party_utils.R

# 
# print("hello")
# 
# print(getwd())

all_dat <- readRDS("../data/all_dat.rds")

# print("hello")

sets <- jsonlite::fromJSON("../settings.json")




options(scipen = 999)


# wtm_data %>% count(party,sort = T)


# source("../party_utils.R")
color_dat <- tibble(
  colors = c("#00b13d", "#80c31c", "#0a2cca", "#008067", "#bf0000", "#ff0000", "#6f2421", "#02a6e9", "#92107d", "#04d3d4", "#242b57", "#66cdaa", "#242b57", "#006b28", "#012758", "#ea5b0b", "#582c83", "#698c0c", "#fdfd00", "#8da6d6", "#dc1f26", "#FFD700"),
  party = c("D66", "GroenLinks", "VVD", "CDA", "SP", "PvdA", "FvD", "ChristenUnie", "50PLUS", "Alliantie", "BVNL", "DENK", "Ja21", "PvdD", "PVV", "SGP", "Volt Nederland", "BBB", "BIJ1", "NSC", "GroenLinks-PvdA", "Libertaire Partij"))


most_left_party <- "VVD"


scale_fill_parties <- function(...){
  ggplot2:::manual_scale(
    'fill',
    values = setNames(color_dat$colors, color_dat$party),
    ...
  )
}
scale_color_parties <- function(...){
  ggplot2:::manual_scale(
    'color',
    values = setNames(color_dat$colors, color_dat$party),
    ...
  )
}

# election_dat30 <- read_rds("https://github.com/groene/TK2023/raw/main/historic/2023-11-17/30.rds") %>%
#   # left_join(all_dat) %>%
#   rename(internal_id = page_id) %>%
#   filter(party != "And")  %>%
#   filter(is.na(no_data)) %>%
#   mutate(party = ifelse(party %in% c("GroenLinks", "PvdA"), "GroenLinks-PvdA", party))
# 
# election_dat7 <- read_rds("https://github.com/groene/TK2023/raw/main/historic/2023-11-17/7.rds") %>%
#   # left_join(all_dat) %>%
#   rename(internal_id = page_id) %>%
#   filter(party != "And")  %>%
#   filter(is.na(no_data)) %>%
#   mutate(party = ifelse(party %in% c("GroenLinks", "PvdA"), "GroenLinks-PvdA", party))

election_dat30 <- readRDS("../data/election_dat30.rds") %>%
  # left_join(all_dat) %>%
  rename(internal_id = page_id) %>%
  filter(party != "And")  %>%
  filter(is.na(no_data)) %>%
  mutate(party = ifelse(party %in% c("GroenLinks", "PvdA"), "GroenLinks-PvdA", party))


election_dat7 <- readRDS("../data/election_dat7.rds") %>%
  # left_join(all_dat) %>%
  rename(internal_id = page_id) %>%
  filter(party != "And")  %>%
  filter(is.na(no_data)) %>%
  mutate(party = ifelse(party %in% c("GroenLinks", "PvdA"), "GroenLinks-PvdA", party))

# saveRDS(election_dat30, "../data/election_dat30.rds")
# saveRDS(election_dat7, "../data/election_dat7.rds")

fin <- (as.Date(election_dat30$ds[1])-lubridate::days(1))
begin7 <- fin-lubridate::days(6)
begin30 <- fin-lubridate::days(29)

tibble(fin,
       begin7,
       begin30) %>% 
  write_csv("../data/dates.csv")


# Setting the system locale to Dutch for time/date formatting
Sys.setlocale("LC_TIME", "nl_NL")

# Function to create Dutch date strings with suffixes
create_date <- function(x) {
  the_date <- format(x, "%e %b") # %e for day of the month without leading zeros, %B for full month name in Dutch
  # In Dutch, date suffixes are not commonly used so we can omit the 'append_date_suffix' part
  return(trimws(the_date)) # trimws to remove any leading or trailing whitespace which might be left after %e
}

last7days_string <- paste0(create_date(begin7), " - ", create_date(fin), " ", lubridate::year(fin)) %>% str_replace("Oct", "Okt")
last30days_string <- paste0(create_date(begin30), " - ", create_date(fin), " ", lubridate::year(fin)) %>% str_replace("Oct", "Okt")

# # Print the Dutch date range strings
# print(last7days_string)
# print(last30days_string)
# 
# # Reset locale back to the original if necessary
# Sys.setlocale("LC_TIME", "C")





the_currency <- election_dat30 %>%
  count(main_currency, sort = T) %>%
  slice(1) %>%
  pull(main_currency)

if(the_currency == "EUR"){
  currency_symbol <- "€"
} else if(the_currency=="INR"){
  currency_symbol <- "₹"
} else {
  currency_symbol <- the_currency
}