R/valmyndigheten_get.R
In Elmahi92/apivalm: API connection package
Defines functions
valmyndigheten_get
Documented in
valmyndigheten_get
library(tidyverse)
library(httr)
library(readxl)
urls <- c("https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_R.xls",
"https://data.val.se/val/val2014/statistik/2014_riksdagsval_per_kommun.xls",
"https://data.val.se/val/val2018/statistik/2018_R_per_kommun.xlsx",
"https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_L.xls",
"https://data.val.se/val/val2014/statistik/2014_landstingsval_per_kommun.xls",
"https://data.val.se/val/val2018/statistik/2018_L_per_kommun.xlsx",
"https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_K_antal.xls",
"https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_K_procent.xls",
"https://data.val.se/val/val2014/statistik/2014_kommunval_per_kommun.xlsx",
"https://data.val.se/val/val2018/statistik/2018_K_per_kommun.xlsx")
#' Get data from Valmyndigheten
#'
#' @title valmyndigheten_get
#' @param years A numeric vector of years (2010, 2014 and/or 2018)
#' @param election_types A character vector of election types ("riksdag", "county" and/or "municipality")
#' @return A tibble of elections matching the specificed \code{year} and \code{election_type}
#' @examples
#' valmyndigheten_get(c(2010), c("riksdag"))
#' valmyndigheten_get(c(2010, 2014, 2018), c("riksdag", "county", "municipal"))
#' @import httr readxl tidyverse
#' @export
#'
valmyndigheten_get <- function(years, election_types) {
if(!all(years %in% c(2010, 2014, 2018))) stop("Incorrect year! Data is only available for 2010, 2014 and 2018.")
if(!all(election_types %in% c("riksdag", "county", "municipal"))) stop("Incorrect election type! Available election types are riksdag, county and municipal.")
df <- tibble(`Year` = numeric(),
`Election type` = character(),
`County code` = numeric(),
`Municipality code` = numeric(),
`County` = character(),
`Municipality` = character(),
`M no` = numeric(),
`M pct` = numeric(),
`C no` = numeric(),
`C pct` = numeric(),
`L no` = numeric(),
`L pct` = numeric(),
`KD no` = numeric(),
`KD pct` = numeric(),
`S no` = numeric(),
`S pct` = numeric(),
`V no` = numeric(),
`V pct` = numeric(),
`MP no` = numeric(),
`MP pct` = numeric(),
`SD no` = numeric(),
`SD pct` = numeric(),
`FI no` = numeric(),
`FI pct` = numeric(),
`Other no` = numeric(),
`Other pct` = numeric(),
`Blank no` = numeric(),
`Blank pct` = numeric(),
`Invalid no` = numeric(),
`Invalid pct` = numeric(),
`Valid votes` = numeric(),
`Votes cast` = numeric(),
`Registered voters` = numeric(),
`Turnout` = numeric())
#######################################
#### Riksdag (Sweden's parliament) ####
#######################################
if("riksdag" %in% election_types) {
## Riksdag, 2010 ##
if(2010 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[1],
write_disk(tempfile(fileext = strsplit(basename(urls[1]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other no` = rowSums(.[,c(23,25,27)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(24,26,28)], na.rm = TRUE)) %>%
select(-c(23:28)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = LAN, `Municipality code` = KOM, County = 'L\u00C4N', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`,
`Blank no` = `BL no`, `Blank pct` = `BL pct`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb, `Turnout` = VDT,
`Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "Riksdag", .before = "County code"))
}
## Riksdag, 2014 ##
if(2014 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[2],
write_disk(tempfile(fileext = strsplit(basename(urls[2]), split="\\.")[[1]][2])))$content, skip = 2) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = LAN, `Municipality code` = KOM, County = 'L\u00C4N', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Other no` = `OVR no`, `Other pct` = `OVR pct`,
