add 2019 plot

2019/2019-03-05/20190305.R

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+# Load packages -----------------------------------------------------------
+
+library(tidyverse)
+library(showtext)
+library(camcorder)
+library(ggtext)
+library(nrBrand)
+library(glue)
+library(scales)
+
+
+# Load data ---------------------------------------------------------------
+
+jobs_gender <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-03-05/jobs_gender.csv")
+
+
+# Load fonts --------------------------------------------------------------
+
+font_add_google("Roboto", "roboto")
+font_add_google("Roboto Slab", "roboto_slab")
+showtext_auto()
+
+
+# Define colours and fonts-------------------------------------------------
+
+bg_col <- "grey95"
+text_col <- "black"
+highlight_col <- "#93032E"
+
+body_font <- "roboto"
+title_font <- "roboto_slab"
+
+
+# Data wrangling ----------------------------------------------------------
+
+set.seed(123)
+plot_data <- jobs_gender |>
+  filter(year == 2016) |>
+  select(occupation, major_category, total_earnings_male, total_earnings_female) |>
+  drop_na() |>
+  group_by(major_category) |>
+  mutate(
+    min_cat = min(total_earnings_female),
+    max_cat = max(total_earnings_female)
+  ) |>
+  slice_sample(n = 1) |>
+  ungroup() |>
+  mutate(
+    label = glue("{str_to_sentence(occupation)} ({major_category})")
+  ) |>
+  mutate(label = reorder(label, -total_earnings_female))
+
+
+# Start recording ---------------------------------------------------------
+
+gg_record(
+  dir = file.path("2024", "recording"),
+  device = "png",
+  width = 7.5,
+  height = 5.5,
+  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 <- "The Gender Pay Gap"
+st <- "The gender pay gap is the gap between what men and women are paid. Most
+commonly, it refers to the median annual pay of all women who work full time
+and year-round, compared to the pay of a similar cohort of men. This chart shows
+the median annual income of female employess for a random sample of 8 occupations -
+one from each major occupation category. The black line shows the median annual
+income of males in the same occupation. The background bars indicate the minimum and maximum
+median female incomes for other occupations in the same major category."
+cap <- paste0(
+  "**Data**: Bureau of Labor Statistics (2016)<br>**Graphic**:", social
+)
+
+
+# Plot --------------------------------------------------------------------
+
+ggplot(plot_data) +
+  geom_col(
+    mapping = aes(x = max_cat, y = "1"),
+    fill = alpha(highlight_col, 0.3),
+    width = 1
+  ) +
+  geom_col(
+    mapping = aes(x = min_cat, y = 1),
+    fill = alpha(highlight_col, 0.3),
+    width = 1
+  ) +
+  geom_col(
+    mapping = aes(x = total_earnings_female, y = 1),
+    width = 0.35,
+    fill = highlight_col
+  ) +
+  geom_linerange(
+    aes(
+      x = total_earnings_male,
+      ymin = 1 - 0.3,
+      ymax = 1 + 0.3
+    ),
+    linewidth = 1.5,
+    colour = text_col
+  ) +
+  facet_wrap(~label,
+    ncol = 2, strip.position = "left",
+    labeller = labeller(label = label_wrap_gen(28))
+  ) +
+  scale_x_continuous(labels = comma) +
+  labs(
+    title = title, subtitle = st, caption = cap,
+    x = "Median annual income in 2016 ($)", y = ""
+  ) +
+  theme_minimal(base_size = 24, base_family = body_font) +
+  theme(
+    plot.margin = margin(5, 15, 5, 10),
+    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,
+      family = title_font,
+      face = "bold",
+      size = rel(2)
+    ),
+    plot.subtitle = element_textbox_simple(
+      colour = text_col,
+      hjust = 0,
+      halign = 0,
+      margin = margin(b = 10, t = 0),
+      lineheight = 0.5,
+      family = body_font
+    ),
+    plot.caption = element_textbox_simple(
+      colour = text_col,
+      hjust = 0,
+      halign = 0,
+      margin = margin(b = 5, t = 10),
+      lineheight = 0.5,
+      family = body_font
+    ),
+    axis.text.y = element_blank(),
+    strip.text.y.left = element_text(
+      hjust = 1,
+      angle = 0,
+      lineheight = 0.4,
+      margin = margin(r = 0, l = 5)
+    ),
+    panel.spacing.y = unit(0.4, "lines"),
+    plot.title.position = "plot",
+    plot.caption.position = "plot",
+    panel.grid.major.x = element_line(
+      linewidth = 0.5,
+      colour = alpha(text_col, 0.1)
+    ),
+    panel.grid.major.y = element_blank(),
+    panel.grid.minor = element_blank()
+  )
+
+
+# Save gif ----------------------------------------------------------------
+
+gg_playback(
+  name = file.path("2024", paste0("day_01", ".gif")),
+  first_image_duration = 4,
+  last_image_duration = 20,
+  frame_duration = .25,
+  background = bg_col
+)

2019/2019-03-05/README.md

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+<h1 align="center"> Women in the Workforce </h1>
+
+<p align="center">
+  <img src="/2019/2019-03-05/20190305.png" width="60%">
+</p>
+
+The making of this visualisation was also recorded using the {camcorder} package.
+
+<p align="center">
+  <img src="/2019/2019-03-05/20190305.gif" width="60%">
+</p>