alias{Sector_FinalDemandCodeName_2017} +\title{Sector Final Demand Code and Name (2017 schema)} +\format{ +A dataframe with 6 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Sector_FinalDemandCodeName_2017 +} +\description{ +Sector Final Demand Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_GrossOutput_IO_17sch.Rd b/man/Sector_GrossOutput_IO_17sch.Rd new file mode 100644 index 00000000..9a4cc8e9 --- /dev/null +++ b/man/Sector_GrossOutput_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_GrossOutput_IO_17sch} +\alias{Sector_GrossOutput_IO_17sch} +\title{Sector 2017-2022 Gross Output (2017 schema)} +\format{ +A dataframe with 15 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Sector_GrossOutput_IO_17sch +} +\description{ +Sector 2017-2022 Gross Output (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_IndustryCodeName_2017.Rd b/man/Sector_IndustryCodeName_2017.Rd new file mode 100644 index 00000000..bbda2d45 --- /dev/null +++ b/man/Sector_IndustryCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_IndustryCodeName_2017} +\alias{Sector_IndustryCodeName_2017} +\title{Sector Industry Code and Name (2017 schema)} +\format{ +A dataframe with 17 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Sector_IndustryCodeName_2017 +} +\description{ +Sector Industry Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_Make_2010_AfterRedef.Rd b/man/Sector_Make_2010_AfterRedef.Rd deleted file mode 100644 index e4d8c53d..00000000 --- a/man/Sector_Make_2010_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2010_AfterRedef} -\alias{Sector_Make_2010_AfterRedef} -\title{Sector 2010 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2010_AfterRedef -} -\description{ -Sector 2010 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2010_BeforeRedef.Rd b/man/Sector_Make_2010_BeforeRedef.Rd deleted file mode 100644 index f19c2215..00000000 --- a/man/Sector_Make_2010_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2010_BeforeRedef} -\alias{Sector_Make_2010_BeforeRedef} -\title{Sector 2010 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2010_BeforeRedef -} -\description{ -Sector 2010 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2011_AfterRedef.Rd b/man/Sector_Make_2011_AfterRedef.Rd deleted file mode 100644 index 94a81d50..00000000 --- a/man/Sector_Make_2011_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2011_AfterRedef} -\alias{Sector_Make_2011_AfterRedef} -\title{Sector 2011 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2011_AfterRedef -} -\description{ -Sector 2011 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2011_BeforeRedef.Rd b/man/Sector_Make_2011_BeforeRedef.Rd deleted file mode 100644 index 6ac81993..00000000 --- a/man/Sector_Make_2011_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2011_BeforeRedef} -\alias{Sector_Make_2011_BeforeRedef} -\title{Sector 2011 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2011_BeforeRedef -} -\description{ -Sector 2011 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2012_AfterRedef.Rd b/man/Sector_Make_2012_AfterRedef.Rd deleted file mode 100644 index 1fa18aba..00000000 --- a/man/Sector_Make_2012_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2012_AfterRedef} -\alias{Sector_Make_2012_AfterRedef} -\title{Sector 2012 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2012_AfterRedef -} -\description{ -Sector 2012 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2012_BeforeRedef.Rd b/man/Sector_Make_2012_BeforeRedef.Rd deleted file mode 100644 index f8ffd583..00000000 --- a/man/Sector_Make_2012_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2012_BeforeRedef} -\alias{Sector_Make_2012_BeforeRedef} -\title{Sector 2012 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2012_BeforeRedef -} -\description{ -Sector 2012 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2013_AfterRedef.Rd b/man/Sector_Make_2013_AfterRedef.Rd deleted file mode 100644 index 3e07dabc..00000000 --- a/man/Sector_Make_2013_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2013_AfterRedef} -\alias{Sector_Make_2013_AfterRedef} -\title{Sector 2013 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2013_AfterRedef -} -\description{ -Sector 2013 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2013_BeforeRedef.Rd b/man/Sector_Make_2013_BeforeRedef.Rd deleted file mode 100644 index 86165030..00000000 --- a/man/Sector_Make_2013_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2013_BeforeRedef} -\alias{Sector_Make_2013_BeforeRedef} -\title{Sector 2013 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2013_BeforeRedef -} -\description{ -Sector 2013 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2014_AfterRedef.Rd b/man/Sector_Make_2014_AfterRedef.Rd deleted file mode 100644 index b3524a8c..00000000 --- a/man/Sector_Make_2014_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2014_AfterRedef} -\alias{Sector_Make_2014_AfterRedef} -\title{Sector 2014 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2014_AfterRedef -} -\description{ -Sector 2014 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2014_BeforeRedef.Rd b/man/Sector_Make_2014_BeforeRedef.Rd deleted file mode 100644 index 53a2693d..00000000 --- a/man/Sector_Make_2014_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2014_BeforeRedef} -\alias{Sector_Make_2014_BeforeRedef} -\title{Sector 2014 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2014_BeforeRedef -} -\description{ -Sector 2014 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2015_AfterRedef.Rd b/man/Sector_Make_2015_AfterRedef.Rd deleted file mode 100644 index cbf6ac27..00000000 --- a/man/Sector_Make_2015_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2015_AfterRedef} -\alias{Sector_Make_2015_AfterRedef} -\title{Sector 2015 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2015_AfterRedef -} -\description{ -Sector 2015 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2015_BeforeRedef.Rd b/man/Sector_Make_2015_BeforeRedef.Rd deleted file mode 100644 index 167cd3f3..00000000 --- a/man/Sector_Make_2015_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2015_BeforeRedef} -\alias{Sector_Make_2015_BeforeRedef} -\title{Sector 2015 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2015_BeforeRedef -} -\description{ -Sector 2015 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2016_AfterRedef.Rd b/man/Sector_Make_2016_AfterRedef.Rd deleted file mode 100644 index 5fb3b0db..00000000 --- a/man/Sector_Make_2016_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2016_AfterRedef} -\alias{Sector_Make_2016_AfterRedef} -\title{Sector 2016 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2016_AfterRedef -} -\description{ -Sector 2016 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2016_BeforeRedef.Rd b/man/Sector_Make_2016_BeforeRedef.Rd deleted file mode 100644 index 1430e5be..00000000 --- a/man/Sector_Make_2016_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2016_BeforeRedef} -\alias{Sector_Make_2016_BeforeRedef} -\title{Sector 2016 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2016_BeforeRedef -} -\description{ -Sector 2016 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2017_AfterRedef.Rd b/man/Sector_Make_2017_AfterRedef.Rd deleted file mode 100644 index 3962a283..00000000 --- a/man/Sector_Make_2017_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2017_AfterRedef} -\alias{Sector_Make_2017_AfterRedef} -\title{Sector 2017 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2017_AfterRedef -} -\description{ -Sector 2017 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2017_BeforeRedef.Rd b/man/Sector_Make_2017_BeforeRedef.Rd deleted file mode 100644 index 1a558a08..00000000 --- a/man/Sector_Make_2017_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2017_BeforeRedef} -\alias{Sector_Make_2017_BeforeRedef} -\title{Sector 2017 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2017_BeforeRedef -} -\description{ -Sector 2017 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2018_AfterRedef.Rd b/man/Sector_Make_2018_AfterRedef.Rd deleted file mode 100644 index 8ea1fa82..00000000 --- a/man/Sector_Make_2018_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2018_AfterRedef} -\alias{Sector_Make_2018_AfterRedef} -\title{Sector 2018 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2018_AfterRedef -} -\description{ -Sector 2018 Make