`Blank no` = `BL no`, `Blank pct` = `BL pct`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb, `Turnout` = VDT,
`Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2014, .before = "County code") %>%
add_column(`Election type` = "Riksdag", .before = "County code"))
}
## Riksdag, 2018 ##
if(2018 %in% years) {
df <- bind_rows(df,
left_join(read_xlsx(GET(urls[3],
write_disk(tempfile(fileext = strsplit(basename(urls[3]), split="\\.")[[1]][2])))$content, sheet = "R antal") %>%
mutate(`Invalid no` = rowSums(.[,c(39,41)], na.rm = TRUE)) %>%
mutate(`Other no` = rowSums(.[,c(14:38)], na.rm = TRUE)) %>%
select(-c(14:39,41)) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:14)) %>%
add_column(`Year` = 2018, .before = "L\U00C4NSKOD") %>%
add_column(`Election type` = "Riksdag", .before = "L\U00C4NSKOD"),
read_xlsx(GET(urls[3],
write_disk(tempfile(fileext = strsplit(basename(urls[3]), split="\\.")[[1]][2])))$content, sheet = "R procent") %>%
mutate(`Invalid pct` = rowSums(.[,c(39,41)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(14:38)], na.rm = TRUE)) %>%
select(-c(14:39,41)) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:14)) %>%
add_column(`Year` = 2018, .before = "L\U00C4NSKOD") %>%
add_column(`Election type` = "Riksdag", .before = "L\U00C4NSKOD")) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\u00C4NSKOD', `Municipality code` = KOMMUNKOD, County = 'L\u00C4NSNAMN',
Municipality = KOMMUNNAMN, `Valid votes` = 'R\u00D6STER GILTIGA', `Votes cast` = 'R\u00D6STANDE',
`Registered voters` = 'R\u00D6STBER\u00C4TTIGADE', `Turnout` = VALDELTAGANDE,
`Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`))
}
}
########################
#### County Council ####
########################
if("county" %in% election_types) {
## County Council, 2010 ##
if(2010 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[4],
write_disk(tempfile(fileext = strsplit(basename(urls[4]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other no` = rowSums(.[,c(seq(21, 40, 2), seq(43, 92, 2))], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(seq(22, 40, 2), seq(44, 92, 2))], na.rm = TRUE)) %>%
select(-c(21:40, 43:92)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\U00C4N...1', `Municipality code` = KOM, County = 'L\U00C4N...3', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`,
`Valid votes` = `Rost Giltiga`, `Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "County council", .before = "County code"))
}
## County Council, 2014 ##
if(2014 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[5],
write_disk(tempfile(fileext = strsplit(basename(urls[5]), split="\\.")[[1]][2])))$content, skip = 2) %>%
mutate(`Other no` = rowSums(.[,seq(23, 112, 2)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,seq(24, 112, 2)], na.rm = TRUE)) %>%
select(-c(23:112)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\U00C4N...1', `Municipality code` = KOM, County = 'L\U00C4N...3', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`,
`Valid votes` = `Rost Giltiga`, `Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2014, .before = "County code") %>%
add_column(`Election type` = "County council", .before = "County code"))
}
## County Council, 2018 ##
if(2018 %in% years) {
df <- bind_rows(df,
left_join(read_xlsx(GET(urls[6],
write_disk(tempfile(fileext = strsplit(basename(urls[6]), split="\\.")[[1]][2])))$content, sheet = "L antal") %>%
mutate(`Invalid no` = rowSums(.[,c(53,55)], na.rm = TRUE)) %>%
mutate(`Other no` = rowSums(.[,c(14:52)], na.rm = TRUE)) %>%
select(-c(14:52,53,55)) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:14)),
read_xlsx(GET(urls[6],
write_disk(tempfile(fileext = strsplit(basename(urls[6]), split="\\.")[[1]][2])))$content, sheet = "L procent") %>%
mutate(`Invalid pct` = rowSums(.[,c(53,55)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(14:52)], na.rm = TRUE)) %>%
