The partycoloR package extracts political party colors
and logos from English Wikipedia party pages. This is useful for
political scientists and data visualization practitioners who want
consistent, recognizable colors for political parties in their charts
and graphs.
The main function get_party_color() takes Wikipedia URLs
and returns the party’s primary color as a hex code:
# Single party
dem_url <- "https://en.wikipedia.org/wiki/Democratic_Party_(United_States)"
get_party_color(dem_url)
#> "#0015BC"
# Multiple parties
urls <- c(
"https://en.wikipedia.org/wiki/Democratic_Party_(United_States)",
"https://en.wikipedia.org/wiki/Republican_Party_(United_States)",
"https://en.wikipedia.org/wiki/Green_Party_of_the_United_States"
)
get_party_color(urls)
#> "#0015BC" "#E81B23" "#17AA5C"Some parties have more than one official color. Use
all_colors = TRUE to get all colors:
Use get_party_logo() to get the URL of the party’s logo
image:
You can download logos to a local file using
download_party_logo():
# Get logo URL and download it
logo_url <- get_party_logo(dem_url)
download_party_logo(logo_url, "democratic_logo.png")
# Or use a pipeline with get_party_logo_by_name()
get_party_logo_by_name("SPD", country = "DEU") %>%
download_party_logo("spd_logo.svg")Note that the file extension should match the actual image format. Many Wikipedia logos are SVGs, so check the URL to determine the correct extension.
For efficiency, use get_party_info() to extract both
color and logo in a single request:
get_party_info(urls)
#> # A tibble: 3 x 3
#> url color logo_url
#> <chr> <chr> <chr>
#> 1 https://en.wikipedia.org/wiki/Democratic_Party_(Unite... #0015BC https://...
#> 2 https://en.wikipedia.org/wiki/Republican_Party_(Unite... #E81B23 https://...
#> 3 https://en.wikipedia.org/wiki/Green_Party_of_the_Unit... #17AA5C https://...The functions are designed to work seamlessly with
dplyr::mutate():
parties <- tibble(
party = c("Democrats", "Republicans", "Greens"),
wiki_url = c(
"https://en.wikipedia.org/wiki/Democratic_Party_(United_States)",
"https://en.wikipedia.org/wiki/Republican_Party_(United_States)",
"https://en.wikipedia.org/wiki/Green_Party_of_the_United_States"
)
)
parties %>%
mutate(
color = get_party_color(wiki_url),
logo = get_party_logo(wiki_url)
)When using all_colors = TRUE, the result is a
list-column. Use purrr functions to extract specific
colors:
library(purrr)
german_parties <- tibble(
party = c("CDU", "SPD"),
wiki_url = c(
"https://en.wikipedia.org/wiki/Christian_Democratic_Union_of_Germany",
"https://en.wikipedia.org/wiki/Social_Democratic_Party_of_Germany"
)
)
# Extract all colors as a list-column, then extract individual colors
german_parties %>%
mutate(
all_colors = get_party_color(wiki_url, all_colors = TRUE),
color_1 = map_chr(all_colors, pluck, 1, 1, .default = NA_character_),
color_2 = map_chr(all_colors, pluck, 1, 2, .default = NA_character_)
)
#> # A tibble: 2 x 5
#> party wiki_url all_colors color_1 color_2
#> <chr> <chr> <list> <chr> <chr>
#> 1 CDU https://en.wikipedia.org/wiki/Chris.. <list [1]> #000000 #FF6600
#> 2 SPD https://en.wikipedia.org/wiki/Soci.. <list [1]> #E3000F NAAlternatively, unnest to long format (one row per color):
german_parties %>%
mutate(all_colors = get_party_color(wiki_url, all_colors = TRUE)) %>%
tidyr::unnest_longer(all_colors) %>%
tidyr::unnest_longer(all_colors, values_to = "color")
#> # A tibble: 3 x 3
#> party wiki_url color
#> <chr> <chr> <chr>
#> 1 CDU https://en.wikipedia.org/wiki/Christian_Democratic... #000000
#> 2 CDU https://en.wikipedia.org/wiki/Christian_Democratic... #FF6600
#> 3 SPD https://en.wikipedia.org/wiki/Social_Democratic_Pa... #E3000FIf you don’t have Wikipedia URLs, you can look up parties by name using the Party Facts database integration.
Use get_party_color_by_name() to combine lookup and
color extraction:
Here’s how to use party colors in a ggplot2 visualization:
library(ggplot2)
# Example data: German 2021 election results
german_parties <- tibble(
party = c("SPD", "CDU/CSU", "Greens", "FDP", "AfD", "Left"),
vote_share = c(25.7, 24.1, 14.8, 11.5, 10.3, 4.9),
wiki_url = c(
"https://en.wikipedia.org/wiki/Social_Democratic_Party_of_Germany",
"https://en.wikipedia.org/wiki/Christian_Democratic_Union_of_Germany",
"https://en.wikipedia.org/wiki/Alliance_90/The_Greens",
"https://en.wikipedia.org/wiki/Free_Democratic_Party_(Germany)",
"https://en.wikipedia.org/wiki/Alternative_for_Germany",
"https://en.wikipedia.org/wiki/The_Left_(Germany)"
)
)
# Get party colors
german_parties <- german_parties %>%
mutate(color = get_party_color(wiki_url))
# Create bar chart with party colors
ggplot(german_parties, aes(x = reorder(party, -vote_share), y = vote_share)) +
geom_col(fill = german_parties$color) +
labs(
title = "German Federal Election 2021",
x = NULL,
y = "Vote Share (%)"
) +
theme_minimal()The functions handle errors gracefully:
# Invalid URLs return NA
get_party_color("https://not-wikipedia.com/page")
#> NA
# Non-existent pages return NA
get_party_color("https://en.wikipedia.org/wiki/Nonexistent_Party_12345")
#> NA
# Mixed valid and invalid URLs
urls <- c(
"https://en.wikipedia.org/wiki/Democratic_Party_(United_States)",
NA,
"invalid_url"
)
get_party_color(urls)
#> "#0015BC" NA NAThe Party Facts data is cached in the R session to avoid repeated downloads:
Batch requests: When processing many parties,
pass all URLs to get_party_color() at once rather than
calling it in a loop.
Cache Party Facts data: If you’ll be doing
multiple lookups, call get_partyfacts_wikipedia() once and
pass the result to lookup_party_url().
Handle missing data: Always check for NA values in the results, as some Wikipedia pages may not have color information or may have unexpected formatting.
Wikipedia changes: The scraping depends on Wikipedia’s HTML structure. If results seem wrong, the Wikipedia page format may have changed.