Unlocking the Power of Data Visualization with R

Plate 14

Sun, 31 Mar 2024 22:00:00 GMT

Overview

Illiteracy (plate 14)

Plate 25

Sun, 31 Mar 2024 22:00:00 GMT

Overview

Assessed Value of Household and Kitchen Furniture Owned by Georgia Negroes (plate 25)

Follow the code here: https://r4ds.github.io/bookclub-ggplot2/non-linear-coordinate-systems.html

Challenge 05 - Plate 13

Sun, 03 Mar 2024 23:00:00 GMT

Overview

Race Amalgamation in Georgia (plate 13), March 4

Install Libraries

# install.packages("tidyverse")
# remotes::install_github("coolbutuseless/ggpattern")

Load Libraries

suppressPackageStartupMessages({
  library(tidyverse)
  library(patchwork)
  library(sysfonts)
  library(showtext)
})

Load Data

url <- "https://raw.githubusercontent.com/ajstarks/dubois-data-portraits/master/challenge/2024/challenge05/data.csv"

dat <- read_csv("https://raw.githubusercontent.com/ajstarks/dubois-data-portraits/master/challenge/2024/challenge05/data.csv")
dat

Bar Plot

dat %>%
  ggplot(aes(x=Category,y=Percentage))+
  geom_col()

Staked Bar Plot

dat %>%
  ggplot(aes(x=1,y=Percentage,fill=Category))+
  geom_col(show.legend = F)

Dubois Style

colors_bar <- c("#1C1C1Bff","#2A1A12ff","#FDBA00ff")
colors_text <- c("#E6D7C6ff","#dc143c","#1C1C1Bff")

sysfonts::font_add_google(name="Public Sans",
                          family = "Public Sans",
                          regular.wt = 100)

sysfonts::font_add_google(name="Public Sans",
                          family = "Public Sans-med",
                          regular.wt = 600)
sysfonts::font_add_google(name="Freehand",
                          family="Freehand")
showtext::showtext_auto()
showtext::showtext_opts(dpi=320)

Stacked Bar Plot with Dubois’ style

dat %>%
  ggplot(aes(x=1,y=Percentage,fill=Category))+
  geom_col(show.legend = F)+
  scale_fill_manual(values = colors_bar)+
  geom_text(aes(label=Percentage))

Plot 1

plot1 <- dat %>%
  mutate(yy=c(Percentage[3]+Percentage[2]+Percentage[1]/2,
              Percentage[3]+Percentage[2]/2,
              Percentage[3]/2)) %>%
  ggplot(aes(x=1,y=Percentage,fill=Category))+
  geom_col(show.legend = F)+
  scale_fill_manual(values = colors_bar)+
  geom_text(aes(y=yy,label=paste0(Percentage,"%")),
            color=colors_text,
            family="Freehand")+
  xlim(0.5,1.5)

Text

text <- c("I.E. FULL-BLOODED\nNEGROES.",
          "I.E. PERSONS WITH\nSOME WHITE BLOOD\nOR DESCENDANTS\nOF LIGHT COLORED\nAFRICANS.",
          "I.E. PERSONS WITH\nMORE WHITE THAN\nNEGRO BLOOD.")

Text Plot

dat %>%
  mutate(text1=rev(cumsum(rev(Percentage))))%>%
  ggplot(aes(x=1,y=text1))+
  geom_text(aes(label=text))

Plot 2

plot2 <- dat %>%
  mutate(text1=rev(cumsum(rev(Percentage))))%>%
  ggplot(aes(x=1,y=text1))+
  geom_text(aes(label=c("BLACK.","BROWN.","YELLOW.")),
            family="Public Sans-med",
            size=3)+
  geom_text(aes(label=text),
          size=1.7,
          hjust=0,
          vjust=2*c(1,0.6,0.7),
          family="Public Sans")+
  ylim(0,110)+
  xlim(0.5,1.7)

Plot Layout

(plot2 + plot1) + 
  patchwork::plot_layout(ncol = 2)