select(-c(14:52,53,55)) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:14))) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\u00C4NSKOD', `Municipality code` = KOMMUNKOD, County = 'L\u00C4NSNAMN',
Municipality = KOMMUNNAMN, `Valid votes` = 'R\u00D6STER GILTIGA', `Votes cast` = 'R\u00D6STANDE',
`Registered voters` = 'R\u00D6STBER\u00C4TTIGADE', `Turnout` = VALDELTAGANDE,
`Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`) %>%
add_column(`Year` = 2018, .before = "County code") %>%
add_column(`Election type` = "County council", .before = "County code"))
}
}
###########################
#### Municipal Council ####
###########################
if("municipal" %in% election_types) {
## Municipal Council, 2010 ##
if(2010 %in% years) {
df <- bind_rows(df,
left_join(read_xls(GET(urls[7],
write_disk(tempfile(fileext = strsplit(basename(urls[7]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other no` = rowSums(.[,c(13:96, 98:222)], na.rm = TRUE)) %>%
select(-c(13:96, 98:222)) %>%
rename(`County code` = 'L\U00C4N...1', `County` = 'L\U00C4N...3', `Municipality code` = `KOM...2`,
`Municipality` = `KOMMUN`, `Blank` = `BLANK`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid` = `OG`, `Invalid` = `OG`,
L = FP) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:15)) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code"),
read_xls(GET(urls[8],
write_disk(tempfile(fileext = strsplit(basename(urls[8]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other pct` = rowSums(.[,c(13:96, 98:222)], na.rm = TRUE)) %>%
select(-c(13:96, 98:222)) %>%
rename(`County code` = 'L\U00C4N...1', `County` = 'L\U00C4N...3', `Municipality code` = `KOM...2`,
`Municipality` = `KOMMUN`, `Blank` = `BLANK`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid` = `OG`, `Invalid` = `OG`,
L = FP) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:15)) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code")))
}
## Municipal Council, 2014 ##
if(2014 %in% years) {
df <- bind_rows(df,
read_xlsx(GET(urls[9],
write_disk(tempfile(fileext = strsplit(basename(urls[9]), split="\\.")[[1]][2])))$content, skip = 2) %>%
mutate(`Other no` = rowSums(.[,seq(23, 518, 2)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,seq(24, 518, 2)], na.rm = TRUE)) %>%
select(-c(23:518)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\U00C4N...1', `Municipality code` = KOM, County = 'L\U00C4N...3', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`,
`Valid votes` = `Rost Giltiga`, `Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2014, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code"))
}
## Municipal Council, 2018 ##
if(2018 %in% years) {
df <- bind_rows(df,
left_join(read_xlsx(GET(urls[10],
write_disk(tempfile(fileext = strsplit(basename(urls[10]), split="\\.")[[1]][2])))$content, sheet = "K antal") %>%
mutate(`Invalid no` = rowSums(.[,c(225,227)], na.rm = TRUE)) %>%
mutate(`Other no` = rowSums(.[,c(14:224)], na.rm = TRUE)) %>%
select(-c(14:224,225,227)) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:14)),
read_xlsx(GET(urls[10],
write_disk(tempfile(fileext = strsplit(basename(urls[10]), split="\\.")[[1]][2])))$content, sheet = "K procent") %>%
mutate(`Invalid pct` = rowSums(.[,c(225,227)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(14:224)], na.rm = TRUE)) %>%
select(-c(14:224,225,227)) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:14))) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\u00C4NSKOD', `Municipality code` = KOMMUNKOD, County = 'L\u00C4NSNAMN',
Municipality = KOMMUNNAMN, `Valid votes` = 'R\u00D6STER GILTIGA', `Votes cast` = 'R\u00D6STANDE',
`Registered voters` = 'R\u00D6STBER\u00C4TTIGADE', `Turnout` = VALDELTAGANDE,
`Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`) %>%
add_column(`Year` = 2018, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code"))
}
}
return(df)
}
Elmahi92/apivalm documentation built on Dec. 17, 2021, 6:27 p.m.
