live download + unzip

.gitignore

@@ -9,5 +9,4 @@ _bookdown_files/
 _main_files
 .DS_Store
 docs/
-dataset/epa/daily_88101_2021.csv
 dataset/narr/air.2m_2021.nc

chapters/01-02-spatial-point-data.Rmd

@@ -67,7 +67,7 @@ unzip(
 
 After inspecting the file size, unzip `epa_data.zip`.
 
-```{r, eval = FALSE}
+```{r, eval = TRUE}
 unzip(
   "./dataset/epa/epa_data.zip",
   exdir = "./dataset/epa/"
@@ -80,32 +80,19 @@ Inspecting the file with `utils::unzip(list = TRUE)` returned the size of the fi
 Multiple chunks of code in this tutorial will contain `./dataset/`, a fixed directory path to run the tutorial code. To run the code on your machine, substitute `./dataset/` with the file path where you would like to store the tutorial data.
 :::
 
-```{r, eval = FALSE}
+```{r}
 list.files("./dataset/epa")
 ```
-```{r, echo = FALSE, include = FALSE}
-cat("[1] \"daily_88101_2021.csv\" \"epa_data.zip\"")
-```
 
 ## Data Preparation
 
 ### Import
 
 Now that the contents of the zip file have been saved on your machine and the data file of interest has been identified, import the data with `sf::st_read()`.
 
-```{r, eval = FALSE}
+```{r}
 pm <- sf::st_read("./dataset/epa/daily_88101_2021.csv")
 ```
-```{r, echo = FALSE, include = FALSE}
-pm <- readRDS("./dataset/epa/daily_sf.rds")
-```
-```{r, echo = FALSE, include = FALSE}
-cat("Reading layer `daily_88101_2021' from data source 
-  `/Users/manwareme/Documents/bookdown/niehs/PCOR_bookdown_tools/dataset/epa/daily_88101_2021.csv' 
-  using driver `CSV'
-Warning message:
-no simple feature geometries present: returning a data.frame or tbl_df ")
-```
 
 The previous chunk of code returned a `Warning:` message. This warning informs the user that the imported data does not have native spatial features, so the data was imported as a `data.frame`.
 

chapters/01-04-spatial-raster-data.Rmd

@@ -47,7 +47,7 @@ The `utils::download.file()` function downloads the file according to the define
 Multiple chunks of code in this tutorial will contain `./dataset/`, a fixed directory path to run the tutorial code. To run the code on your machine, substitute `./dataset/` with the file path where you would like to store the tutorial data.
 :::
 
-```{r, eval = FALSE}
+```{r, eval = TRUE}
 # specify the URL where data is stored based on year variable of interest
 url_narr <- paste0(
   "https://downloads.psl.noaa.gov//Datasets/NARR/Dailies/monolevel/air.2m.",
@@ -72,11 +72,7 @@ download.file(
 Identify the desired data file with `utils::list.files()`
 
 ```{r, eval = FALSE}
-list.files("./dataset/narr/")
-```
-
-```{r, echo = FALSE, include = FALSE}
-cat("[1] \"air_2m.2021.nc\"")
+list.files("./dataset/narr")
 ```
 
 The file downloaded from NOAA's NARR data set is an `.nc`, or netCDF, file. NetCDF files are common for raster data, and do not need to be unzipped.
@@ -87,14 +83,10 @@ The file downloaded from NOAA's NARR data set is an `.nc`, or netCDF, file. NetC
 
 Now that the data file of interest has been downloaded and identified, import the data with `terra::rast()`.
 
-```{r, eval = FALSE}
+```{r}
 narr <- terra::rast("./dataset/narr/air.2m_2021.nc")
 ```
 
-```{r, echo = FALSE, include = FALSE}
-narr <- readRDS("./dataset/narr/air.2m_2021.rds")
-```
-
 ### Inspect Structure
 
 Inspect the structure of `narr` to see its class, dimensions, variables, and layer names.