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# NOTE: It's not working on Posistron because of rJava, it works on RStudio. | |
if(!"rlang" %in% installed.packages()){ | |
if(!interactive()) { stop("The package \"rlang\" is required.") } | |
cat("The package \"rlang\" is required.\n✖ Would you like to install it?\n\n1: Yes\n2: No\n\nSelection:") | |
if (readLines(n = 1) == "1"){ | |
install.packages("rlang") | |
} | |
} | |
rlang::check_installed( | |
"jrrosell (>= 0.0.0.9006)", | |
action = \(pkg,...) { | |
if("jrrosell" %in% installed.packages()){ remove.packages("jrrosell") } | |
pak::pak("jrosell/jrrosell") | |
} | |
) | |
rlang::check_installed("tidyverse") | |
rlang::check_installed("rJava") | |
jrrosell::check_installed_gihub("cynkra/constructive") | |
jrrosell::check_installed_gihub("ropensci/tabulapdf") | |
# $ sudo apt-get install -y default-jre default-jdk | |
# $ sudo R CMD javareconf | |
# > install.packages("rJava") | |
library(tidyverse) | |
library(magick) | |
library(tesseract) | |
invisible(!dir.exists("data") && dir.create("data")) | |
jrrosell::theme_set_roboto_darkblue() | |
library(tabulapdf) | |
# extracted_areas <- "~/2022.pdf" |> | |
# locate_areas( | |
# pages = c(10,36,64,86), | |
# copy = TRUE | |
# ) | |
# constructive::construct(extracted_areas) | |
extracted_areas <- list( | |
c( | |
top = 201.27430329932372, | |
left = 42.011084579588, | |
bottom = 479.40651566442375, | |
right = 586.3601466864 | |
), | |
c( | |
top = 218.25947657352378, | |
left = 42.011084579588, | |
bottom = 496.39168893862376, | |
right = 579.98105611484 | |
), | |
c( | |
top = 199.15115664004372, | |
left = 39.884721055733, | |
bottom = 470, | |
right = 575.72832906713 | |
), | |
c( | |
top = 203.3974499585937, | |
left = 44.137448103443, | |
bottom = 479.40651566442375, | |
right = 567.22287497171 | |
) | |
) | |
lists_2022 <- "~/2022.pdf" |> | |
extract_tables( | |
pages = c(10,36,64,86), | |
area = extracted_areas, | |
guess = FALSE, | |
col_names = c("comunidad", "inicial", "value", "percent") | |
) | |
lists_2022[[1]]$name <- "Oblig. Reconocidas de la AGE" | |
lists_2022[[2]]$name <- "Oblig. Reconocidas de ORGANISMOS" | |
lists_2022[[3]]$name <- "Inversión real de ESTIMATIVOS" | |
lists_2022[[4]]$name <- "Inversión real de EMPRESAS" | |
df_2022 <- lists_2022 |> | |
list_rbind() |> | |
mutate(ano = 2022) | |
lists_2023 <- "~/2023.pdf" |> | |
extract_tables( | |
pages = c(10,36,64,86), | |
area = extracted_areas, | |
guess = FALSE, | |
col_names = c("comunidad", "inicial", "value", "percent") | |
) | |
lists_2023[[1]]$name <- "Oblig. Reconocidas de la AGE" | |
lists_2023[[2]]$name <- "Oblig. Reconocidas de ORGANISMOS" | |
lists_2023[[3]]$name <- "Inversión real de ESTIMATIVOS" | |
lists_2023[[4]]$name <- "Inversión real de EMPRESAS" | |
df_2023 <- lists_2023 |> | |
list_rbind() |> | |
mutate(ano = 2023) | |
locale_es <- readr::locale( | |
encoding = "latin1", | |
decimal_mark = ",", | |
grouping_mark = "." | |
) | |
df <- bind_rows(df_2022, df_2023) |> | |
mutate(value = parse_number(value, locale = locale_es)) |> | |
select(comunidad, ano, name, value) |> | |
print(n = Inf) | |
# Dades 2015-2021 | |
# Baixar manualment o executar la seguent funció | |
download_banco_datos <- \(x) { | |
rlang::check_installed("selenider") | |