After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2018_BeforeRedef.Rd b/man/Sector_Make_2018_BeforeRedef.Rd deleted file mode 100644 index 7d150d8a..00000000 --- a/man/Sector_Make_2018_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2018_BeforeRedef} -\alias{Sector_Make_2018_BeforeRedef} -\title{Sector 2018 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Make_2018_BeforeRedef -} -\description{ -Sector 2018 Make Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Make_2019_AfterRedef.Rd b/man/Sector_Make_2019_AfterRedef.Rd deleted file mode 100644 index 94885cdc..00000000 --- a/man/Sector_Make_2019_AfterRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2019_AfterRedef} -\alias{Sector_Make_2019_AfterRedef} -\title{Sector 2019 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Make_2019_AfterRedef -} -\description{ -Sector 2019 Make After Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Make_2019_BeforeRedef.Rd b/man/Sector_Make_2019_BeforeRedef.Rd deleted file mode 100644 index c580783f..00000000 --- a/man/Sector_Make_2019_BeforeRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2019_BeforeRedef} -\alias{Sector_Make_2019_BeforeRedef} -\title{Sector 2019 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Make_2019_BeforeRedef -} -\description{ -Sector 2019 Make Before Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Make_2020_AfterRedef.Rd b/man/Sector_Make_2020_AfterRedef.Rd deleted file mode 100644 index b566aa68..00000000 --- a/man/Sector_Make_2020_AfterRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2020_AfterRedef} -\alias{Sector_Make_2020_AfterRedef} -\title{Sector 2020 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Make_2020_AfterRedef -} -\description{ -Sector 2020 Make After Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Make_2020_BeforeRedef.Rd b/man/Sector_Make_2020_BeforeRedef.Rd deleted file mode 100644 index a99c4807..00000000 --- a/man/Sector_Make_2020_BeforeRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2020_BeforeRedef} -\alias{Sector_Make_2020_BeforeRedef} -\title{Sector 2020 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Make_2020_BeforeRedef -} -\description{ -Sector 2020 Make Before Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Make_2021_AfterRedef.Rd b/man/Sector_Make_2021_AfterRedef.Rd deleted file mode 100644 index a33edee9..00000000 --- a/man/Sector_Make_2021_AfterRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2021_AfterRedef} -\alias{Sector_Make_2021_AfterRedef} -\title{Sector 2021 Make After Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Make_2021_AfterRedef -} -\description{ -Sector 2021 Make After Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Make_2021_BeforeRedef.Rd b/man/Sector_Make_2021_BeforeRedef.Rd deleted file mode 100644 index 73bce8ab..00000000 --- a/man/Sector_Make_2021_BeforeRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Make_2021_BeforeRedef} -\alias{Sector_Make_2021_BeforeRedef} -\title{Sector 2021 Make Before Redefinition (2012 schema)} -\format{ -A dataframe with 16 obs. and 18 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Make_2021_BeforeRedef -} -\description{ -Sector 2021 Make Before Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Supply_2010.Rd b/man/Sector_Supply_2010.Rd deleted file mode 100644 index d75eb06e..00000000 --- a/man/Sector_Supply_2010.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2010} -\alias{Sector_Supply_2010} -\title{Sector 2010 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2010 -} -\description{ -Sector 2010 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2012.Rd b/man/Sector_Supply_2012.Rd deleted file mode 100644 index ce127132..00000000 --- a/man/Sector_Supply_2012.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2012} -\alias{Sector_Supply_2012} -\title{Sector 2012 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2012 -} -\description{ -Sector 2012 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2013.Rd b/man/Sector_Supply_2013.Rd deleted file mode 100644 index e06719f5..00000000 --- a/man/Sector_Supply_2013.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2013} -\alias{Sector_Supply_2013} -\title{Sector 2013 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2013 -} -\description{ -Sector 2013 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2014.Rd b/man/Sector_Supply_2014.Rd deleted file mode 100644 index b7cf0555..00000000 --- a/man/Sector_Supply_2014.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2014} -\alias{Sector_Supply_2014} -\title{Sector 2014 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2014 -} -\description{ -Sector 2014 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2015.Rd b/man/Sector_Supply_2015.Rd deleted file mode 100644 index d5a998ec..00000000 --- a/man/Sector_Supply_2015.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2015} -\alias{Sector_Supply_2015} -\title{Sector 2015 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2015 -} -\description{ -Sector 2015 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2016.Rd b/man/Sector_Supply_2016.Rd deleted file mode 100644 index bd3a1a2d..00000000 --- a/man/Sector_Supply_2016.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2016} -\alias{Sector_Supply_2016} -\title{Sector 2016 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2016 -} -\description{ -Sector 2016 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2017.Rd b/man/Sector_Supply_2017.Rd deleted file mode 100644 index 12cf0d8d..00000000 --- a/man/Sector_Supply_2017.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2017} -\alias{Sector_Supply_2017} -\title{Sector 2017 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2017 -} -\description{ -Sector 2017 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2018.Rd b/man/Sector_Supply_2018.Rd deleted file mode 100644 index 6e07087e..00000000 --- a/man/Sector_Supply_2018.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2018} -\alias{Sector_Supply_2018} -\title{Sector 2018 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2018 -} -\description{ -Sector 2018 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2019.Rd b/man/Sector_Supply_2019.Rd deleted file mode 100644 index 7307fce2..00000000 --- a/man/Sector_Supply_2019.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2019} -\alias{Sector_Supply_2019} -\title{Sector 2019 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2019 -} -\description{ -Sector 2019 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Supply_2020.Rd b/man/Sector_Supply_2020.Rd deleted file mode 100644 index 700342d9..00000000 --- a/man/Sector_Supply_2020.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Supply_2020} -\alias{Sector_Supply_2020} -\title{Sector 2020 Supply (2012 schema)} -\format{ -A dataframe with 18 obs. and 27 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Supply_2020 -} -\description{ -Sector 2020 Supply (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2010_PRO_AfterRedef.Rd b/man/Sector_Use_2010_PRO_AfterRedef.Rd deleted file mode 100644 index 48608d91..00000000 --- a/man/Sector_Use_2010_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2010_PRO_AfterRedef} -\alias{Sector_Use_2010_PRO_AfterRedef} -\title{Sector 2010 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2010_PRO_AfterRedef -} -\description{ -Sector 2010 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2010_PRO_BeforeRedef.Rd b/man/Sector_Use_2010_PRO_BeforeRedef.Rd deleted file mode 100644 index 23d3473f..00000000 --- a/man/Sector_Use_2010_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2010_PRO_BeforeRedef} -\alias{Sector_Use_2010_PRO_BeforeRedef} -\title{Sector 2010 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2010_PRO_BeforeRedef -} -\description{ -Sector 2010 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2011_PRO_AfterRedef.Rd b/man/Sector_Use_2011_PRO_AfterRedef.Rd deleted file mode 100644 index ed4da87e..00000000 --- a/man/Sector_Use_2011_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2011_PRO_AfterRedef} -\alias{Sector_Use_2011_PRO_AfterRedef} -\title{Sector 2011 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2011_PRO_AfterRedef -} -\description{ -Sector 2011 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2011_PRO_BeforeRedef.Rd b/man/Sector_Use_2011_PRO_BeforeRedef.Rd deleted file mode 100644 index