R/map_results.R
In electorArg/polAr: Argentina Political Analysis
Defines functions
map_results
Documented in
map_results
#' Mapea resultados (\emph{Map results})
#'
#' @description
#' Función para mapear resultados de la elección
#' (\emph{Function to map election results})
#'
#' @param data un tibble guardado como objeto en el Enviroment luego de consultar \code{\link{get_election_data}} con parámetro
#' \code{level} en \code{provincia} para elecciones presidenciales y \code{level} en \code{departamento} para legislativas
#' (\emph{tibble saved as an object in the Enviroment after querying \code{\link{get_election_data}}} with \code{provincia} as
#' \code{level} parameter for presidential elections and \code{departmanto} for legislative elections).
#' #'
#' @details \strong{REQUISITOS:}
#'
#' @details \strong{1}. El formato de \code{data} debe ser \code{long} para poder graficar. Si \code{data} es \emph{wide} se puede
#' transformar con \code{\link{make_long}}
#' (\emph{\code{long} format of \code{data} is required for plotting results. If \code{data} is in \emph{wide} format you can transform
#' it with \code{\link{make_long}}})
#'
#' @details \strong{2.} \code{data} tiene que haber incorporando los nombres de las listas. Agreguelos con \code{\link{get_names}}
#' (\emph{\code{data} must have party names. Add them with \code{\link{get_names}}})
#'
#' @return Devuelve un objeto de \code{class"gg" "ggplot"} que mapea el resultado de una eleccion condicional al nivel de agregacion de data
#' (\emph{Returns an object of \code{class "gg" "ggplot"} that plots the election results in a map conditional on the level of \code{data} aggregation.}).
#'
#'
#' @seealso
#' \code{\link{tabulate_results}, \link{plot_results}}
#'
#' @export
map_results <- function(data){
level <- if("circuito" %in% colnames(data)) {
c("circuito")
} else if (dim(data)[2] == 8){
c("provincia")
} else {
c("departamento")
}
## Check for internet coection
attempt::stop_if_not(.x = curl::has_internet(),
msg = "Internet access was not detected. Please check your connection //
No se detecto acceso a internet. Por favor chequear la conexion.")
# Check parameters and data format
assertthat::assert_that("listas" %in% colnames(data),
msg = "data is not in a long format. Use 'make_long()' to transform it")
assertthat::assert_that(level %in% c("provincia", "departamento"),
msg = glue::glue({level}," is not a valid level. Options are 'provincia' for presidential elections & 'departamento' for legislative elections"))
if(unique(data$category) %in% c("dip", "sen")){
assertthat::assert_that(level == "departamento" & "coddepto" %in% colnames(data),
msg = glue::glue({level}," is not a valid level for legislative election. Download it at 'departamento' level"))
}else if(unique(data$category) == "presi" & level == "departamento"){
assertthat::assert_that(level == "provincia",
msg = glue::glue({level}," is not a valid level for presidential election. Download it at 'provincia' level"))
}
# DATA INPUT
election_district <- if(unique(data$category == "presi")){
"ARGENTINA"
} else {
unique(data$name_prov)
}
election_date <- unique(data$year)
election_category <- data %>%
dplyr::ungroup() %>%
dplyr::select(category) %>%
dplyr::distinct() %>%
dplyr::mutate(value = dplyr::case_when(
category == "dip" ~ "Diputado Nacional",
category == "sen" ~ "Senador Nacional",
category == "presi" ~ "Presidente de la Naci\u00F3n"
)) %>%
dplyr::pull()
election_round <- data %>%
dplyr::ungroup() %>%
dplyr::select(round) %>%
dplyr::distinct() %>%
dplyr::mutate(value = dplyr::case_when(
round == "gral" ~ "General",
round == "paso" ~ "PASO",
round == "balota" ~ "Balotaje"
)) %>%
dplyr::pull()
## COMPUTE VOTES
votes_pct <- if(unique(data$category) == "presi"){