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Defines functions valmyndigheten_get
Documented in valmyndigheten_get
library(tidyverse)
library(httr)
library(readxl)
urls <- c("https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_R.xls",
"https://data.val.se/val/val2014/statistik/2014_riksdagsval_per_kommun.xls",
"https://data.val.se/val/val2018/statistik/2018_R_per_kommun.xlsx",
"https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_L.xls",
"https://data.val.se/val/val2014/statistik/2014_landstingsval_per_kommun.xls",
"https://data.val.se/val/val2018/statistik/2018_L_per_kommun.xlsx",
"https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_K_antal.xls",
"https://data.val.se/val/val2010/statistik/slutligt_valresultat_kommuner_K_procent.xls",
"https://data.val.se/val/val2014/statistik/2014_kommunval_per_kommun.xlsx",
"https://data.val.se/val/val2018/statistik/2018_K_per_kommun.xlsx")
#' Get data from Valmyndigheten
#'
#' @title valmyndigheten_get
#' @param years A numeric vector of years (2010, 2014 and/or 2018)
#' @param election_types A character vector of election types ("riksdag", "county" and/or "municipality")
#' @return A tibble of elections matching the specificed \code{year} and \code{election_type}
#' @examples
#' valmyndigheten_get(c(2010), c("riksdag"))
#' valmyndigheten_get(c(2010, 2014, 2018), c("riksdag", "county", "municipal"))
#' @import httr readxl tidyverse
#' @export
#'
valmyndigheten_get <- function(years, election_types) {
if(!all(years %in% c(2010, 2014, 2018))) stop("Incorrect year! Data is only available for 2010, 2014 and 2018.")
if(!all(election_types %in% c("riksdag", "county", "municipal"))) stop("Incorrect election type! Available election types are riksdag, county and municipal.")
df <- tibble(`Year` = numeric(),
`Election type` = character(),
`County code` = numeric(),
`Municipality code` = numeric(),
`County` = character(),
`Municipality` = character(),
`M no` = numeric(),
`M pct` = numeric(),
`C no` = numeric(),
`C pct` = numeric(),
`L no` = numeric(),
`L pct` = numeric(),
`KD no` = numeric(),
`KD pct` = numeric(),
`S no` = numeric(),
`S pct` = numeric(),
`V no` = numeric(),
`V pct` = numeric(),
`MP no` = numeric(),
`MP pct` = numeric(),
`SD no` = numeric(),
`SD pct` = numeric(),
`FI no` = numeric(),
`FI pct` = numeric(),
`Other no` = numeric(),
`Other pct` = numeric(),
`Blank no` = numeric(),
`Blank pct` = numeric(),
`Invalid no` = numeric(),
`Invalid pct` = numeric(),
`Valid votes` = numeric(),
`Votes cast` = numeric(),
`Registered voters` = numeric(),
`Turnout` = numeric())
#######################################
#### Riksdag (Sweden's parliament) ####
#######################################
if("riksdag" %in% election_types) {
## Riksdag, 2010 ##
if(2010 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[1],
write_disk(tempfile(fileext = strsplit(basename(urls[1]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other no` = rowSums(.[,c(23,25,27)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(24,26,28)], na.rm = TRUE)) %>%
select(-c(23:28)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = LAN, `Municipality code` = KOM, County = 'L\u00C4N', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`,
`Blank no` = `BL no`, `Blank pct` = `BL pct`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb, `Turnout` = VDT,
`Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "Riksdag", .before = "County code"))
}
## Riksdag, 2014 ##
if(2014 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[2],
write_disk(tempfile(fileext = strsplit(basename(urls[2]), split="\\.")[[1]][2])))$content, skip = 2) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = LAN, `Municipality code` = KOM, County = 'L\u00C4N', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Other no` = `OVR no`, `Other pct` = `OVR pct`,
`Blank no` = `BL no`, `Blank pct` = `BL pct`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb, `Turnout` = VDT,
`Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2014, .before = "County code") %>%
add_column(`Election type` = "Riksdag", .before = "County code"))
}
## Riksdag, 2018 ##
if(2018 %in% years) {
df <- bind_rows(df,
left_join(read_xlsx(GET(urls[3],
write_disk(tempfile(fileext = strsplit(basename(urls[3]), split="\\.")[[1]][2])))$content, sheet = "R antal") %>%
mutate(`Invalid no` = rowSums(.[,c(39,41)], na.rm = TRUE)) %>%
mutate(`Other no` = rowSums(.[,c(14:38)], na.rm = TRUE)) %>%
select(-c(14:39,41)) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:14)) %>%
add_column(`Year` = 2018, .before = "L\U00C4NSKOD") %>%
add_column(`Election type` = "Riksdag", .before = "L\U00C4NSKOD"),
read_xlsx(GET(urls[3],
write_disk(tempfile(fileext = strsplit(basename(urls[3]), split="\\.")[[1]][2])))$content, sheet = "R procent") %>%
mutate(`Invalid pct` = rowSums(.[,c(39,41)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(14:38)], na.rm = TRUE)) %>%
select(-c(14:39,41)) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:14)) %>%
add_column(`Year` = 2018, .before = "L\U00C4NSKOD") %>%
add_column(`Election type` = "Riksdag", .before = "L\U00C4NSKOD")) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\u00C4NSKOD', `Municipality code` = KOMMUNKOD, County = 'L\u00C4NSNAMN',
Municipality = KOMMUNNAMN, `Valid votes` = 'R\u00D6STER GILTIGA', `Votes cast` = 'R\u00D6STANDE',
`Registered voters` = 'R\u00D6STBER\u00C4TTIGADE', `Turnout` = VALDELTAGANDE,
`Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`))
}
}
########################
#### County Council ####
########################
if("county" %in% election_types) {
## County Council, 2010 ##
if(2010 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[4],
write_disk(tempfile(fileext = strsplit(basename(urls[4]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other no` = rowSums(.[,c(seq(21, 40, 2), seq(43, 92, 2))], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(seq(22, 40, 2), seq(44, 92, 2))], na.rm = TRUE)) %>%
select(-c(21:40, 43:92)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\U00C4N...1', `Municipality code` = KOM, County = 'L\U00C4N...3', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`,
`Valid votes` = `Rost Giltiga`, `Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "County council", .before = "County code"))
}
## County Council, 2014 ##
if(2014 %in% years) {
df <- bind_rows(df,
read_xls(GET(urls[5],
write_disk(tempfile(fileext = strsplit(basename(urls[5]), split="\\.")[[1]][2])))$content, skip = 2) %>%
mutate(`Other no` = rowSums(.[,seq(23, 112, 2)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,seq(24, 112, 2)], na.rm = TRUE)) %>%
select(-c(23:112)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\U00C4N...1', `Municipality code` = KOM, County = 'L\U00C4N...3', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`,
`Valid votes` = `Rost Giltiga`, `Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2014, .before = "County code") %>%
add_column(`Election type` = "County council", .before = "County code"))
}
## County Council, 2018 ##
if(2018 %in% years) {
df <- bind_rows(df,
left_join(read_xlsx(GET(urls[6],
write_disk(tempfile(fileext = strsplit(basename(urls[6]), split="\\.")[[1]][2])))$content, sheet = "L antal") %>%
mutate(`Invalid no` = rowSums(.[,c(53,55)], na.rm = TRUE)) %>%
mutate(`Other no` = rowSums(.[,c(14:52)], na.rm = TRUE)) %>%
select(-c(14:52,53,55)) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:14)),
read_xlsx(GET(urls[6],
write_disk(tempfile(fileext = strsplit(basename(urls[6]), split="\\.")[[1]][2])))$content, sheet = "L procent") %>%
mutate(`Invalid pct` = rowSums(.[,c(53,55)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(14:52)], na.rm = TRUE)) %>%
select(-c(14:52,53,55)) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:14))) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\u00C4NSKOD', `Municipality code` = KOMMUNKOD, County = 'L\u00C4NSNAMN',
Municipality = KOMMUNNAMN, `Valid votes` = 'R\u00D6STER GILTIGA', `Votes cast` = 'R\u00D6STANDE',