e66672d5..00000000 --- a/man/Sector_Use_2011_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2011_PRO_BeforeRedef} -\alias{Sector_Use_2011_PRO_BeforeRedef} -\title{Sector 2011 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2011_PRO_BeforeRedef -} -\description{ -Sector 2011 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2012_PRO_AfterRedef.Rd b/man/Sector_Use_2012_PRO_AfterRedef.Rd deleted file mode 100644 index e7c417ee..00000000 --- a/man/Sector_Use_2012_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2012_PRO_AfterRedef} -\alias{Sector_Use_2012_PRO_AfterRedef} -\title{Sector 2012 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2012_PRO_AfterRedef -} -\description{ -Sector 2012 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2012_PRO_BeforeRedef.Rd b/man/Sector_Use_2012_PRO_BeforeRedef.Rd deleted file mode 100644 index 012b6b76..00000000 --- a/man/Sector_Use_2012_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2012_PRO_BeforeRedef} -\alias{Sector_Use_2012_PRO_BeforeRedef} -\title{Sector 2012 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2012_PRO_BeforeRedef -} -\description{ -Sector 2012 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2012_PUR_BeforeRedef.Rd b/man/Sector_Use_2012_PUR_BeforeRedef.Rd deleted file mode 100644 index 51c451b7..00000000 --- a/man/Sector_Use_2012_PUR_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2012_PUR_BeforeRedef} -\alias{Sector_Use_2012_PUR_BeforeRedef} -\title{Sector 2012 Use Purchaser's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2012_PUR_BeforeRedef -} -\description{ -Sector 2012 Use Purchaser's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2013_PRO_AfterRedef.Rd b/man/Sector_Use_2013_PRO_AfterRedef.Rd deleted file mode 100644 index 5155107e..00000000 --- a/man/Sector_Use_2013_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2013_PRO_AfterRedef} -\alias{Sector_Use_2013_PRO_AfterRedef} -\title{Sector 2013 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2013_PRO_AfterRedef -} -\description{ -Sector 2013 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2013_PRO_BeforeRedef.Rd b/man/Sector_Use_2013_PRO_BeforeRedef.Rd deleted file mode 100644 index ba326ebc..00000000 --- a/man/Sector_Use_2013_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2013_PRO_BeforeRedef} -\alias{Sector_Use_2013_PRO_BeforeRedef} -\title{Sector 2013 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2013_PRO_BeforeRedef -} -\description{ -Sector 2013 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2014_PRO_AfterRedef.Rd b/man/Sector_Use_2014_PRO_AfterRedef.Rd deleted file mode 100644 index 0f3aedb2..00000000 --- a/man/Sector_Use_2014_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2014_PRO_AfterRedef} -\alias{Sector_Use_2014_PRO_AfterRedef} -\title{Sector 2014 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2014_PRO_AfterRedef -} -\description{ -Sector 2014 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2014_PRO_BeforeRedef.Rd b/man/Sector_Use_2014_PRO_BeforeRedef.Rd deleted file mode 100644 index 2344657e..00000000 --- a/man/Sector_Use_2014_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2014_PRO_BeforeRedef} -\alias{Sector_Use_2014_PRO_BeforeRedef} -\title{Sector 2014 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2014_PRO_BeforeRedef -} -\description{ -Sector 2014 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2015_PRO_AfterRedef.Rd b/man/Sector_Use_2015_PRO_AfterRedef.Rd deleted file mode 100644 index 15f2f34d..00000000 --- a/man/Sector_Use_2015_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2015_PRO_AfterRedef} -\alias{Sector_Use_2015_PRO_AfterRedef} -\title{Sector 2015 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2015_PRO_AfterRedef -} -\description{ -Sector 2015 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2015_PRO_BeforeRedef.Rd b/man/Sector_Use_2015_PRO_BeforeRedef.Rd deleted file mode 100644 index ebc16ac6..00000000 --- a/man/Sector_Use_2015_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2015_PRO_BeforeRedef} -\alias{Sector_Use_2015_PRO_BeforeRedef} -\title{Sector 2015 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2015_PRO_BeforeRedef -} -\description{ -Sector 2015 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2016_PRO_AfterRedef.Rd b/man/Sector_Use_2016_PRO_AfterRedef.Rd deleted file mode 100644 index 72ca0d3d..00000000 --- a/man/Sector_Use_2016_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2016_PRO_AfterRedef} -\alias{Sector_Use_2016_PRO_AfterRedef} -\title{Sector 2016 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2016_PRO_AfterRedef -} -\description{ -Sector 2016 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2016_PRO_BeforeRedef.Rd b/man/Sector_Use_2016_PRO_BeforeRedef.Rd deleted file mode 100644 index 8804feaf..00000000 --- a/man/Sector_Use_2016_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2016_PRO_BeforeRedef} -\alias{Sector_Use_2016_PRO_BeforeRedef} -\title{Sector 2016 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2016_PRO_BeforeRedef -} -\description{ -Sector 2016 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2017_PRO_AfterRedef.Rd b/man/Sector_Use_2017_PRO_AfterRedef.Rd deleted file mode 100644 index 4cee2d84..00000000 --- a/man/Sector_Use_2017_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2017_PRO_AfterRedef} -\alias{Sector_Use_2017_PRO_AfterRedef} -\title{Sector 2017 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2017_PRO_AfterRedef -} -\description{ -Sector 2017 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2017_PRO_BeforeRedef.Rd b/man/Sector_Use_2017_PRO_BeforeRedef.Rd deleted file mode 100644 index 83127160..00000000 --- a/man/Sector_Use_2017_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2017_PRO_BeforeRedef} -\alias{Sector_Use_2017_PRO_BeforeRedef} -\title{Sector 2017 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2017_PRO_BeforeRedef -} -\description{ -Sector 2017 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2018_PRO_AfterRedef.Rd b/man/Sector_Use_2018_PRO_AfterRedef.Rd deleted file mode 100644 index 47391b7a..00000000 --- a/man/Sector_Use_2018_PRO_AfterRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2018_PRO_AfterRedef} -\alias{Sector_Use_2018_PRO_AfterRedef} -\title{Sector 2018 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2018_PRO_AfterRedef -} -\description{ -Sector 2018 Use Producer's Value After Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2018_PRO_BeforeRedef.Rd b/man/Sector_Use_2018_PRO_BeforeRedef.Rd deleted file mode 100644 index 80d64711..00000000 --- a/man/Sector_Use_2018_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2018_PRO_BeforeRedef} -\alias{Sector_Use_2018_PRO_BeforeRedef} -\title{Sector 2018 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://edap-ord-data-commons.s3.amazonaws.com/useeior/AllTablesIO.zip} -} -\usage{ -Sector_Use_2018_PRO_BeforeRedef -} -\description{ -Sector 2018 Use Producer's Value Before Redefinition (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_2019_PRO_AfterRedef.Rd b/man/Sector_Use_2019_PRO_AfterRedef.Rd deleted file mode 100644 index 8cba2d1d..00000000 --- a/man/Sector_Use_2019_PRO_AfterRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2019_PRO_AfterRedef} -\alias{Sector_Use_2019_PRO_AfterRedef} -\title{Sector 2019 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Use_2019_PRO_AfterRedef -} -\description{ -Sector 2019 Use Producer's Value After Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Use_2019_PRO_BeforeRedef.Rd b/man/Sector_Use_2019_PRO_BeforeRedef.Rd deleted file mode 100644 index de5028b9..00000000 --- a/man/Sector_Use_2019_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2019_PRO_BeforeRedef} -\alias{Sector_Use_2019_PRO_BeforeRedef} -\title{Sector 2019 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Use_2019_PRO_BeforeRedef -} -\description{ -Sector 2019 Use Producer's Value Before Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Use_2020_PRO_AfterRedef.Rd b/man/Sector_Use_2020_PRO_AfterRedef.Rd deleted file mode 100644 index e1236cbd..00000000 --- a/man/Sector_Use_2020_PRO_AfterRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2020_PRO_AfterRedef} -\alias{Sector_Use_2020_PRO_AfterRedef} -\title{Sector 2020 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Use_2020_PRO_AfterRedef -} -\description{ -Sector 2020 Use Producer's