#PRESIDENTIAL DATA
data %>%
dplyr::group_by(codprov) %>%
dplyr::filter(!listas %in% c("blancos", "nulos")) %>%
dplyr::mutate(pct = votos/sum(votos)*100) %>%
polAr::get_names()
}else{
# LEGISLTIVE DATA
data %>%
dplyr::group_by(codprov, coddepto) %>%
dplyr::filter(!listas %in% c("blancos", "nulos")) %>%
dplyr::mutate(pct = votos/sum(votos)*100) %>%
polAr::get_names()
}
### GET FRONT RUNNERS
front_runners <- votes_pct %>%
dplyr::ungroup() %>%
dplyr::group_by(nombre_lista) %>%
dplyr::summarise(totales = sum(votos)) %>%
dplyr::top_n(n = 2, wt = totales) %>%
dplyr::arrange(dplyr::desc(totales))
data <- votes_pct %>%
dplyr::filter(nombre_lista %in% front_runners$nombre_lista) %>%
dplyr::left_join(front_runners, by = "nombre_lista") %>%
dplyr::arrange(dplyr::desc(totales)) %>%
dplyr::mutate(dif = pct - dplyr::lead(pct)) %>%
dplyr::slice(1) %>%
dplyr::mutate(group = dplyr::case_when(
dif > 0 & dif < 5 ~ 5,
dif >= 5 & dif < 10 ~ 10,
dif >= 10 & dif < 15 ~ 15,
dif >= 15 ~ 20,
dif < 0 & dif > -5 ~ -5,
dif <= -5 & dif > -10 ~ -10,
dif <= -10 & dif > -15 ~ -15,
dif <= -15 ~ -20,
))
# IMPORT MAPS CONDITIONAL
if(unique(data$category) == "presi"){
# ARG MAP
map <- sf::read_sf("https://github.com/electorArg/PolAr_Data/raw/master/geo/provincias.geojson")
# PRESIDENTIAL ELECTION
# NATIONAL MAP
pais <- data %>%
dplyr::left_join(map, by = "codprov") %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::geom_rect(xmin = -59, xmax = -58, ymin = -34, ymax = -35,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3",
limits = c(-20, 20),
breaks = c(-20, -15, -10, -5, 0, 5, 10, 15, 20),
labels = c(paste0("20 o + \n", front_runners$nombre_lista[2]),
"15",
"10",
"5",
"0",
"5",
"10",
"15",
paste0(front_runners$nombre_lista[1], "\n20 o +"))) +
ggplot2::theme(legend.direction = "vertical",
legend.position = "right",
legend.text.align = 0,
legend.spacing.x = ggplot2::unit(.5, 'cm'),
legend.text = ggplot2::element_text(margin = ggplot2::margin(t = 10))) +
ggplot2::labs(fill = "",
title = glue::glue("Elecci\u00F3n a {election_category} - {election_round} {election_date}"),
subtitle = "Puntos Porcentuales de Diferencia",
caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr")
# SUBSET MAP
caba <- data %>%
dplyr::left_join(map, by = "codprov") %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::coord_sf(xlim = c(-58.55, -58.3),
ylim = c(-34.75, -34.5), expand = FALSE) +
ggplot2::geom_rect(xmin = -58.55, xmax = -58.3, ymin = -34.5, ymax = -34.75,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3") +
ggplot2::theme(legend.position = "none")
# COWPLOT COMBINE
cowplot::ggdraw(pais) +
cowplot::draw_plot(caba,
width = 0.26,
height = 0.26 * .5,
x = 0.6, y = 0.5)
}else{
# PROVs MAPs
map <- sf::read_sf("https://github.com/electorArg/PolAr_Data/raw/master/geo/departamentos.geojson") %>%
dplyr::rename(coddepto = coddept) %>%
dplyr::select(-depto)
if (unique(data$name_prov) == "BUENOS AIRES"){
pba <- data %>%
dplyr::left_join(map, by = c("codprov", "coddepto")) %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::geom_rect(xmin = -59, xmax = -58, ymin = -34, ymax = -35,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3",
breaks = c(-20, -15, -10, -5, 0, 5, 10, 15, 20),
limits = c(-20, 20),
labels = c(paste0("20 o + \n", front_runners$nombre_lista[2]),
"15",
"10",
"5",
"0",
"5",
"10",
"15",
paste0(front_runners$nombre_lista[1], "\n20 o +"))) +
ggplot2::theme(legend.direction = "vertical",
legend.position = "right",
legend.text.align = 0,
legend.spacing.x = ggplot2::unit(.5, 'cm'),
legend.text = ggplot2::element_text(margin = ggplot2::margin(t = 10))) +
ggplot2::labs(fill = "",
title = glue::glue("Elecci\u00F3n a {election_category} por {election_district} - {election_round} {election_date}"),