Full Visualization

(plot2 + plot1) + 
  patchwork::plot_layout(ncol = 2) & 
  plot_annotation(
    title="RACE AMALGAMATION IN GEORGIA .",
    subtitle = "BASED  ON  A  STUDY  OF  40,000  INDIVIDUALS  OF  NEGRO  DESCENT.\n",
    caption = "#DuboisChallenge2024 - Challenge05 | Federica Gazzelloni\n") &
  theme_void() &
  theme(plot.title = element_text(hjust=0.5,
                                  family="Public Sans-med",
                                  size=10),
        plot.subtitle = element_text(hjust=0.5,
                                     family="Public Sans",
                                     size=6.5),
        plot.caption = element_text(hjust=0.5,
                                    family="Public Sans",
                                    size=6.5))

Add a place holder

(plot2 + plot_spacer() + plot1) + 
  patchwork::plot_layout(ncol = 3, widths = c(1,0,1)) & 
  plot_annotation(
    title="RACE AMALGAMATION IN GEORGIA .",
    subtitle = "BASED  ON  A  STUDY  OF  40,000  INDIVIDUALS  OF  NEGRO  DESCENT.\n",
    caption = "#DuboisChallenge2024 - Challenge05 | Federica Gazzelloni\n") &
  theme_void() &
  theme(plot.title = element_text(hjust=0.5,
                                  family="Public Sans-med",
                                  size=10),
        plot.subtitle = element_text(hjust=0.5,
                                     family="Public Sans",
                                     size=6.5),
        plot.caption = element_text(hjust=0.5,
                                    family="Public Sans",
                                    size=6.5))

Save it!

ggsave(filename = "your_challenge05.png", 
       bg="#E6D7C6ff",
       height=5.5, width=4.5, unit="in")

Challenge 04 - Plate 1

Sun, 03 Mar 2024 23:00:00 GMT

Overview

The Georgia Negro (plate 01), February 26

Challenge 03 - Plate 19

Sun, 18 Feb 2024 23:00:00 GMT

Overview

Acres of Land Owned by Negroes in Georgia (plate 19), February 19

library(tidyverse)
library(sysfonts)
library(showtext)
sysfonts::font_add_google("Public Sans","Public Sans")
# font_add_google("Carter One", "Carter One")
showtext::showtext_auto()
showtext::showtext_opts(dpi=320)

data <- read.csv("https://raw.githubusercontent.com/ajstarks/dubois-data-portraits/master/challenge/2024/challenge03/data.csv")
data%>%dim

data$Date%>%typeof()

data %>%
  mutate(Date=as.factor(-Date))%>%
  ggplot(aes(x=Land,y=factor(Date)))+
  geom_col(width=0.6,
           linewidth=0.1,
           color=alpha("#483c32",alpha = 0.9),
           fill="#ec3e58")+
  geom_text(aes(x=0,y=factor(Date),label=(data$Date)),
            family="Public Sans",
            color=alpha("#483c32",alpha = 0.7),
            hjust = 1.1,size=2)+
  geom_text(data=data%>%filter(Date=="1874"),
            aes(x=0,y=factor(Date)),
                label="338,769",
            color=alpha("black",alpha = 0.9),
            family="Public Sans",  fontface="bold",
            hjust = -0.5,vjust=2.7,size=1.5)+
    geom_text(data=data%>%filter(Date=="1899"),
            aes(x=0,y=factor(Date)),
                label="1,062,223",
            color=alpha("black",alpha = 0.9),
            family="Public Sans",fontface="bold",
            hjust = -2.5,vjust=55.75,size=1.5)+
  scale_y_discrete(labels=rev(data$Date),
                   expand =expansion(mult=0,add = 0))+
  scale_x_continuous(expand =expansion(mult=1,add = 0))+
  coord_cartesian(ylim = c(-1,29),clip = "off")+
  labs(title="ACRES OF LAND OWNED BY NEGROES\nIN GEORGIA.",
       caption="#DuboisChallenge 2024 Challenge 03 | Federica Gazzelloni")+
  theme_void()+
  theme(text=element_text(family="Public Sans"),
        plot.title = element_text(family="Public Sans",
                                  face="bold",
                                  size=8,
                                  color=alpha("#483c32",alpha = 0.9),
                                  hjust = 0.6,vjust=-18),
        plot.caption = element_text(hjust=0.5,size=4),
        axis.ticks = element_blank(),
        axis.text =element_blank(),
        axis.title = element_blank(),
        plot.background = element_rect(color="#eee3d5",fill="#eee3d5"),
        panel.background = element_rect(color="#eee3d5",fill="#eee3d5")
        )

ggsave("challenge03.png")