Value After Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Use_2020_PRO_BeforeRedef.Rd b/man/Sector_Use_2020_PRO_BeforeRedef.Rd deleted file mode 100644 index 71304433..00000000 --- a/man/Sector_Use_2020_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2020_PRO_BeforeRedef} -\alias{Sector_Use_2020_PRO_BeforeRedef} -\title{Sector 2020 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Use_2020_PRO_BeforeRedef -} -\description{ -Sector 2020 Use Producer's Value Before Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Use_2021_PRO_AfterRedef.Rd b/man/Sector_Use_2021_PRO_AfterRedef.Rd deleted file mode 100644 index 13ab3911..00000000 --- a/man/Sector_Use_2021_PRO_AfterRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2021_PRO_AfterRedef} -\alias{Sector_Use_2021_PRO_AfterRedef} -\title{Sector 2021 Use Producer's Value After Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Use_2021_PRO_AfterRedef -} -\description{ -Sector 2021 Use Producer's Value After Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Use_2021_PRO_BeforeRedef.Rd b/man/Sector_Use_2021_PRO_BeforeRedef.Rd deleted file mode 100644 index cee56c32..00000000 --- a/man/Sector_Use_2021_PRO_BeforeRedef.Rd +++ /dev/null @@ -1,22 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_2021_PRO_BeforeRedef} -\alias{Sector_Use_2021_PRO_BeforeRedef} -\title{Sector 2021 Use Producer's Value Before Redefinition (2012 schema)} -\format{ -A dataframe with 23 obs. and 24 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} -} -\usage{ -Sector_Use_2021_PRO_BeforeRedef -} -\description{ -Sector 2021 Use Producer's Value Before Redefinition (2012 schema) -} -\note{ -Remove 'backslash' before 'percent sign' in url to access the source of data. -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2010.Rd b/man/Sector_Use_SUT_2010.Rd deleted file mode 100644 index ac0b975c..00000000 --- a/man/Sector_Use_SUT_2010.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2010} -\alias{Sector_Use_SUT_2010} -\title{Sector 2010 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2010 -} -\description{ -Sector 2010 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2011.Rd b/man/Sector_Use_SUT_2011.Rd deleted file mode 100644 index c37f515a..00000000 --- a/man/Sector_Use_SUT_2011.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2011} -\alias{Sector_Use_SUT_2011} -\title{Sector 2011 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2011 -} -\description{ -Sector 2011 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2012.Rd b/man/Sector_Use_SUT_2012.Rd deleted file mode 100644 index 4807a0a7..00000000 --- a/man/Sector_Use_SUT_2012.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2012} -\alias{Sector_Use_SUT_2012} -\title{Sector 2012 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2012 -} -\description{ -Sector 2012 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2013.Rd b/man/Sector_Use_SUT_2013.Rd deleted file mode 100644 index 9880d5fb..00000000 --- a/man/Sector_Use_SUT_2013.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2013} -\alias{Sector_Use_SUT_2013} -\title{Sector 2013 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2013 -} -\description{ -Sector 2013 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2014.Rd b/man/Sector_Use_SUT_2014.Rd deleted file mode 100644 index 6ec40738..00000000 --- a/man/Sector_Use_SUT_2014.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2014} -\alias{Sector_Use_SUT_2014} -\title{Sector 2014 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2014 -} -\description{ -Sector 2014 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2015.Rd b/man/Sector_Use_SUT_2015.Rd deleted file mode 100644 index 98cec639..00000000 --- a/man/Sector_Use_SUT_2015.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2015} -\alias{Sector_Use_SUT_2015} -\title{Sector 2015 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2015 -} -\description{ -Sector 2015 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2016.Rd b/man/Sector_Use_SUT_2016.Rd deleted file mode 100644 index 43d1f97f..00000000 --- a/man/Sector_Use_SUT_2016.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2016} -\alias{Sector_Use_SUT_2016} -\title{Sector 2016 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2016 -} -\description{ -Sector 2016 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2017.Rd b/man/Sector_Use_SUT_2017.Rd deleted file mode 100644 index 938ada5e..00000000 --- a/man/Sector_Use_SUT_2017.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2017} -\alias{Sector_Use_SUT_2017} -\title{Sector 2017 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2017 -} -\description{ -Sector 2017 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2018.Rd b/man/Sector_Use_SUT_2018.Rd deleted file mode 100644 index f7571c35..00000000 --- a/man/Sector_Use_SUT_2018.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2018} -\alias{Sector_Use_SUT_2018} -\title{Sector 2018 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2018 -} -\description{ -Sector 2018 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2019.Rd b/man/Sector_Use_SUT_2019.Rd deleted file mode 100644 index a5d56153..00000000 --- a/man/Sector_Use_SUT_2019.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2019} -\alias{Sector_Use_SUT_2019} -\title{Sector 2019 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2019 -} -\description{ -Sector 2019 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_Use_SUT_2020.Rd b/man/Sector_Use_SUT_2020.Rd deleted file mode 100644 index 083447a8..00000000 --- a/man/Sector_Use_SUT_2020.Rd +++ /dev/null @@ -1,19 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/DataDocumentation.R -\docType{data} -\name{Sector_Use_SUT_2020} -\alias{Sector_Use_SUT_2020} -\title{Sector 2020 Use (2012 schema)} -\format{ -A dataframe with 26 obs. and 22 variables -} -\source{ -\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} -} -\usage{ -Sector_Use_SUT_2020 -} -\description{ -Sector 2020 Use (2012 schema) -} -\keyword{datasets} diff --git a/man/Sector_ValueAddedCodeName_2017.Rd b/man/Sector_ValueAddedCodeName_2017.Rd new file mode 100644 index 00000000..1bd6165a --- /dev/null +++ b/man/Sector_ValueAddedCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_ValueAddedCodeName_2017} +\alias{Sector_ValueAddedCodeName_2017} +\title{Sector Value Added Code and Name (2017 schema)} +\format{ +A dataframe with 3 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Sector_ValueAddedCodeName_2017 +} +\description{ +Sector Value Added Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Sector_ValueAdded_IO_17sch.Rd b/man/Sector_ValueAdded_IO_17sch.Rd new file mode 100644 index 00000000..468642fd --- /dev/null +++ b/man/Sector_ValueAdded_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Sector_ValueAdded_IO_17sch} +\alias{Sector_ValueAdded_IO_17sch} +\title{Sector 2017-2022 Value Added (2017 schema)} +\format{ +A dataframe with 15 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Sector_ValueAdded_IO_17sch +} +\description{ +Sector 2017-2022 Value Added (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_CPI_IO_17sch.Rd b/man/Summary_CPI_IO_17sch.Rd new file mode 100644 index 00000000..bb7a6d18 --- /dev/null +++ b/man/Summary_CPI_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_CPI_IO_17sch} +\alias{Summary_CPI_IO_17sch} +\title{Summary 2017-2022 CPI (2017 schema)} +\format{ +A dataframe with 71 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Summary_CPI_IO_17sch +} +\description{ +Summary 2017-2022 CPI (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_CommodityCodeName_2017.Rd b/man/Summary_CommodityCodeName_2017.Rd new file mode 100644 index 00000000..3ef9850b --- /dev/null +++ b/man/Summary_CommodityCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_CommodityCodeName_2017} +\alias{Summary_CommodityCodeName_2017} +\title{Summary Commodity Code and Name (2017 schema)} +\format{ +A dataframe with 73 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_CommodityCodeName_2017 +} +\description{ +Summary Commodity Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_FinalDemandCodeName_2017.Rd b/man/Summary_FinalDemandCodeName_2017.Rd new file mode 100644 index 00000000..63639160 --- /dev/null +++ b/man/Summary_FinalDemandCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_FinalDemandCodeName_2017} +\alias{Summary_FinalDemandCodeName_2017} +\title{Summary