subtitle = "Puntos Porcentuales de Diferencia",
caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr")
# SUBSET MAP
amba <- data %>%
dplyr::left_join(map, by = c("codprov", "coddepto")) %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3") +
ggplot2::coord_sf(xlim = c(-59, -58),
ylim = c(-35, -34), expand = FALSE) +
ggplot2::geom_rect(xmin = -59, xmax = -58, ymin = -34, ymax = -35,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::theme(legend.position = "none")
# COWPLOT COMBINE
cowplot::ggdraw(pba) +
cowplot::draw_plot(amba,
width = 0.3,
height = 0.3 ,
x = 0.7, y = 0.6)
} else {
data %>%
dplyr::left_join(map, by = c("codprov", "coddepto")) %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3",
limits = c(-20, 20),
breaks = c(-20, -15, -10, -5, 0, 5, 10, 15, 20),
labels = c(paste0("20 o + \n", front_runners$nombre_lista[2]),
"15",
"10",
"5",
"0",
"5",
"10",
"15",
paste0(front_runners$nombre_lista[1], "\n20 o +"))) +
ggplot2::theme(legend.direction = "vertical",
legend.position = "right",
legend.text.align = 0,
legend.spacing.x = ggplot2::unit(.5, 'cm'),
legend.text = ggplot2::element_text(margin = ggplot2::margin(t = 10))) +
ggplot2::labs(fill = "",
title = glue::glue("Elecci\u00F3n a {election_category} por {election_district} - {election_round} {election_date}"),
subtitle = "Puntos Porcentuales de Diferencia",
caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr")
} # Close provs != PBA if condition
} # Close legislative if condition
} # Close function
electorArg/polAr documentation built on Oct. 31, 2023, 8:27 a.m.
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Defines functions map_results
Documented in map_results
#' Mapea resultados (\emph{Map results})
#'
#' @description
#' Función para mapear resultados de la elección
#' (\emph{Function to map election results})
#'
#' @param data un tibble guardado como objeto en el Enviroment luego de consultar \code{\link{get_election_data}} con parámetro
#' \code{level} en \code{provincia} para elecciones presidenciales y \code{level} en \code{departamento} para legislativas
#' (\emph{tibble saved as an object in the Enviroment after querying \code{\link{get_election_data}}} with \code{provincia} as
#' \code{level} parameter for presidential elections and \code{departmanto} for legislative elections).
#' #'
#' @details \strong{REQUISITOS:}
#'
#' @details \strong{1}. El formato de \code{data} debe ser \code{long} para poder graficar. Si \code{data} es \emph{wide} se puede
#' transformar con \code{\link{make_long}}
#' (\emph{\code{long} format of \code{data} is required for plotting results. If \code{data} is in \emph{wide} format you can transform
#' it with \code{\link{make_long}}})
#'
#' @details \strong{2.} \code{data} tiene que haber incorporando los nombres de las listas. Agreguelos con \code{\link{get_names}}
#' (\emph{\code{data} must have party names. Add them with \code{\link{get_names}}})
#'
#' @return Devuelve un objeto de \code{class"gg" "ggplot"} que mapea el resultado de una eleccion condicional al nivel de agregacion de data
#' (\emph{Returns an object of \code{class "gg" "ggplot"} that plots the election results in a map conditional on the level of \code{data} aggregation.}).
#'
#'
#' @seealso
#' \code{\link{tabulate_results}, \link{plot_results}}
#'
#' @export
map_results <- function(data){
level <- if("circuito" %in% colnames(data)) {
c("circuito")
} else if (dim(data)[2] == 8){
c("provincia")
} else {
c("departamento")
}
## Check for internet coection
attempt::stop_if_not(.x = curl::has_internet(),
msg = "Internet access was not detected. Please check your connection //
No se detecto acceso a internet. Por favor chequear la conexion.")
