pacdf

library(tidyverse)

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library(gganimate)

Warning: package 'gganimate' was built under R version 4.3.1

library(gifski)

pacdf1 <- read_csv("pacdf/pacdf1999-2000.csv", show_col_types = FALSE) |>
  mutate(year = 2000)

pacdf2 <- read_csv("pacdf/pacdf2001-2002.csv",  show_col_types = FALSE) |>
  mutate(year = 2002)

pacdf3 <- read_csv("pacdf/pacdf2003-2004.csv", show_col_types = FALSE) |>
  mutate(year = 2004)

pacdf4 <- read_csv("pacdf/pacdf2005-2006.csv", show_col_types = FALSE) |>
  mutate(year = 2006)

pacdf5 <- read_csv("pacdf/pacdf2007-2008.csv", show_col_types = FALSE) |>
  mutate(year = 2008)

pacdf6 <- read_csv("pacdf/pacdf2009-2010.csv", show_col_types = FALSE) |>
  mutate(year = 2010)

pacdf7 <- read_csv("pacdf/pacdf2011-2012.csv", show_col_types = FALSE) |>
  mutate(year = 2012)

pacdf8 <- read_csv("pacdf/pacdf2013-2014.csv", show_col_types = FALSE) |>
  mutate(year = 2014)

pacdf9 <- read_csv("pacdf/pacdf2015-2016.csv", show_col_types = FALSE) |>
  mutate(year = 2016)

pacdf10 <- read_csv("pacdf/pacdf2017-2018.csv", show_col_types = FALSE) |>
  mutate(year = 2018)

pacdf11 <- read_csv("pacdf/pacdf2019-2020.csv", show_col_types = FALSE) |>
  mutate(year = 2020)

pacdf12 <- read_csv("pacdf/pacdf2021-2022.csv", show_col_types = FALSE) |>
  mutate(year = 2022)

pacdf13 <- read_csv("pacdf/pacdf2023-2024.csv", show_col_types = FALSE) |>
  mutate(year = 2024)


combinepacdf <- bind_rows(pacdf1, pacdf2, pacdf3, pacdf4, pacdf5, 
          pacdf6, pacdf7, pacdf8, pacdf9, pacdf10, 
          pacdf11, pacdf12, pacdf13)

processpac <- combinepacdf |>
  separate( "Country of Origin/Parent Company", into = c("Country", "Parent_Company"), sep = "/") |>
  mutate(Dems = as.double(str_sub(Dems, 2, 12))) |>
  mutate(Repubs = as.double(str_sub(Repubs, 2, 12))) |>
  mutate(Total = as.double(str_sub(Total, 2, 12))) |>
  drop_na()

processpac |>
  summarise(Dems = sum(Dems), 
            Repubs = sum(Repubs), .by = c(year)) |>
  pivot_longer(cols = c("Dems", "Repubs"), names_to = "Parties",
               values_to = "Values") |>
  ggplot(aes(x = year, y = Values, color = Parties)) +
  geom_point() + 
  geom_line()

processpac |>
  pivot_longer(cols = c("Dems", "Repubs"), names_to = "Parties",
               values_to = "Values") |>
  summarise(valuescount = sum(Values), .by = c(Country, year, Parties)) |>
  ggplot(aes(x = Country, y = valuescount, fill = Parties)) +
  geom_col(position = 'dodge') + 
  transition_time(year)+
  scale_x_discrete(guide = guide_axis(angle = 45)) + 
  theme_bw()

animated_plot <- processpac %>%
  pivot_longer(cols = c("Dems", "Repubs"), names_to = "Parties", values_to = "Values") %>%
  summarise(valuescount = sum(Values), .by = c(Country, year, Parties)) %>%
  ungroup() |>
  ggplot(aes(x = Country, y = valuescount, fill = Parties)) +
  geom_col(position = 'dodge') +
  scale_x_discrete(guide = guide_axis(angle = 45)) +
  theme_bw() +
  transition_time(year) +
  labs(title = 'Year: {frame_time}', y = 'Total Donations', x = 'Country') +
  ease_aes('linear')

# Render and save the animation
animate(animated_plot,  fps = 10)