Adult employment rate.R

# Code generated with eurodata_codegen on 2024-09-18 16:26:27 (UTC+2:00, Central European Summer Time)
library(magrittr)
library(data.table)
library(eurodata)
library(openxlsx2)

dt__lfsi_emp_a <-
  ## Link to filtered raw data (TSV):
  # https://ec.europa.eu/eurostat/api/dissemination/sdmx/2.1/data/LFSI_EMP_A/.EMP_LFS.T.Y20-64.PC_POP.EU27_2020?format=TSV 
  ## Meaning of the codes in `filters` below:
  # age=Y20-64 -- Age class = From 20 to 64 years
  # geo=EU27_2020 -- Geopolitical entity (reporting) = European Union - 27 countries (from 2020)
  # indic_em=EMP_LFS -- Employment indicator = Total employment (resident population concept - LFS)
  # sex=T -- Sex = Total
  # unit=PC_POP -- Unit of measure = Percentage of total population
  ## Warning: importData() below may return an empty data.frame (with 0 observations)
  ## if the application of `filters` results in no available data!
  importData("lfsi_emp_a", # Employment and activity by sex and age - annual data
             filters = list(age = c("Y20-64"),
                            geo = c("EU27_2020"),
                            indic_em = c("EMP_LFS"),
                            sex = c("T"),
                            TIME_PERIOD = c(""),
                            unit = c("PC_POP"))) %>%
  `if`(nrow(.)==0,stop("\n",deparse1(substitute(.)),"\nreturned empty data.frame!",call.=FALSE),.) %>%
  as.data.table() %>%
  .[!is.na(value_)] %>%
  .[, freq := NULL] %>% # not needed
  .[, value_ := as.numeric(value_)] %>%
  .[, flags_ := NULL] %>% # flags not needed
  .[, TIME_PERIOD := TIME_PERIOD %>% as.character %>% as.integer] %>% 
  dcast(geo + TIME_PERIOD ~ age + indic_em + sex + unit,
        fun.aggregate=identity, value.var="value_",
        fill=NA_real_, sep=" ")

dt__OECD.ELS.SAE <-
  fread(paste0('https://sdmx.oecd.org/public/rest/data/OECD.ELS.SAE,DSD_LFS@DF_LFS_INDIC,',
               '/GBR+USA+JPN.EMP_RATIO.PT_POP_SUB._T.Y20T64.EMP',
               '?startPeriod=2010&dimensionAtObservation=AllDimensions&format=csvfilewithlabels')) %>% 
  .[, TIME_PERIOD := TIME_PERIOD %>% as.character %>% as.integer] %>% 
  dcast(REF_AREA + TIME_PERIOD ~ AGE + MEASURE + LABOUR_FORCE_STATUS + SEX + UNIT_MEASURE,
        fun.aggregate=identity, value.var="OBS_VALUE",
        fill=NA_real_, sep=" ")

EU_data <-
  dt__lfsi_emp_a %>% 
  copy %>% 
  setnames(colnames(.) %>% setdiff(c('geo','TIME_PERIOD')),
           'EU') %>% 
  .[, geo := NULL]

Other_data <-
  dt__OECD.ELS.SAE %>% 
  copy %>% 
  setnames(colnames(.) %>% setdiff(c('REF_AREA','TIME_PERIOD')),
           'value_') %>% 
  dcast(TIME_PERIOD ~ REF_AREA,
        fun.aggregate=identity, value.var="value_",
        fill=NA_real_, sep=" ")

Final_table<-
  merge(EU_data, Other_data, by='TIME_PERIOD') %>% 
  .[, EU_2030_Target := 78] %T>% 
  write_xlsx('Adult employment rate.xlsx')

shell('open "Adult employment rate.xlsx"')