# Check parameters and data format
assertthat::assert_that("listas" %in% colnames(data),
msg = "data is not in a long format. Use 'make_long()' to transform it")
assertthat::assert_that(level %in% c("provincia", "departamento"),
msg = glue::glue({level}," is not a valid level. Options are 'provincia' for presidential elections & 'departamento' for legislative elections"))
if(unique(data$category) %in% c("dip", "sen")){
assertthat::assert_that(level == "departamento" & "coddepto" %in% colnames(data),
msg = glue::glue({level}," is not a valid level for legislative election. Download it at 'departamento' level"))
}else if(unique(data$category) == "presi" & level == "departamento"){
assertthat::assert_that(level == "provincia",
msg = glue::glue({level}," is not a valid level for presidential election. Download it at 'provincia' level"))
}
# DATA INPUT
election_district <- if(unique(data$category == "presi")){
"ARGENTINA"
} else {
unique(data$name_prov)
}
election_date <- unique(data$year)
election_category <- data %>%
dplyr::ungroup() %>%
dplyr::select(category) %>%
dplyr::distinct() %>%
dplyr::mutate(value = dplyr::case_when(
category == "dip" ~ "Diputado Nacional",
category == "sen" ~ "Senador Nacional",
category == "presi" ~ "Presidente de la Naci\u00F3n"
)) %>%
dplyr::pull()
election_round <- data %>%
dplyr::ungroup() %>%
dplyr::select(round) %>%
dplyr::distinct() %>%
dplyr::mutate(value = dplyr::case_when(
round == "gral" ~ "General",
round == "paso" ~ "PASO",
round == "balota" ~ "Balotaje"
)) %>%
dplyr::pull()
## COMPUTE VOTES
votes_pct <- if(unique(data$category) == "presi"){
#PRESIDENTIAL DATA
data %>%
dplyr::group_by(codprov) %>%
dplyr::filter(!listas %in% c("blancos", "nulos")) %>%
dplyr::mutate(pct = votos/sum(votos)*100) %>%
polAr::get_names()
}else{
# LEGISLTIVE DATA
data %>%
dplyr::group_by(codprov, coddepto) %>%
dplyr::filter(!listas %in% c("blancos", "nulos")) %>%
dplyr::mutate(pct = votos/sum(votos)*100) %>%
polAr::get_names()
}
### GET FRONT RUNNERS
front_runners <- votes_pct %>%
dplyr::ungroup() %>%
dplyr::group_by(nombre_lista) %>%
dplyr::summarise(totales = sum(votos)) %>%
dplyr::top_n(n = 2, wt = totales) %>%
dplyr::arrange(dplyr::desc(totales))
data <- votes_pct %>%
dplyr::filter(nombre_lista %in% front_runners$nombre_lista) %>%
dplyr::left_join(front_runners, by = "nombre_lista") %>%
dplyr::arrange(dplyr::desc(totales)) %>%
dplyr::mutate(dif = pct - dplyr::lead(pct)) %>%
dplyr::slice(1) %>%
dplyr::mutate(group = dplyr::case_when(
dif > 0 & dif < 5 ~ 5,
dif >= 5 & dif < 10 ~ 10,
dif >= 10 & dif < 15 ~ 15,
dif >= 15 ~ 20,
dif < 0 & dif > -5 ~ -5,
dif <= -5 & dif > -10 ~ -10,
dif <= -10 & dif > -15 ~ -15,
dif <= -15 ~ -20,
))
# IMPORT MAPS CONDITIONAL
if(unique(data$category) == "presi"){
# ARG MAP
map <- sf::read_sf("https://github.com/electorArg/PolAr_Data/raw/master/geo/provincias.geojson")
# PRESIDENTIAL ELECTION
# NATIONAL MAP
pais <- data %>%
dplyr::left_join(map, by = "codprov") %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::geom_rect(xmin = -59, xmax = -58, ymin = -34, ymax = -35,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3",
limits = c(-20, 20),
breaks = c(-20, -15, -10, -5, 0, 5, 10, 15, 20),
labels = c(paste0("20 o + \n", front_runners$nombre_lista[2]),
"15",
"10",
"5",
"0",
"5",
"10",
"15",
paste0(front_runners$nombre_lista[1], "\n20 o +"))) +
ggplot2::theme(legend.direction = "vertical",
legend.position = "right",
legend.text.align = 0,
legend.spacing.x = ggplot2::unit(.5, 'cm'),
legend.text = ggplot2::element_text(margin = ggplot2::margin(t = 10))) +
