Investigating...

Added VEH1060 data, added some investigation, changed to latest available year of final data that I could manage to download.

R/carmatch.R

@@ -1,5 +1,5 @@
 # single place for functions (for now)
-cm_get = function(u = "https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-18/co2-emissions-cars-2017-provisional/co2_passengers_cars_v15_csv/at_download/file", dir = tempdir()) {
+cm_get = function(u = "https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-18/co2-emissions-cars-2017-final/co2_passengers_cars_v16_csv.zip/at_download/file", dir = tempdir()) {
   f = file.path(dir, "co2.zip")
   dd = file.path(dir, "co2")
 if(!file.exists(f)) {
@@ -79,6 +79,36 @@ d_raw = cm_get()
 system.time(saveRDS(d_raw, "d_raw_euco2.Rds"))
 # 35s on fast computer! 40 MB
 
-summary(as.factor(d_raw$Fuel_type))
+library(readxl)
+sheet1 <- read_excel("veh0160.xlsx", sheet = 1)
+rownumber <- which(sheet1$`Department for Transport statistics` == "Make")
+headers <- as.list(sheet1[rownumber,])
+sheet1 <- sheet1[-c(1:(rownumber)),]
+colnames(sheet1) <- headers
+rm(headers)
+rownumber <- which(sheet1$Make == "1. Entries containing \"MISSING\" or \"UNKNOWN MODEL\" are either for vehicles that have never been allocated a model code (most likely older vehicles manufactured before 1972) or new vehicles when the code lookup has not yet been published.")
+sheet1 <- sheet1[-c(rownumber:nrow(sheet1)),]
+sheet1 <- subset(sheet1, !(is.na(sheet1$Make)))
 
+sheet1$UK2017 <- as.numeric(sheet1$`2017 Q1 UK`) +
+                 as.numeric(sheet1$`2017 Q2 UK`) +
+                 as.numeric(sheet1$`2017 Q3 UK`) +
+                 as.numeric(sheet1$`2017 Q4 UK`)
 
+UK2017 <- as.data.frame(cbind(sheet1$Make, sheet1$`Model 1`, sheet1$UK2017))
+colnames(UK2017) <- c("Make", "DVLAModel", "2017 Registrations")
+UK2017 <- subset(UK2017, !is.na(UK2017$`2017 Registrations`))
+
+EU_GB <- subset(d_raw, d_raw$Country == "GB")
+
+library(tidyverse)
+EU_data_summary <- EU_GB %>% group_by(Manufacturer_name_MS,Commercial_name, NEDC_CO2, Mass_kg, Wheelbase, SteeringAxle, OtherAxle, Fuel_type, Engine_capacity) %>% dplyr::summarise("freq in EU data for UK" = n())
+
+EU_data_summary$Commercial_name_in_VEH0160_2017 <- NA
+EU_data_summary$Commercial_name_in_VEH0160 <- NA
+UK2017$MakeModel <- paste0(UK2017$Make, " ", UK2017$DVLAModel)
+EU_data_summary$MakeModel <- paste0(EU_data_summary$Manufacturer_name_MS, " ", EU_data_summary$Commercial_name)
+sheet1$MakeModel <- paste0(sheet1$Make, " ", sheet1$`Model 1`)
+
+EU_data_summary$Commercial_name_in_VEH0160_2017[EU_data_summary$MakeModel %in% UK2017$MakeModel] <- TRUE
+EU_data_summary$Commercial_name_in_VEH0160[EU_data_summary$MakeModel %in% sheet1$MakeModel] <- TRUE