Challenge 02 - Plate 12

Sun, 11 Feb 2024 23:00:00 GMT

Overview

Slave and Free Negroes (plate 12), February 12

Load Libraries

library(tidyverse)
library(cowplot)
library(sysfonts)
library(showtext)
sysfonts::font_add_google("Public Sans","Public Sans")
# font_add_google("Carter One", "Carter One")
showtext::showtext_auto()
showtext::showtext_opts(dpi=320)

Load Data

ch2 <- read.csv("https://raw.githubusercontent.com/ajstarks/dubois-data-portraits/master/challenge/2024/challenge02/data.csv")
ch2

ch2_1 <- ch2 %>%
  arrange(Year)%>%
  mutate(Year=as.factor(Year),
         id=rev(row_number()))%>%
  relocate(id)
ch2_1

ch2_1%>%
  # pivot_longer(cols = c("Slave","Free"))%>%
  ggplot()+
  geom_col(aes(y=factor(id),x=Slave),fill="black")+
  geom_col(aes(y=factor(id),x=Free),fill="red")+
  coord_cartesian(xlim = c(3,100))

ch2_1%>%
  #pivot_longer(cols = c("Slave","Free"))%>%
  ggplot()+
  geom_line(aes(x=factor(id),y=Slave,group=1),color="red")+
  geom_line(aes(x=factor(id),y=Free,group=1),color="black")+
  scale_y_reverse()+
  coord_flip()

ch2_1%>%
  #pivot_longer(cols = c("Slave","Free"))%>%
  ggplot()+
  geom_area(aes(x=(id),y=Slave),fill="red")+
  geom_area(aes(x=(id),y=Free),fill="black")+
  scale_y_log10()+
  coord_flip()

ch2_1

ch2_2 <- ch2_1%>%
  mutate(Year=as.integer(Year))%>%
  mutate(Free_ln=log(Free),
         Slave_ln=log(Slave))
ch2_2

ch2_2%>%
  ggplot()+

  geom_ribbon(mapping=aes(x=Year,y=log(Free),
                         ymin=pmax(log(Free), -1),
                         ymax=pmax(log(Free), 5)), 
             fill='black')+
    geom_ribbon(mapping=aes(x=Year,y=log(Free),
                         ymin=pmin(log(Free), -1),
                         ymax=pmin(log(Free), 5)), 
             fill='#b5102d')+
    geom_line(aes(x=Year,y=log(Free)),
              linewidth=0.1,
              color="white")+
    geom_vline(aes(xintercept=Year),
             color="white",
             linewidth=0.1)+
  scale_y_reverse()+
  scale_x_reverse()+
  coord_flip(xlim = c(9,1),ylim = c(2,-0.8))+
  theme_void()+
  theme(#plot.background = element_rect(fill="#d2394f"),
        #panel.background = element_rect(fill="#d2394f"),
        panel.grid = element_blank())

ggsave("test.png",bg="#dbc8b4",
       width = 3,height = 6)

ch2_2

length(rep(ch2_2$id,11))

set.seed(000)
d <- tibble(x=rep(rnorm(90,mean=5,sd=20),each=10),
            y=seq(1.9,2,0.0001112347) #1/98
            )
# 0.2/(length(x)-1)
d%>%
  ggplot()+
  geom_line(aes(x=x,y=y))
  coord_flip()