ggplot2::labs(fill = "",
title = glue::glue("Elecci\u00F3n a {election_category} - {election_round} {election_date}"),
subtitle = "Puntos Porcentuales de Diferencia",
caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr")
# SUBSET MAP
caba <- data %>%
dplyr::left_join(map, by = "codprov") %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::coord_sf(xlim = c(-58.55, -58.3),
ylim = c(-34.75, -34.5), expand = FALSE) +
ggplot2::geom_rect(xmin = -58.55, xmax = -58.3, ymin = -34.5, ymax = -34.75,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3") +
ggplot2::theme(legend.position = "none")
# COWPLOT COMBINE
cowplot::ggdraw(pais) +
cowplot::draw_plot(caba,
width = 0.26,
height = 0.26 * .5,
x = 0.6, y = 0.5)
}else{
# PROVs MAPs
map <- sf::read_sf("https://github.com/electorArg/PolAr_Data/raw/master/geo/departamentos.geojson") %>%
dplyr::rename(coddepto = coddept) %>%
dplyr::select(-depto)
if (unique(data$name_prov) == "BUENOS AIRES"){
pba <- data %>%
dplyr::left_join(map, by = c("codprov", "coddepto")) %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::geom_rect(xmin = -59, xmax = -58, ymin = -34, ymax = -35,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3",
breaks = c(-20, -15, -10, -5, 0, 5, 10, 15, 20),
limits = c(-20, 20),
labels = c(paste0("20 o + \n", front_runners$nombre_lista[2]),
"15",
"10",
"5",
"0",
"5",
"10",
"15",
paste0(front_runners$nombre_lista[1], "\n20 o +"))) +
ggplot2::theme(legend.direction = "vertical",
legend.position = "right",
legend.text.align = 0,
legend.spacing.x = ggplot2::unit(.5, 'cm'),
legend.text = ggplot2::element_text(margin = ggplot2::margin(t = 10))) +
ggplot2::labs(fill = "",
title = glue::glue("Elecci\u00F3n a {election_category} por {election_district} - {election_round} {election_date}"),
subtitle = "Puntos Porcentuales de Diferencia",
caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr")
# SUBSET MAP
amba <- data %>%
dplyr::left_join(map, by = c("codprov", "coddepto")) %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3") +
ggplot2::coord_sf(xlim = c(-59, -58),
ylim = c(-35, -34), expand = FALSE) +
ggplot2::geom_rect(xmin = -59, xmax = -58, ymin = -34, ymax = -35,
fill = NA, colour = "black", size = 1.5) +
ggthemes::theme_map() +
ggplot2::theme(legend.position = "none")
# COWPLOT COMBINE
cowplot::ggdraw(pba) +
cowplot::draw_plot(amba,
width = 0.3,
height = 0.3 ,
x = 0.7, y = 0.6)
} else {
data %>%
dplyr::left_join(map, by = c("codprov", "coddepto")) %>%
dplyr::ungroup() %>% sf::st_as_sf() %>%
ggplot2::ggplot() +
ggplot2::geom_sf(ggplot2::aes(fill = group)) +
ggthemes::theme_map() +
ggplot2::scale_fill_gradient2(low = "#7fbf7b", mid = "white", high = "#af8dc3",
limits = c(-20, 20),
breaks = c(-20, -15, -10, -5, 0, 5, 10, 15, 20),
labels = c(paste0("20 o + \n", front_runners$nombre_lista[2]),
"15",
"10",
"5",
"0",
"5",
"10",
"15",
paste0(front_runners$nombre_lista[1], "\n20 o +"))) +
ggplot2::theme(legend.direction = "vertical",
legend.position = "right",
legend.text.align = 0,
legend.spacing.x = ggplot2::unit(.5, 'cm'),
legend.text = ggplot2::element_text(margin = ggplot2::margin(t = 10))) +
ggplot2::labs(fill = "",
title = glue::glue("Elecci\u00F3n a {election_category} por {election_district} - {election_round} {election_date}"),
subtitle = "Puntos Porcentuales de Diferencia",
caption = "Fuente: polAr - Pol\u00EDtica Argentina usando R - https://electorarg.github.io/polAr")
} # Close provs != PBA if condition
} # Close legislative if condition
} # Close function
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