inst/doc/recode.R

In regions: Processing Regional Statistics

## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup, message=FALSE, warnings=FALSE, echo=FALSE-------------------------
library(regions)
library(dplyr)
library(tidyr)

## ----changes, results='asis'--------------------------------------------------
data(nuts_changes)

nuts_changes %>%
  mutate ( geo_16 = .data$code_2016, 
           geo_13 = .data$code_2013 ) %>%
  filter ( code_2016 %in% c("FRB", "HU11") | 
             code_2013 %in% c("FR7", "HU10", "FR24")) %>%
  select ( all_of(c("typology", "geo_16", "geo_13", "start_year",
           "code_2013", "change_2013",
           "code_2016", "change_2016")) 
           ) %>%
  pivot_longer ( cols = starts_with("code"), 
                 names_to = 'definition', 
                 values_to = 'code') %>%
  pivot_longer ( cols = starts_with("change"), 
                 names_to = 'change', 
                 values_to = 'description')  %>%
  filter (!is.na(.data$description), 
          !is.na(.data$code)) %>%
  select ( -.data$change ) %>%
  knitr::kable ()

## ----recode, results='asis'---------------------------------------------------
example_df <- data.frame ( 
  geo  =  c("FR", "DEE32", "UKI3" ,
            "HU12", "DED", 
            "FRK"), 
  values = runif(6, 0, 100 ),
  stringsAsFactors = FALSE )

recode_nuts(dat = example_df, 
            nuts_year = 2013) %>%
  select ( geo, values, code_2013) %>%
  knitr::kable()

## ----recode2013, results='asis'-----------------------------------------------
recode_nuts(example_df, nuts_year = 2013) %>%
  select ( all_of(c("geo", "values", "typology_change", "code_2013")) ) %>%
  knitr::kable()

## ----changes2013, results='asis'----------------------------------------------
recode_nuts(example_df, nuts_year = 2013) %>%
  select ( .data$code_2013, .data$values, .data$typology_change ) %>%
  rename ( geo = .data$code_2013 ) %>% 
  filter ( !is.na(.data$geo) ) %>%
  knitr::kable()

## ----recode2021, results='asis'-----------------------------------------------
recode_nuts(example_df, nuts_year = 2021) %>%
  select ( .data$code_2021, .data$values, .data$typology_change ) %>%
  rename ( geo = .data$code_2021 ) %>% 
  filter ( !is.na(.data$geo) ) %>%
  knitr::kable()

## ----recodeHU12, results='asis'-----------------------------------------------
data(nuts_changes) 
nuts_changes %>% 
  select( .data$code_2016, .data$geo_name_2016, .data$change_2016) %>%
  filter( code_2016 == "HU12") %>%
  filter( complete.cases(.) ) %>%
  knitr::kable()

## ----citation-regions, message=FALSE, eval=TRUE, echo=TRUE--------------------
citation("regions")