Final Demand Code and Name (2017 schema)} +\format{ +A dataframe with 20 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_FinalDemandCodeName_2017 +} +\description{ +Summary Final Demand Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_GrossOutput_IO_17sch.Rd b/man/Summary_GrossOutput_IO_17sch.Rd new file mode 100644 index 00000000..7cff9aae --- /dev/null +++ b/man/Summary_GrossOutput_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_GrossOutput_IO_17sch} +\alias{Summary_GrossOutput_IO_17sch} +\title{Summary 2017-2022 Gross Output (2017 schema)} +\format{ +A dataframe with 71 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Summary_GrossOutput_IO_17sch +} +\description{ +Summary 2017-2022 Gross Output (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Import_2017_BeforeRedef_17sch.Rd b/man/Summary_Import_2017_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..271de1d0 --- /dev/null +++ b/man/Summary_Import_2017_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Import_2017_BeforeRedef_17sch} +\alias{Summary_Import_2017_BeforeRedef_17sch} +\title{Summary 2017 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 73 obs. and 93 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +} +\usage{ +Summary_Import_2017_BeforeRedef_17sch +} +\description{ +Summary 2017 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Import_2018_BeforeRedef_17sch.Rd b/man/Summary_Import_2018_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..a82cfaee --- /dev/null +++ b/man/Summary_Import_2018_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Import_2018_BeforeRedef_17sch} +\alias{Summary_Import_2018_BeforeRedef_17sch} +\title{Summary 2018 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 73 obs. and 93 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +} +\usage{ +Summary_Import_2018_BeforeRedef_17sch +} +\description{ +Summary 2018 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Import_2019_BeforeRedef_17sch.Rd b/man/Summary_Import_2019_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..95fc0deb --- /dev/null +++ b/man/Summary_Import_2019_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Import_2019_BeforeRedef_17sch} +\alias{Summary_Import_2019_BeforeRedef_17sch} +\title{Summary 2019 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 73 obs. and 93 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +} +\usage{ +Summary_Import_2019_BeforeRedef_17sch +} +\description{ +Summary 2019 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Import_2020_BeforeRedef_17sch.Rd b/man/Summary_Import_2020_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..4b942e4d --- /dev/null +++ b/man/Summary_Import_2020_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Import_2020_BeforeRedef_17sch} +\alias{Summary_Import_2020_BeforeRedef_17sch} +\title{Summary 2020 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 73 obs. and 93 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +} +\usage{ +Summary_Import_2020_BeforeRedef_17sch +} +\description{ +Summary 2020 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Import_2021_BeforeRedef_17sch.Rd b/man/Summary_Import_2021_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..15ab9f61 --- /dev/null +++ b/man/Summary_Import_2021_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Import_2021_BeforeRedef_17sch} +\alias{Summary_Import_2021_BeforeRedef_17sch} +\title{Summary 2021 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 73 obs. and 93 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +} +\usage{ +Summary_Import_2021_BeforeRedef_17sch +} +\description{ +Summary 2021 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Import_2022_BeforeRedef_17sch.Rd b/man/Summary_Import_2022_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..f2838903 --- /dev/null +++ b/man/Summary_Import_2022_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Import_2022_BeforeRedef_17sch} +\alias{Summary_Import_2022_BeforeRedef_17sch} +\title{Summary 2022 Import Before Redefinition (2017 schema)} +\format{ +A dataframe with 73 obs. and 93 variables +} +\source{ +\url{https://apps.bea.gov/industry/xls/io-annual/ImportMatrices_Before_Redefinitions_SUM_2017-2022.xlsx} +} +\usage{ +Summary_Import_2022_BeforeRedef_17sch +} +\description{ +Summary 2022 Import Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_IndustryCodeName_2017.Rd b/man/Summary_IndustryCodeName_2017.Rd new file mode 100644 index 00000000..8b1f6768 --- /dev/null +++ b/man/Summary_IndustryCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_IndustryCodeName_2017} +\alias{Summary_IndustryCodeName_2017} +\title{Summary Industry Code and Name (2017 schema)} +\format{ +A dataframe with 73 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_IndustryCodeName_2017 +} +\description{ +Summary Industry Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2017_AfterRedef_17sch.Rd b/man/Summary_Make_2017_AfterRedef_17sch.Rd new file mode 100644 index 00000000..a9e68e88 --- /dev/null +++ b/man/Summary_Make_2017_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2017_AfterRedef_17sch} +\alias{Summary_Make_2017_AfterRedef_17sch} +\title{Summary 2017 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2017_AfterRedef_17sch +} +\description{ +Summary 2017 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2017_BeforeRedef_17sch.Rd b/man/Summary_Make_2017_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..6d085757 --- /dev/null +++ b/man/Summary_Make_2017_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2017_BeforeRedef_17sch} +\alias{Summary_Make_2017_BeforeRedef_17sch} +\title{Summary 2017 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2017_BeforeRedef_17sch +} +\description{ +Summary 2017 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2018_AfterRedef_17sch.Rd b/man/Summary_Make_2018_AfterRedef_17sch.Rd new file mode 100644 index 00000000..0c514125 --- /dev/null +++ b/man/Summary_Make_2018_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2018_AfterRedef_17sch} +\alias{Summary_Make_2018_AfterRedef_17sch} +\title{Summary 2018 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2018_AfterRedef_17sch +} +\description{ +Summary 2018 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2018_BeforeRedef_17sch.Rd b/man/Summary_Make_2018_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..b96168d9 --- /dev/null +++ b/man/Summary_Make_2018_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2018_BeforeRedef_17sch} +\alias{Summary_Make_2018_BeforeRedef_17sch} +\title{Summary 2018 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2018_BeforeRedef_17sch +} +\description{ +Summary 2018 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2019_AfterRedef_17sch.Rd b/man/Summary_Make_2019_AfterRedef_17sch.Rd new file mode 100644 index 00000000..9520595f --- /dev/null +++ b/man/Summary_Make_2019_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2019_AfterRedef_17sch} +\alias{Summary_Make_2019_AfterRedef_17sch} +\title{Summary 2019 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2019_AfterRedef_17sch +} +\description{ +Summary 2019 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2019_BeforeRedef_17sch.Rd b/man/Summary_Make_2019_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..cd885aa5 --- /dev/null +++ b/man/Summary_Make_2019_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2019_BeforeRedef_17sch} +\alias{Summary_Make_2019_BeforeRedef_17sch} +\title{Summary 2019 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2019_BeforeRedef_17sch +} +\description{ +Summary 2019 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2020_AfterRedef_17sch.Rd b/man/Summary_Make_2020_AfterRedef_17sch.Rd new file mode 100644 index 00000000..c0c1acc3 --- /dev/null +++ b/man/Summary_Make_2020_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2020_AfterRedef_17sch} +\alias{Summary_Make_2020_AfterRedef_17sch} +\title{Summary 2020 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2020_AfterRedef_17sch +} +\description{ +Summary 2020 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2020_BeforeRedef_17sch.Rd b/man/Summary_Make_2020_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..e455c7d7 --- /dev/null +++ b/man/Summary_Make_2020_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2020_BeforeRedef_17sch} +\alias{Summary_Make_2020_BeforeRedef_17sch} +\title{Summary 