Du Bois Challenge

Recreating plate 37 from W.E.B. Du Bois’s 1900 data portraits in ggplot2.

A ggplot2 recreation of plate 37 from W.E.B. Du Bois’s data portraits for the 1900 Paris Exposition, for the 2024 Du Bois Visualization Challenge on TidyTuesday.

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TidyTuesday week2 Apr 2024

DatasetTidyTuesday 2024-04-02 readme ↗

Built withR · ggplot2

ChartsAnnotated pie chart

0. Introduction

This particular visualization is done on R and image is rendered on this blog. Replicating the entire challenge seems to be very tough especially having a unique background across the plots.

1. The original Du Bois plate

2. My Version for replication

#DubiosChallenge2024

library(tidyverse)

dubois_week10 <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-04-02/dubois_week10.csv')

order_series <- c(1,6,4,5,3,2)

color_palette <- c("#EC2744", "#FFC56F", "#8C7C70", "#EFC1B3", "#CCA288", "#61719D")

dubois_week10 <- cbind(dubois_week10,order_series,color_palette)



color_palette <- c("#EC2744", "#FFC56F", "#8C7C70", "#EFC1B3", "#CCA288", "#61719D")

#Source - https://redketchup.io/color-picker


dubois_week10 |>
  arrange(desc(Percentage)) |>
  ggplot(aes(x= "",y = Percentage,fill = reorder(order_series,Occupation))) + 
  geom_bar(stat = "identity",width = 1) + 
  coord_polar("y", start = 2.1) + 
  scale_fill_manual(values = color_palette) +
  theme_void() + 
  theme(legend.position = "none",
        plot.background = element_rect(fill = "#F5DEB3")) + 
  annotate(
  "text",
  x = 0.9,
  y = 65,
  label = expression(bold("58.5%")),
  size = 5
) + 
  annotate(
    "text",
    x = 1,
    y = 30,
    label = expression(bold("28.1%")),
    size = 5
  ) + 
  annotate(
    "text",
    x = 1.4,
    y = 11.5,
    label = expression(bold("3.8%")),
    size = 4
  )+ 
  annotate(
    "text",
    x = 1.4,
    y = 8,
    label = expression(bold("3.2%")),
    size = 4
  )+ 
  annotate(
    "text",
    x = 1.4,
    y = 5,
    label = expression(bold("2.1%")),
    size = 3
  )+ 
  annotate(
    "text",
    x = 1.3,
    y = 2,
    label = expression(bold("4.3%")),
    size = 4
  ) -> base_plot

dubois_week10 |>
  ggplot(aes(x=0.2,y=reorder(order_series/10,Occupation))) + 
  geom_point(aes(color = Occupation),size = 4) + 
  scale_y_discrete(expand = expansion(mult = c(1, 1))) + 
  coord_cartesian(xlim = c(0, 1))  +
  scale_color_manual(values = c("#61719D","#EFC1B3", "#8C7C70", "#EC2744", "#CCA288","#FFC56F")) +
  theme_void() + theme(legend.position = "none", plot.background = element_rect(fill = "#F5DEB3")) + 
  annotate(
    "text",
    x = 0.2,
    y = 6,
    hjust = -0.21,
    label = "TEACHERS"
  ) + 
  annotate(
    "text",
    x = 0.2,
    y = 5,
    hjust = -0.21,
    label = "MINISTERS"
  )+ 
  annotate(
    "text",
    x = 0.2,
    y = 4,
    hjust = -0.09,
    label = "GOVERNMENT SERVICE"
  )+ 
  annotate(
    "text",
    x = 0.2,
    y = 3,
    hjust = -0.21,
    label = "BUSINESS"
  )+ 
  annotate(
    "text",
    x = 0.2,
    y = 2,
    hjust = -0.1,
    label = "OTHER PROFESSORS"
  )+ 
  annotate(
    "text",
    x = 0.2,
    y = 1,
    hjust = -0.16,
    label = "HOUSE WIVES"
  ) -> label_plot



dubois_week10 |>
  ggplot(aes(x=0.9,y=reorder(order_series/10,Occupation))) + 
  geom_point(aes(color = Occupation),size = 4) + 
  scale_y_discrete(expand = expansion(mult = c(1, 1))) + 
  coord_cartesian(xlim = c(0, 1))  +
  scale_color_manual(values = c("#61719D","#EFC1B3", "#8C7C70", "#EC2744", "#CCA288","#FFC56F")) +
  theme_void() + theme(legend.position = "none",plot.background = element_rect(fill = "#F5DEB3")) + 
  annotate(
    "text",
    x = 0.57,
    y = 6,
    hjust = 0.7,
    label = "PROFESSEURS ET INSTITUTEURS",
  ) + 
  annotate(
    "text",
    x = 0.635,
    y = 5,
    hjust = 0.7,
    label = "MINISTERS DE L'EVANGILE"
  )+ 
  annotate(
    "text",
    x = 0.625,
    y = 4,
    hjust = 0.72,
    label = "EMPLOYEES DU GOVERNMENT"
  )+ 
  annotate(
    "text",
    x = 0.76,
    y = 3,
    hjust = 0.72,
    label = "MARCHANDS"
  )+ 
  annotate(
    "text",
    x = 0.60,
    y = 2,
    hjust = 0.72,
    label = "MEDCNS, ADVOCATS, ETUDIANTS"
  )+ 
  annotate(
    "text",
    x = 0.71,
    y = 1,
    hjust = 0.72,
    label = "MERES DE FAMILLE"
  ) -> label_plot1
  

library(patchwork)

final_plot <-  label_plot + base_plot + label_plot1 +
  plot_layout(widths = c(1, 1.6, 1)) 

final_plot 

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