`Registered voters` = 'R\u00D6STBER\u00C4TTIGADE', `Turnout` = VALDELTAGANDE,
`Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`) %>%
add_column(`Year` = 2018, .before = "County code") %>%
add_column(`Election type` = "County council", .before = "County code"))
}
}
###########################
#### Municipal Council ####
###########################
if("municipal" %in% election_types) {
## Municipal Council, 2010 ##
if(2010 %in% years) {
df <- bind_rows(df,
left_join(read_xls(GET(urls[7],
write_disk(tempfile(fileext = strsplit(basename(urls[7]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other no` = rowSums(.[,c(13:96, 98:222)], na.rm = TRUE)) %>%
select(-c(13:96, 98:222)) %>%
rename(`County code` = 'L\U00C4N...1', `County` = 'L\U00C4N...3', `Municipality code` = `KOM...2`,
`Municipality` = `KOMMUN`, `Blank` = `BLANK`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid` = `OG`, `Invalid` = `OG`,
L = FP) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:15)) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code"),
read_xls(GET(urls[8],
write_disk(tempfile(fileext = strsplit(basename(urls[8]), split="\\.")[[1]][2])))$content) %>%
mutate(`Other pct` = rowSums(.[,c(13:96, 98:222)], na.rm = TRUE)) %>%
select(-c(13:96, 98:222)) %>%
rename(`County code` = 'L\U00C4N...1', `County` = 'L\U00C4N...3', `Municipality code` = `KOM...2`,
`Municipality` = `KOMMUN`, `Blank` = `BLANK`, `Valid votes` = `Rost Giltiga`,
`Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid` = `OG`, `Invalid` = `OG`,
L = FP) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:15)) %>%
add_column(`Year` = 2010, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code")))
}
## Municipal Council, 2014 ##
if(2014 %in% years) {
df <- bind_rows(df,
read_xlsx(GET(urls[9],
write_disk(tempfile(fileext = strsplit(basename(urls[9]), split="\\.")[[1]][2])))$content, skip = 2) %>%
mutate(`Other no` = rowSums(.[,seq(23, 518, 2)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,seq(24, 518, 2)], na.rm = TRUE)) %>%
select(-c(23:518)) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\U00C4N...1', `Municipality code` = KOM, County = 'L\U00C4N...3', Municipality = KOMMUN,
`L no` = `FP no`, `L pct` = `FP pct`, `Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`,
`Valid votes` = `Rost Giltiga`, `Votes cast` = Rostande, `Registered voters` = Rostb,
`Turnout` = VDT, `Invalid no` = `OG no`, `Invalid pct` = `OG pct`) %>%
add_column(`Year` = 2014, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code"))
}
## Municipal Council, 2018 ##
if(2018 %in% years) {
df <- bind_rows(df,
left_join(read_xlsx(GET(urls[10],
write_disk(tempfile(fileext = strsplit(basename(urls[10]), split="\\.")[[1]][2])))$content, sheet = "K antal") %>%
mutate(`Invalid no` = rowSums(.[,c(225,227)], na.rm = TRUE)) %>%
mutate(`Other no` = rowSums(.[,c(14:224)], na.rm = TRUE)) %>%
select(-c(14:224,225,227)) %>%
rename_with(.fn = ~ paste0(.x, " no"), .cols = c(5:14)),
read_xlsx(GET(urls[10],
write_disk(tempfile(fileext = strsplit(basename(urls[10]), split="\\.")[[1]][2])))$content, sheet = "K procent") %>%
mutate(`Invalid pct` = rowSums(.[,c(225,227)], na.rm = TRUE)) %>%
mutate(`Other pct` = rowSums(.[,c(14:224)], na.rm = TRUE)) %>%
select(-c(14:224,225,227)) %>%
rename_with(.fn = ~ paste0(.x, " pct"), .cols = c(5:14))) %>%
rename_with(., ~ gsub(" tal", " no", .x, fixed = TRUE)) %>%
rename_with(., ~ gsub(" proc", " pct", .x, fixed = TRUE)) %>%
rename(`County code` = 'L\u00C4NSKOD', `Municipality code` = KOMMUNKOD, County = 'L\u00C4NSNAMN',
Municipality = KOMMUNNAMN, `Valid votes` = 'R\u00D6STER GILTIGA', `Votes cast` = 'R\u00D6STANDE',
`Registered voters` = 'R\u00D6STBER\u00C4TTIGADE', `Turnout` = VALDELTAGANDE,
`Blank no` = `BLANK no`, `Blank pct` = `BLANK pct`) %>%
add_column(`Year` = 2018, .before = "County code") %>%
add_column(`Election type` = "Municipal council", .before = "County code"))
}
}
return(df)
}
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