2020 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2020_BeforeRedef_17sch +} +\description{ +Summary 2020 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2021_AfterRedef_17sch.Rd b/man/Summary_Make_2021_AfterRedef_17sch.Rd new file mode 100644 index 00000000..8da5e25c --- /dev/null +++ b/man/Summary_Make_2021_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2021_AfterRedef_17sch} +\alias{Summary_Make_2021_AfterRedef_17sch} +\title{Summary 2021 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2021_AfterRedef_17sch +} +\description{ +Summary 2021 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2021_BeforeRedef_17sch.Rd b/man/Summary_Make_2021_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..f28c0cbb --- /dev/null +++ b/man/Summary_Make_2021_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2021_BeforeRedef_17sch} +\alias{Summary_Make_2021_BeforeRedef_17sch} +\title{Summary 2021 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2021_BeforeRedef_17sch +} +\description{ +Summary 2021 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2022_AfterRedef_17sch.Rd b/man/Summary_Make_2022_AfterRedef_17sch.Rd new file mode 100644 index 00000000..6d3d98d8 --- /dev/null +++ b/man/Summary_Make_2022_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2022_AfterRedef_17sch} +\alias{Summary_Make_2022_AfterRedef_17sch} +\title{Summary 2022 Make After Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2022_AfterRedef_17sch +} +\description{ +Summary 2022 Make After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Make_2022_BeforeRedef_17sch.Rd b/man/Summary_Make_2022_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..03185425 --- /dev/null +++ b/man/Summary_Make_2022_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Make_2022_BeforeRedef_17sch} +\alias{Summary_Make_2022_BeforeRedef_17sch} +\title{Summary 2022 Make Before Redefinition (2017 schema)} +\format{ +A dataframe with 72 obs. and 74 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Make_2022_BeforeRedef_17sch +} +\description{ +Summary 2022 Make Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Supply_2017.Rd b/man/Summary_Supply_2017_17sch.Rd similarity index 64% rename from man/Summary_Supply_2017.Rd rename to man/Summary_Supply_2017_17sch.Rd index 6cfa292b..3ed1711f 100644 --- a/man/Summary_Supply_2017.Rd +++ b/man/Summary_Supply_2017_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Supply_2017} -\alias{Summary_Supply_2017} -\title{Summary 2017 Supply (2012 schema)} +\name{Summary_Supply_2017_17sch} +\alias{Summary_Supply_2017_17sch} +\title{Summary 2017 Supply (2017 schema)} \format{ A dataframe with 74 obs. and 83 variables } @@ -11,9 +11,9 @@ A dataframe with 74 obs. and 83 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Supply_2017 +Summary_Supply_2017_17sch } \description{ -Summary 2017 Supply (2012 schema) +Summary 2017 Supply (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Supply_2020.Rd b/man/Summary_Supply_2018_17sch.Rd similarity index 64% rename from man/Summary_Supply_2020.Rd rename to man/Summary_Supply_2018_17sch.Rd index 0b1a5062..4d05f80d 100644 --- a/man/Summary_Supply_2020.Rd +++ b/man/Summary_Supply_2018_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Supply_2020} -\alias{Summary_Supply_2020} -\title{Summary 2020 Supply (2012 schema)} +\name{Summary_Supply_2018_17sch} +\alias{Summary_Supply_2018_17sch} +\title{Summary 2018 Supply (2017 schema)} \format{ A dataframe with 74 obs. and 83 variables } @@ -11,9 +11,9 @@ A dataframe with 74 obs. and 83 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Supply_2020 +Summary_Supply_2018_17sch } \description{ -Summary 2020 Supply (2012 schema) +Summary 2018 Supply (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Supply_2018.Rd b/man/Summary_Supply_2019_17sch.Rd similarity index 64% rename from man/Summary_Supply_2018.Rd rename to man/Summary_Supply_2019_17sch.Rd index 2d9cccb9..74b6cadc 100644 --- a/man/Summary_Supply_2018.Rd +++ b/man/Summary_Supply_2019_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Supply_2018} -\alias{Summary_Supply_2018} -\title{Summary 2018 Supply (2012 schema)} +\name{Summary_Supply_2019_17sch} +\alias{Summary_Supply_2019_17sch} +\title{Summary 2019 Supply (2017 schema)} \format{ A dataframe with 74 obs. and 83 variables } @@ -11,9 +11,9 @@ A dataframe with 74 obs. and 83 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Supply_2018 +Summary_Supply_2019_17sch } \description{ -Summary 2018 Supply (2012 schema) +Summary 2019 Supply (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Supply_2019.Rd b/man/Summary_Supply_2020_17sch.Rd similarity index 64% rename from man/Summary_Supply_2019.Rd rename to man/Summary_Supply_2020_17sch.Rd index dcb3b062..39953798 100644 --- a/man/Summary_Supply_2019.Rd +++ b/man/Summary_Supply_2020_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Supply_2019} -\alias{Summary_Supply_2019} -\title{Summary 2019 Supply (2012 schema)} +\name{Summary_Supply_2020_17sch} +\alias{Summary_Supply_2020_17sch} +\title{Summary 2020 Supply (2017 schema)} \format{ A dataframe with 74 obs. and 83 variables } @@ -11,9 +11,9 @@ A dataframe with 74 obs. and 83 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Supply_2019 +Summary_Supply_2020_17sch } \description{ -Summary 2019 Supply (2012 schema) +Summary 2020 Supply (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Supply_2021_17sch.Rd b/man/Summary_Supply_2021_17sch.Rd new file mode 100644 index 00000000..0cd22d1b --- /dev/null +++ b/man/Summary_Supply_2021_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Supply_2021_17sch} +\alias{Summary_Supply_2021_17sch} +\title{Summary 2021 Supply (2017 schema)} +\format{ +A dataframe with 74 obs. and 83 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +} +\usage{ +Summary_Supply_2021_17sch +} +\description{ +Summary 2021 Supply (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Supply_2022_17sch.Rd b/man/Summary_Supply_2022_17sch.Rd new file mode 100644 index 00000000..10987aaf --- /dev/null +++ b/man/Summary_Supply_2022_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Supply_2022_17sch} +\alias{Summary_Supply_2022_17sch} +\title{Summary 2022 Supply (2017 schema)} +\format{ +A dataframe with 74 obs. and 83 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +} +\usage{ +Summary_Supply_2022_17sch +} +\description{ +Summary 2022 Supply (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2017_PRO_AfterRedef_17sch.Rd b/man/Summary_Use_2017_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..af964775 --- /dev/null +++ b/man/Summary_Use_2017_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2017_PRO_AfterRedef_17sch} +\alias{Summary_Use_2017_PRO_AfterRedef_17sch} +\title{Summary 2017 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2017_PRO_AfterRedef_17sch +} +\description{ +Summary 2017 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2017_PRO_BeforeRedef_17sch.Rd b/man/Summary_Use_2017_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..be17d750 --- /dev/null +++ b/man/Summary_Use_2017_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2017_PRO_BeforeRedef_17sch} +\alias{Summary_Use_2017_PRO_BeforeRedef_17sch} +\title{Summary 2017 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2017_PRO_BeforeRedef_17sch +} +\description{ +Summary 2017 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2017_PUR_BeforeRedef_17sch.Rd b/man/Summary_Use_2017_PUR_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..4782ce3b --- /dev/null +++ b/man/Summary_Use_2017_PUR_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2017_PUR_BeforeRedef_17sch} +\alias{Summary_Use_2017_PUR_BeforeRedef_17sch} +\title{Summary 2017 Use Purchaser's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 76 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2017_PUR_BeforeRedef_17sch +} +\description{ +Summary 2017 Use Purchaser's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2018_PRO_AfterRedef_17sch.Rd b/man/Summary_Use_2018_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..9eb95a02 --- /dev/null +++ b/man/Summary_Use_2018_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2018_PRO_AfterRedef_17sch} +\alias{Summary_Use_2018_PRO_AfterRedef_17sch} +\title{Summary 2018 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2018_PRO_AfterRedef_17sch +} +\description{ +Summary 2018 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2018_PRO_BeforeRedef_17sch.Rd b/man/Summary_Use_2018_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..0944d660 --- /dev/null +++ b/man/Summary_Use_2018_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2018_PRO_BeforeRedef_17sch} +\alias{Summary_Use_2018_PRO_BeforeRedef_17sch} +\title{Summary 2018 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2018_PRO_BeforeRedef_17sch +} +\description{ +Summary 2018 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2019_PRO_AfterRedef_17sch.Rd b/man/Summary_Use_2019_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..d971ca0a --- /dev/null +++ b/man/Summary_Use_2019_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2019_PRO_AfterRedef_17sch} +\alias{Summary_Use_2019_PRO_AfterRedef_17sch} +\title{Summary 2019 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2019_PRO_AfterRedef_17sch +} +\description{ +Summary 2019 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2019_PRO_BeforeRedef_17sch.Rd b/man/Summary_Use_2019_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..34ac44f7 --- /dev/null +++ b/man/Summary_Use_2019_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2019_PRO_BeforeRedef_17sch} +\alias{Summary_Use_2019_PRO_BeforeRedef_17sch} +\title{Summary 2019 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2019_PRO_BeforeRedef_17sch +} +\description{ +Summary 2019 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2020_PRO_AfterRedef_17sch.Rd b/man/Summary_Use_2020_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..913f3c61 --- /dev/null +++ b/man/Summary_Use_2020_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2020_PRO_AfterRedef_17sch} +\alias{Summary_Use_2020_PRO_AfterRedef_17sch} +\title{Summary 2020 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2020_PRO_AfterRedef_17sch +} +\description{ +Summary 2020 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2020_PRO_BeforeRedef_17sch.Rd b/man/Summary_Use_2020_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..dc23d94e --- /dev/null +++ b/man/Summary_Use_2020_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2020_PRO_BeforeRedef_17sch} +\alias{Summary_Use_2020_PRO_BeforeRedef_17sch} +\title{Summary 2020 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2020_PRO_BeforeRedef_17sch +} +\description{ +Summary 2020 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2021_PRO_AfterRedef_17sch.Rd b/man/Summary_Use_2021_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..b57ca85a --- /dev/null +++ b/man/Summary_Use_2021_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2021_PRO_AfterRedef_17sch} +\alias{Summary_Use_2021_PRO_AfterRedef_17sch} +\title{Summary 2021 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2021_PRO_AfterRedef_17sch +} +\description{ +Summary 2021 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2021_PRO_BeforeRedef_17sch.Rd b/man/Summary_Use_2021_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..c7b2da89 --- /dev/null +++ b/man/Summary_Use_2021_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2021_PRO_BeforeRedef_17sch} +\alias{Summary_Use_2021_PRO_BeforeRedef_17sch} +\title{Summary 2021 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2021_PRO_BeforeRedef_17sch +} +\description{ +Summary 2021 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2022_PRO_AfterRedef_17sch.Rd b/man/Summary_Use_2022_PRO_AfterRedef_17sch.Rd new file mode 100644 index 00000000..d07d663b --- /dev/null +++ b/man/Summary_Use_2022_PRO_AfterRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2022_PRO_AfterRedef_17sch} +\alias{Summary_Use_2022_PRO_AfterRedef_17sch} +\title{Summary 2022 Use Producer's Value After Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2022_PRO_AfterRedef_17sch +} +\description{ +Summary 2022 Use Producer's Value After Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_2022_PRO_BeforeRedef_17sch.Rd b/man/Summary_Use_2022_PRO_BeforeRedef_17sch.Rd new file mode 100644 index 00000000..80283784 --- /dev/null +++ b/man/Summary_Use_2022_PRO_BeforeRedef_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_2022_PRO_BeforeRedef_17sch} +\alias{Summary_Use_2022_PRO_BeforeRedef_17sch} +\title{Summary 2022 Use Producer's Value Before Redefinition (2017 schema)} +\format{ +A dataframe with 79 obs. and 94 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_Use_2022_PRO_BeforeRedef_17sch +} +\description{ +Summary 2022 Use Producer's Value Before Redefinition (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_SUT_2017.Rd b/man/Summary_Use_SUT_2017_17sch.Rd similarity index 64% rename from man/Summary_Use_SUT_2017.Rd rename to man/Summary_Use_SUT_2017_17sch.Rd index f4ae9ad7..15827e2f 100644 --- a/man/Summary_Use_SUT_2017.Rd +++ b/man/Summary_Use_SUT_2017_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Use_SUT_2017} -\alias{Summary_Use_SUT_2017} -\title{Summary 2017 Use (2012 schema)} +\name{Summary_Use_SUT_2017_17sch} +\alias{Summary_Use_SUT_2017_17sch} +\title{Summary 2017 Use (2017 schema)} \format{ A dataframe with 82 obs. and 92 variables } @@ -11,9 +11,9 @@ A dataframe with 82 obs. and 92 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Use_SUT_2017 +Summary_Use_SUT_2017_17sch } \description{ -Summary 2017 Use (2012 schema) +Summary 2017 Use (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Use_SUT_2018.Rd b/man/Summary_Use_SUT_2018_17sch.Rd similarity index 64% rename from man/Summary_Use_SUT_2018.Rd rename to man/Summary_Use_SUT_2018_17sch.Rd index 4b9aedbe..2254b711 100644 --- a/man/Summary_Use_SUT_2018.Rd +++ b/man/Summary_Use_SUT_2018_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Use_SUT_2018} -\alias{Summary_Use_SUT_2018} -\title{Summary 2018 Use (2012 schema)} +\name{Summary_Use_SUT_2018_17sch} +\alias{Summary_Use_SUT_2018_17sch} +\title{Summary 2018 Use (2017 schema)} \format{ A dataframe with 82 obs. and 92 variables } @@ -11,9 +11,9 @@ A dataframe with 82 obs. and 92 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Use_SUT_2018 +Summary_Use_SUT_2018_17sch } \description{ -Summary 2018 Use (2012 schema) +Summary 2018 Use (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Use_SUT_2019.Rd b/man/Summary_Use_SUT_2019_17sch.Rd similarity index 64% rename from man/Summary_Use_SUT_2019.Rd rename to man/Summary_Use_SUT_2019_17sch.Rd index 34ae960c..ffa6e8ed 100644 --- a/man/Summary_Use_SUT_2019.Rd +++ b/man/Summary_Use_SUT_2019_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Use_SUT_2019} -\alias{Summary_Use_SUT_2019} -\title{Summary 2019 Use (2012 schema)} +\name{Summary_Use_SUT_2019_17sch} +\alias{Summary_Use_SUT_2019_17sch} +\title{Summary 2019 Use (2017 schema)} \format{ A dataframe with 82 obs. and 92 variables } @@ -11,9 +11,9 @@ A dataframe with 82 obs. and 92 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Use_SUT_2019 +Summary_Use_SUT_2019_17sch } \description{ -Summary 2019 Use (2012 schema) +Summary 2019 Use (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Use_SUT_2020.Rd b/man/Summary_Use_SUT_2020_17sch.Rd similarity index 64% rename from man/Summary_Use_SUT_2020.Rd rename to man/Summary_Use_SUT_2020_17sch.Rd index ba86687d..87b65972 100644 --- a/man/Summary_Use_SUT_2020.Rd +++ b/man/Summary_Use_SUT_2020_17sch.Rd @@ -1,9 +1,9 @@ % Generated by roxygen2: do not edit by hand % Please edit documentation in R/DataDocumentation.R \docType{data} -\name{Summary_Use_SUT_2020} -\alias{Summary_Use_SUT_2020} -\title{Summary 2020 Use (2012 schema)} +\name{Summary_Use_SUT_2020_17sch} +\alias{Summary_Use_SUT_2020_17sch} +\title{Summary 2020 Use (2017 schema)} \format{ A dataframe with 82 obs. and 92 variables } @@ -11,9 +11,9 @@ A dataframe with 82 obs. and 92 variables \url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} } \usage{ -Summary_Use_SUT_2020 +Summary_Use_SUT_2020_17sch } \description{ -Summary 2020 Use (2012 schema) +Summary 2020 Use (2017 schema) } \keyword{datasets} diff --git a/man/Summary_Use_SUT_2021_17sch.Rd b/man/Summary_Use_SUT_2021_17sch.Rd new file mode 100644 index 00000000..f75db70c --- /dev/null +++ b/man/Summary_Use_SUT_2021_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_SUT_2021_17sch} +\alias{Summary_Use_SUT_2021_17sch} +\title{Summary 2021 Use (2017 schema)} +\format{ +A dataframe with 82 obs. and 92 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +} +\usage{ +Summary_Use_SUT_2021_17sch +} +\description{ +Summary 2021 Use (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_Use_SUT_2022_17sch.Rd b/man/Summary_Use_SUT_2022_17sch.Rd new file mode 100644 index 00000000..df72db9d --- /dev/null +++ b/man/Summary_Use_SUT_2022_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_Use_SUT_2022_17sch} +\alias{Summary_Use_SUT_2022_17sch} +\title{Summary 2022 Use (2017 schema)} +\format{ +A dataframe with 82 obs. and 92 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesSUP.zip} +} +\usage{ +Summary_Use_SUT_2022_17sch +} +\description{ +Summary 2022 Use (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_ValueAddedCodeName_2017.Rd b/man/Summary_ValueAddedCodeName_2017.Rd new file mode 100644 index 00000000..6c025b03 --- /dev/null +++ b/man/Summary_ValueAddedCodeName_2017.