library(selenider) | |
sess <- selenider_session( | |
"chromote", | |
timeout = 10, | |
options = chromote_options(headless = FALSE) | |
) | |
sess$driver$Browser$setDownloadBehavior( | |
behavior = "allow", | |
downloadPath = "data" | |
) | |
open_url("http://buscadorcdi.gob.es/Cifra/es/buscador/resultados/Ultimos-Distribucion-Territorial") | |
try({ | |
elem_click(s(".introjs-skipbutton"), timeout = 10) | |
}) | |
try({ | |
elem_click(s(".guardarBusqueda li:nth-child(3) img"), timeout = 20) | |
}) | |
Sys.sleep(10) | |
selenider::close_session() | |
} | |
comunidades <- c( | |
"PAÍS VASCO", | |
"CATALUÑA", | |
"GALICIA", | |
"ANDALUCÍA", | |
"PRINCIPADO DE ASTURIAS", | |
"CANTABRIA", | |
"LA RIOJA", | |
"REGION DE MURCIA", | |
"COMUNITAT VALENCIANA", | |
"COMUNITAD VALENCIANA", | |
"ARAGÓN", | |
"CASTILLA-LA MANCHA", | |
"CANARIAS", | |
"COMUNIDAD FORAL DE NAVARRA", | |
"EXTREMADURA", | |
"ILLES BALEARS", | |
"COMUNIDAD DE MADRID", | |
"CASTILLA Y LEÓN", | |
"CASTILLA Y LEON", | |
"CEUTA", | |
"MELILLA" | |
) | |
dat <- list.files("data") |> | |
{\(x) paste0("data/", x[str_detect(x, "Informe_Cifra")]) }() |> | |
read_csv2( | |
show_col_types = FALSE, | |
locale = readr::locale( | |
encoding = "latin1", | |
decimal_mark = ",", | |
grouping_mark = "." | |
), | |
skip = 1, | |
col_names = c( | |
"cod_administracion", "administracion", | |
"jerarquia_administracion", "submateria", | |
"materia", "cod_variable", | |
"variable", "nombre_corto_variable", | |
"unidad", "escala", | |
"ano", "trimestre", | |
"mes", "observaciones", | |
"valor", "variable_referencia", | |
"base_submateria_referencia", "unidad_variable_referencia", | |
"escala_variable_referencia", "valor_variable_referencia", | |
"ano_variable_referencia", "trimestre_variable_referencia", | |
"mes_variable_referencia", "observaciones_variable_referencia" | |
), | |
col_select = 1:24 | |
) |> | |
janitor::clean_names() |> | |
separate_wider_position( | |
cod_variable, c(cod_comunidad = 2), too_many = "debug" | |
) |> | |
select(-cod_comunidad, -cod_variable, -cod_variable_width, -cod_variable_ok) |> | |
rename(cod_variable = cod_variable_remainder) |> | |
filter(cod_variable %in% c("AGE_OR","OOAA_OR","ESTI_IR","EMP_IR")) |> | |
filter(str_detect(variable, paste(comunidades, collapse = "|"))) |> | |
separate_wider_delim( | |
variable, delim = ":", names = c("comunidad", "variable_resto") | |
) |> | |
select(-variable_resto) |> | |
mutate( | |
name = nombre_corto_variable |> | |
str_replace(paste0(" en ", comunidad), "") |> | |
str_replace(" en MURCIA", "") |> | |
str_replace(" en ASTURIAS", "") |> | |
str_replace(" en C. VALENCIANA", "") |> | |
str_replace(" en NAVARRA", "") |> | |
str_replace(" en C.LA MANCHA", "") |> | |
str_replace(" en MADRID", "") | |
) |> | |
filter(ano >= 2015) |> | |
arrange(comunidad, ano) |> | |
rename(value = valor) |> | |
select(comunidad, ano, value, name) | |
df_ccaa <- bind_rows(dat, df) |> | |
mutate(comunidad = comunidad |> | |
str_replace("CASTILLA Y LEON", "CASTILLA Y LEÓN") |> | |
str_replace("REGION DE MURCIA", "REGIÓN DE MURCIA") |> | |
str_replace("PRINCIPADO DE ASTURIAS", "P. ASTURIAS") |> | |
str_replace("COMUNIDAD DE MADRID", "C. MADRID") |> | |
str_replace("COMUNIDAD FORAL DE NAVARRA", "C.F. NAVARRA") |> | |