ch2_2%>%
  ggplot()+

  geom_ribbon(mapping=aes(x=Year,y=log(Free),
                         ymin=pmax(log(Free), -1),
                         ymax=pmax(log(Free), 5)), 
             fill='black')+
    geom_ribbon(mapping=aes(x=Year,y=log(Free),
                         ymin=pmin(log(Free), -1),
                         ymax=pmin(log(Free), 5)), 
             fill='#b5102d')+
    geom_line(aes(x=Year,y=log(Free)),
              linewidth=0.1,
              color="white")+
    geom_vline(aes(xintercept=Year),
             color="white",
             linewidth=0.1)+
  geom_line(data=d,aes(x=x,y=y),color="#dbc8b4")+
  geom_ribbon(data=d,mapping=aes(x,y=y,
                   ymin=pmax(y, -1),
                   ymax=pmax(y, 5)), 
              fill='#dbc8b4')+
  scale_y_reverse()+
  scale_x_reverse()+
  coord_flip(xlim = c(9,1),ylim = c(2,-0.8))+
  theme_void()+
  theme(plot.background = element_rect(fill="#dbc8b4"),
        panel.background = element_rect(fill="#dbc8b4"),
        panel.grid = element_blank())

ggsave("test1.png",bg="#dbc8b4",
       width = 3,height = 6)

ch2_2$Free_ln

# Define the given numbers corresponding to decades
given_numbers <- ch2_2$Free_ln
# Function to simulate numbers within a decade
# Define the number of points to simulate within each decade
num_points_per_decade <- 10
# Initialize a vector to store the simulated numbers
simulated_numbers <- numeric()
# Simulate numbers within each decade
for (i in 1:9) {
  start <- given_numbers[i]
  end <- given_numbers[i + 1]
  simulated_within_decade <- rnorm(num_points_per_decade, start, end)
  simulated_numbers <- c(simulated_numbers, simulated_within_decade)
}

# Print the simulated numbers
print(simulated_numbers)

set.seed(000)
d <- tibble(x=simulated_numbers,
            y=seq(1.9,2,0.1/(length(x)-1)) #1/98
            )
# 0.2/(length(x)-1)
d%>%
  ggplot()+
  geom_line(aes(x=x,y=y))
  coord_flip()

ch2_2$Free%>%mean;
ch2_2$Slave%>%mean

set.seed(000)
d <- tibble(x=rep(rnorm(90,mean=5,sd=20),each=10),
            y=seq(1.9,2,0.0001112347) #1/98
            )
x=rep(rnorm(90,mean=5,sd=20),each=10)
y=seq(1.9,2,0.0001112347)
f <- approxfun(x, y)

# curve(f(x), 0, 11, col = "green2")
# points(x, y)
# 0.2/(length(x)-1)
d$x <- f(x)
ch2_2%>%
  ggplot()+
  geom_line(aes(x=Year,y=Free))+
  geom_line(aes(x=Year,y=log(Free)))
  coord_flip()

tb <- approx(ch2_2$Free,ch2_2$Year,n=900)
d2 <- tibble(x=tb$x,y=rnorm(900,mean=2,sd=0.02))
d2%>%summary()
d2%>%ggplot()+geom_line(aes(x,y))