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_ValueAddedCodeName_2017} +\alias{Summary_ValueAddedCodeName_2017} +\title{Summary Value Added Code and Name (2017 schema)} +\format{ +A dataframe with 3 obs. and 2 variables +} +\source{ +\url{https://apps.bea.gov/industry/iTables\%20Static\%20Files/AllTablesIO.zip} +} +\usage{ +Summary_ValueAddedCodeName_2017 +} +\description{ +Summary Value Added Code and Name (2017 schema) +} +\keyword{datasets} diff --git a/man/Summary_ValueAdded_IO_17sch.Rd b/man/Summary_ValueAdded_IO_17sch.Rd new file mode 100644 index 00000000..9da07c3d --- /dev/null +++ b/man/Summary_ValueAdded_IO_17sch.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/DataDocumentation.R +\docType{data} +\name{Summary_ValueAdded_IO_17sch} +\alias{Summary_ValueAdded_IO_17sch} +\title{Summary 2017-2022 Value Added (2017 schema)} +\format{ +A dataframe with 71 obs. and 6 variables +} +\source{ +\url{https://apps.bea.gov/industry/Release/ZIP/UGdpByInd.zip} +} +\usage{ +Summary_ValueAdded_IO_17sch +} +\description{ +Summary 2017-2022 Value Added (2017 schema) +} +\keyword{datasets} diff --git a/man/downloadNAICS2to6DigitsFile.Rd b/man/downloadNAICS2to6DigitsFile.Rd new file mode 100644 index 00000000..50c2d801 --- /dev/null +++ b/man/downloadNAICS2to6DigitsFile.Rd @@ -0,0 +1,17 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/CrosswalkFunctions.R +\name{downloadNAICS2to6DigitsFile} +\alias{downloadNAICS2to6DigitsFile} +\title{Download NAICS file for 2-6 digit NAICS codes if not present.} +\usage{ +downloadNAICS2to6DigitsFile(year) +} +\arguments{ +\item{year}{int, 2017, 2012, or 2007 accepted.} +} +\value{ +FileName str +} +\description{ +Download NAICS file for 2-6 digit NAICS codes if not present. +} diff --git a/man/getModelCrosswalk.Rd b/man/getModelCrosswalk.Rd new file mode 100644 index 00000000..9c629813 --- /dev/null +++ b/man/getModelCrosswalk.Rd @@ -0,0 +1,17 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/InitializeModel.R +\name{getModelCrosswalk} +\alias{getModelCrosswalk} +\title{Get model crosswalk based on BaseIOSchema and BaseIOLevel} +\usage{ +getModelCrosswalk(model) +} +\arguments{ +\item{model}{EEIO model with specs assigned} +} +\value{ +crosswalk as dataframe +} +\description{ +Get model crosswalk based on BaseIOSchema and BaseIOLevel +} diff --git a/man/getNAICS2to6Digits.Rd b/man/getNAICS2to6Digits.Rd index 90470a5d..fd037e96 100644 --- a/man/getNAICS2to6Digits.Rd +++ b/man/getNAICS2to6Digits.Rd @@ -7,7 +7,7 @@ getNAICS2to6Digits(year) } \arguments{ -\item{year}{int, 2012 or 2007 accepted.} +\item{year}{int, 2017, 2012 or 2007 accepted.} } \value{ data frame with columns NAICS_2, NAICS_3, NAICS_4, NAICS_5, NAICS_6. diff --git a/man/getNAICS2to6DigitsCodeName.Rd b/man/getNAICS2to6DigitsCodeName.Rd index 57ffde33..87decc1b 100644 --- a/man/getNAICS2to6DigitsCodeName.Rd +++ b/man/getNAICS2to6DigitsCodeName.Rd @@ -7,7 +7,7 @@ getNAICS2to6DigitsCodeName(year) } \arguments{ -\item{year}{int. 2012 or 2007 accepted.} +\item{year}{int. 2017, 2012, or 2007 accepted.} } \value{ dataframe with columns NAICS_year_Code and NAICS_year_Name. diff --git a/man/getSchemaCode.Rd b/man/getSchemaCode.Rd new file mode 100644 index 00000000..2f6de7d1 --- /dev/null +++ b/man/getSchemaCode.Rd @@ -0,0 +1,17 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/UtilityFunctions.R +\name{getSchemaCode} +\alias{getSchemaCode} +\title{Return the schema subscript for accessing useeior objects} +\usage{ +getSchemaCode(specs) +} +\arguments{ +\item{specs}{list of model specs must include BaseIOSchema} +} +\value{ +schema, str in form "YYsch" or NULL for 2012 +} +\description{ +Return the schema subscript for accessing useeior objects +} diff --git a/man/loadMasterCrosswalk.Rd b/man/loadMasterCrosswalk.Rd deleted file mode 100644 index 9e8a241c..00000000 --- a/man/loadMasterCrosswalk.Rd +++ /dev/null @@ -1,14 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/CrosswalkFunctions.R -\name{loadMasterCrosswalk} -\alias{loadMasterCrosswalk} -\title{Function to externalize the BEA to NAICS crosswalk} -\usage{ -loadMasterCrosswalk() -} -\value{ -A crosswalk linking 2007 and 2012 NAICS codes to 2012 Sector, Summary, and Detail BEA codes -} -\description{ -Function to externalize the BEA to NAICS crosswalk -} diff --git a/tests/modelspecs/USEEIOv3.0-GHG.yml b/tests/modelspecs/USEEIOv3.0-GHG.yml new file mode 100644 index 00000000..ab921ab9 --- /dev/null +++ b/tests/modelspecs/USEEIOv3.0-GHG.yml @@ -0,0 +1,61 @@ +Model: "USEEIOv3.0-GHG" # 2017 Detail, Commodity +BaseIOSchema: 2017 +BaseIOLevel: "Detail" +IOYear: 2017 # Year for IO data +ModelRegionAcronyms: ["US"] +ModelType: "EEIO" +IODataSource: "BEA" +BasePriceType: "PRO" #producer +BasewithRedefinitions: FALSE +CommodityorIndustryType: "Commodity" +ScrapIncluded: FALSE +DisaggregationSpecs: null + +SatelliteTable: + GHG: + FullName: "Greenhouse Gases" + Abbreviation: "GHG" + StaticSource: TRUE + StaticFile: "flowsa/FlowBySector/GHG_national_2020_m2_v2.0.1_1d3a514.parquet" + FileLocation: "DataCommons" + DataYears: [2020] + Locations: ["US"] + SectorListSource: "NAICS" + SectorListYear: 2012 + SectorListLevel: "6" + OriginalFlowSource: "FEDEFLv1.1.0" + ScriptFunctionCall: "getFlowbySectorCollapsed" #function to call for script + ScriptFunctionParameters: null + DataSources: + USEPA_GHG_2022: + Title: "GHG Inventory" + Author: "USEPA" + DataYear: 2020 + URL: "https://www.epa.gov/ghgemissions/inventory-us-greenhouse-gas-emissions-and-sinks-1990-2020" + Primary: TRUE + +Indicators: + GreenhouseGases: + Name: "Greenhouse Gases" + Code: "GHG" + Group: "Impact Potential" + Unit: "kg CO2 eq" + SimpleUnit: "Kilograms Carbon Dioxide (CO2)" + SimpleName: "Greenhouse Gases" + StaticSource: TRUE + StaticFile: "lciafmt/traci/TRACI_2.1_v1.0.0_5555779.parquet" + FileLocation: "DataCommons" + ScriptFunctionCall: "getImpactMethod" #function to call for script + ScriptFunctionParameters: + indicators: ["Global warming"] + DataSources: + USEPA_TRACI_2.1: + Title: "TRACI 2.1" + Author: "USEPA" + DataYear: NA + URL: "https://www.epa.gov/chemical-research/tool-reduction-and-assessment-chemicals-and-other-environmental-impacts-traci" + Primary: TRUE + +DemandVectors: + DefaultDemand: "DefaultDemandVectors" # Name of default demand vectors yml file +# Additional demand vectors beyond useeior defaults diff --git a/tests/test_model_build.R b/tests/test_model_build.R index f89a513e..c2ac46c4 100644 --- a/tests/test_model_build.R +++ b/tests/test_model_build.R @@ -22,6 +22,24 @@ model <- useeior:::loadDemandVectors(model) model <- useeior:::constructEEIOMatrices(model) printValidationResults(model) +## USEEIOv3.0-GHG Detail, commodity model (2017 Schema) +m <- "USEEIOv3.0-GHG" +cfg <- paste0("modelspecs/", m, ".yml") +model <- buildModel(m, configpaths = file.path(cfg)) +printValidationResults(model) + +## USEEIOv3.0-s-GHG Summary, commodity model (2017 Schema) +model <- useeior:::initializeModel(m, configpaths = file.path(cfg)) +model$specs$Model <- "USEEIOv3.0-s-GHG" +model$specs$BaseIOLevel <- "Summary" +model$crosswalk <- useeior:::getModelCrosswalk(model) # reassign for summary model +model <- useeior:::loadIOData(model) +model <- useeior:::loadandbuildSatelliteTables(model) +model <- useeior:::loadandbuildIndicators(model) +model <- useeior:::loadDemandVectors(model) +model <- useeior:::constructEEIOMatrices(model) +printValidationResults(model) + ## USEEIOv2 - integrated hybrid m <- "USEEIOv2.0-GHG-NGCombustion" cfg <- c(paste0("modelspecs/", m, ".yml"),