str_replace("COMUNITAT VALENCIANA", "C. VALENCIANA") | |
) | |
df_ccaa_all <- df_ccaa |> | |
group_by(comunidad, ano) |> | |
mutate(total = sum(value)) |> | |
ungroup() |> | |
pivot_longer(c(value,total), names_to = "name1") |> | |
mutate( | |
name = if_else( | |
name1 != "total", name, "Total ejecutado" | |
) | |
)|> | |
select(-name1) |> | |
unique() |> | |
print(n = Inf) | |
p1 <- df_ccaa_all |> | |
ggplot(aes(ano, value, colour = name)) + | |
geom_line(data = df_ccaa_all |> filter(name != "Total ejecutado"), size = 0.3) + | |
geom_line(data = df_ccaa_all |> filter(name == "Total ejecutado"), size = 0.9) + | |
facet_wrap("comunidad") + | |
scale_x_continuous(breaks = 2015:2023, guide = guide_axis(angle = 90)) + | |
scale_y_continuous( | |
labels = scales::unit_format(unit = "M €", scale = 1e-6, sep = "") | |
) + | |
labs( | |
subtitle = "Distribución territorial de la inversión del Sector Público Estatal", | |
caption = "Fuente: Ultimos-Distribucion-Territorial en buscadorcdi.gob.es y PDF ejercicios 2022-2023 hasta 31 diciembre | Autor: @jrosell", | |
y = "", x = "", colour = "" | |
) + | |
theme( | |
legend.position = "bottom", | |
panel.spacing.y = unit(2, "lines") | |
) | |
print(p1) | |
df_cat_mad <- df_ccaa |> | |
filter(comunidad %in% c("C. MADRID", "CATALUÑA")) |> | |
group_by(comunidad, name) |> | |
summarize(value = sum(value)) |> | |
ungroup() |> | |
mutate(ano = 2024, .after = 1) | |
df_cat_mad_all <- df_ccaa |> | |
bind_rows(df_cat_mad) |> | |
group_by(comunidad, ano) |> | |
mutate(total = sum(value)) |> | |
ungroup() |> | |
pivot_longer(c(value,total), names_to = "name1") |> | |
mutate( | |
name = if_else( | |
name1 != "total", name, "Total ejecutado" | |
) | |
)|> | |
select(-name1) |> | |
unique() |> | |
mutate(ano_label = factor(if_else(ano == 2024, "Total", as.character(ano)), c("Total", as.character(rev(c(2015:2023)))))) |> | |
filter(comunidad %in% c("C. MADRID", "CATALUÑA"), name == "Total ejecutado") |> | |
mutate(comunidad = factor(comunidad, c( "CATALUÑA", "C. MADRID"))) |> | |
print(n = Inf) | |
p2 <- df_ccaa |> | |
bind_rows(df_cat_mad) |> | |
mutate(ano_label = factor(if_else(ano == 2024, "Total", as.character(ano)), c("Total", as.character(rev(c(2015:2023)))))) |> | |
filter(comunidad %in% c("C. MADRID", "CATALUÑA")) |> | |
mutate(comunidad = factor(comunidad, c( "CATALUÑA", "C. MADRID"))) |> | |
ggplot(aes(ano_label, value)) + | |
geom_col(aes(fill = name)) + | |
geom_text( | |
nudge_y = 500000000, | |
aes(label = scales::number(value, suffix = "M €", scale = 1e-6, sep = "", accuracy = 1, big.mark = "")), | |
data = df_cat_mad_all | |
) + | |
scale_y_continuous( | |
labels = scales::unit_format(unit = "M €", scale = 1e-6, sep = ""), | |
n.breaks = 15, | |
guide = guide_axis(angle = 90) | |
) + | |
facet_wrap("comunidad", ncol = 1) + | |
coord_flip() + | |
labs( | |
title = "Distribución territorial de la inversión del Sector Público Estatal en Cataluña y Comunidad de Madrid", | |
caption = "Fuente: Ultimos-Distribucion-Territorial en buscadorcdi.gob.es y PDF ejercicios 2022-2023 hasta 31 diciembre | Autor: @jrosell", | |
y = "", x = "", fill = "" | |
) + | |
theme( | |
legend.position = "top", | |
panel.spacing.y = unit(2, "lines") | |
) | |
print(p2) |
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