This particular visualization is done on R and image is rendered on this blog. Replicationg of the entire challenge seems to be very tough especially having a unique background across the plots.
1. Original Dubios Visualization
2. My Version for replication
Dubios-Challenge_MyCode
#DubiosChallenge2024library(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-pickerdubois_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_plotdubois_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_plotdubois_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_plot1library(patchwork)final_plot <- label_plot + base_plot + label_plot1 + plot_layout(widths = c(1, 1.6, 1)) final_plot