diff --git a/2024/2024-04-30/20240430.R b/2024/2024-04-30/20240430.R
new file mode 100644
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+++ b/2024/2024-04-30/20240430.R
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+# Load packages -----------------------------------------------------------
+
+library(tidyverse)
+library(showtext)
+library(patchwork)
+library(camcorder)
+library(ggtext)
+library(nrBrand)
+library(glue)
+library(geofacet)
+
+
+# Load data ---------------------------------------------------------------
+
+tuesdata <- tidytuesdayR::tt_load("2024-04-30")
+wwbi_data <- tuesdata$wwbi_data
+wwbi_series <- tuesdata$wwbi_series
+wwbi_country <- tuesdata$wwbi_country
+
+
+# Load fonts --------------------------------------------------------------
+
+font_add_google("Roboto", "roboto")
+font_add_google("Roboto Slab", "robotoslab")
+showtext_auto()
+
+
+# Define colours and fonts-------------------------------------------------
+
+bg_col <- "#fafafa"
+text_col <- "black"
+highlight_col <- "#4EA699"
+fem_col <- "#8D80AD"
+
+body_font <- "roboto"
+title_font <- "robotoslab"
+
+
+# Data wrangling ----------------------------------------------------------
+
+choose_ind <- wwbi_series |>
+ filter(indicator_name %in% c(
+ "Females, as a share of public paid employees",
+ "Number of public paid employees"
+ ))
+
+choose_region <- wwbi_country |>
+ select(country_code, short_name, x2_alpha_code) |>
+ filter(x2_alpha_code %in% geofacet::europe_countries_grid1$code)
+
+plot_data <- wwbi_data |>
+ filter(indicator_code %in% choose_ind$indicator_code) |>
+ filter(country_code %in% choose_region$country_code) |>
+ group_by(country_code) |>
+ slice_max(year) |>
+ ungroup() |>
+ left_join(choose_region, by = "country_code") |>
+ select(x2_alpha_code, short_name, indicator_code, value) |>
+ pivot_wider(names_from = indicator_code, values_from = value) |>
+ mutate(
+ Males = 1 - BI.PWK.PUBS.FE.ZS
+ ) |>
+ rename(Females = BI.PWK.PUBS.FE.ZS) |>
+ pivot_longer(
+ cols = c(Males, Females),
+ names_to = "Gender",
+ values_to = "Share"
+ ) |>
+ mutate(
+ New_Gender = case_when(
+ is.na(Share) ~ "Missing",
+ TRUE ~ Gender
+ ),
+ Share = case_when(
+ is.na(Share) & Gender == "Females" ~ 1,
+ is.na(Share) & Gender == "Males" ~ NA,
+ TRUE ~ Share
+ )
+ ) |>
+ filter(x2_alpha_code != "TR")
+
+new_grid <- europe_countries_grid1 |>
+ left_join(choose_region[,2:3], by = c("code" = "x2_alpha_code")) |>
+ as_tibble() |>
+ select(-name) |>
+ rename(name = short_name) |>
+ mutate(name = str_wrap(name, 10))
+
+
+# Start recording ---------------------------------------------------------
+
+gg_record(
+ dir = file.path("2024", "2024-04-30", "recording"),
+ device = "png",
+ width = 5,
+ height = 7.5,
+ units = "in",
+ dpi = 300
+)
+
+
+# Define text -------------------------------------------------------------
+
+social <- nrBrand::social_caption(
+ bg_colour = bg_col,
+ icon_colour = highlight_col,
+ font_colour = text_col,
+ font_family = body_font
+)
+title <- "Public sector employment in Europe"
+st <- glue("The Worldwide Bureaucracy Indicators (WWBI) database is a unique
+ cross-national dataset on public sector employment and wages that
+ aims to fill an information gap. This infographic shows the share of **males** and
+ **females** in public paid employment, with the size of each
+ pie chart indicating the total number of public paid employees. Grey
+ pie charts indicate countries where the share of male and female employees
+ is unknown.")
+cap <- paste0(
+ "**Data**: World Bank
**Graphic**:", social
+)
+
+
+# Plot --------------------------------------------------------------------
+
+ggplot(plot_data) +
+ geom_arc_bar(
+ mapping = aes(
+ x0 = 0, y0 = 0, r0 = 0, r = BI.PWK.PUBS.NO,
+ amount = Share,
+ fill = New_Gender
+ ),
+ stat = "pie",
+ colour = NA
+ ) +
+ scale_fill_manual(
+ values = c(
+ "Males" = highlight_col,
+ "Females" = fem_col,
+ "Missing" = "grey50"
+ )
+ ) +
+ facet_geo(~x2_alpha_code, grid = new_grid, label = "name") +
+ labs(
+ title = title,
+ subtitle = st,
+ caption = cap
+ ) +
+ coord_fixed(expand = FALSE) +
+ theme_void(base_size = 22, base_family = body_font) +
+ theme(
+ legend.position = "none",
+ plot.margin = margin(5, 5, 5, 5),
+ plot.background = element_rect(fill = bg_col, colour = bg_col),
+ panel.background = element_rect(fill = bg_col, colour = bg_col),
+ plot.title = element_textbox_simple(
+ colour = text_col,
+ hjust = 0,
+ halign = 0,
+ margin = margin(b = 10, t = 10),
+ lineheight = 0.5,
+ size = rel(2),
+ face = "bold",
+ family = title_font
+ ),
+ plot.subtitle = element_textbox_simple(
+ colour = text_col,
+ hjust = 0,
+ halign = 0,
+ margin = margin(b = 10, t = 5),
+ lineheight = 0.5,
+ family = body_font
+ ),
+ plot.caption = element_textbox_simple(
+ colour = text_col,
+ hjust = 0,
+ halign = 0,
+ margin = margin(b = 0, t = 0),
+ lineheight = 0.5,
+ family = body_font
+ ),
+ panel.spacing = unit(0.6, "lines"),
+ strip.text.x = element_text(
+ lineheight = 0.4,
+ vjust = 1,
+ size = rel(0.8),
+ margin = margin(l = 5, r = 5)
+ )
+ )
+
+record_polaroid()
+
+
+# Save gif ----------------------------------------------------------------
+
+gg_playback(
+ name = file.path("2024", "2024-04-30", paste0("20240430", ".gif")),
+ first_image_duration = 4,
+ last_image_duration = 20,
+ frame_duration = .25,
+ background = bg_col
+)
diff --git a/2024/2024-04-30/20240430.gif b/2024/2024-04-30/20240430.gif
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diff --git a/2024/2024-04-30/20240430.png b/2024/2024-04-30/20240430.png
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diff --git a/2024/2024-04-30/README.md b/2024/2024-04-30/README.md
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+++ b/2024/2024-04-30/README.md
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+ Worldwide Bureaucracy Indicators
+
+
+ 
+
+
+The making of this visualisation was also recorded using the {camcorder} package.
+
+
+ 
+