years <- ch2_1$Year

ch2_2%>%
  ggplot()+

  geom_ribbon(mapping=aes(x=Year,y=log(Free),
                         ymin=pmax(log(Free), -1),
                         ymax=pmax(log(Free), 5)), 
             fill='black')+
  geom_ribbon(mapping=aes(x=Year,y=log(Free),
                       ymin=pmin(log(Free), -1),
                       ymax=pmin(log(Free), 5)), 
           fill='#b5102d')+
  geom_line(aes(x=Year,y=log(Free)),
            linewidth=0.1,
            color="#dbc8b4")+
  geom_vline(aes(xintercept=Year),
           color="#dbc8b4",
           linewidth=0.3)+
  geom_ribbon(data=d2,mapping=aes(x=x,y=y,
                   ymin=pmax(y, -1),
                   ymax=pmax(y, 5)), 
              fill='#dbc8b4')+
  geom_point(data=d2%>%filter(x>=1 & x <= 9),
             aes(x=x,y=y),
             color="black",
             shape=".")+
  geom_line(data=d2%>%filter(x>=1 & x <= 9),
          aes(x=x,y=y),
          color="black",linewidth=0.2)+
  # adjust scales to a reverse position
  scale_y_reverse(position = "right",
                  breaks = 0:2,
                  labels = paste0(c("1%", "2%", "3%"), ""))+
  scale_x_reverse(name = "First Axis",
                  position = "top",
                  breaks = 1:9,
                  expand = expansion(add=-0.5),
                  labels = paste0(rev(c("100%", "0.8", "0.7","0.9","0.8","1.2","1.7","1.7","1.3%")), ""),
                  sec.axis = sec_axis(~.*1, 
                                      name="Second Axis",
                                      breaks = 1:9,
                                      labels =years))+
  coord_flip(xlim = c(9.5,0.5),ylim = c(2.1,-0.8),
             clip = "off")+
  annotate("text", x = 0.55, y = -1.38,
       label = "PERCENT\nOF\nFREE NEGROES",
       size = 1.8,
       color=alpha("#483c32",alpha = 0.5),
       #fontface = "bold",
       family =  "Public Sans" ) +
  labs(title = "SLAVES AND FREE NEGROES.\n",
       caption = "\n#DuboisChallenge2024 - Challenge 2 | Federica Gazzelloni") +
  theme(text=element_text(family="Public Sans",color="#483c32"),
        plot.title = element_text(face="bold",hjust = 0.5,size=15,family="Public Sans",color="#483c32"),
        plot.caption = element_text(face="bold",hjust = 0.5,size=8,
                                    color=alpha("#483c32",alpha = 0.5)),
        plot.background = element_rect(fill="#dbc8b4",color="#dbc8b4"),
        panel.background = element_rect(fill="#dbc8b4",color="#dbc8b4"),
        panel.grid = element_blank(),
        axis.title = element_blank(),
        axis.line.x = element_blank(),
        axis.line.y = element_blank(),
        axis.ticks.x.top = element_line(linewidth=0.2,color="black"),
        axis.ticks.y.right = element_blank(),
        axis.ticks.y.left = element_blank(),
        axis.text = element_text(family =  "Public Sans",color=alpha("#483c32",alpha = 0.5)),
        axis.text.y.right = element_text(hjust=0,
                                         margin = margin(15,15,15,15),family =  "Public Sans"),
        axis.text.y.left = element_text(hjust=0,
                                         margin = margin(15,15,15,15),family =  "Public Sans"))

ggsave("test_approx.png",bg="#dbc8b4",
       width = 4,height = 6)

ggdraw()+
  draw_image("test_approx.png",scale = 0.8)

ggsave("challenge02.png",bg="#dbc8b4",
       width = 4.5,height = 6)

Challenge 01 - Plate 06

Sun, 04 Feb 2024 23:00:00 GMT

Overview

Negro Population of Georgia by Counties, 1870, 1880 (plate 06), February 5

library(tidyverse)
library(sf)
library(patchwork)

Data ready from the GitHub Repo

Download the georgia-1880-county-shapefile.zip file from: https://github.com/ajstarks/dubois-data-portraits/tree/master/challenge/2024/challenge01

georgia_shp <- sf::read_sf("data/georgia-1880-county-shapefile")

# georgia_shp%>%head

georgia_shp%>%
  ggplot()+
  geom_sf()

dat_sf <- georgia_shp%>%
  janitor::clean_names()%>%
  separate(data1870,into=c("up70","down70"))%>%
  separate(data1880_p,into=c("up80","down80"))%>%
  mutate(# pop 1870
         up70=ifelse(up70=="",0,up70),
         down70=ifelse(is.na(down70),0,down70),
         up70=as.numeric(up70),
         down70=as.numeric(down70),
         # pop 1880
         up80=ifelse(up80=="",0,up80),
         down80=ifelse(is.na(down80),0,down80),
         up80=as.numeric(up80),
         down80=as.numeric(down80))%>%
  rowwise()%>%
  mutate(pop70=mean(up70,down70),
         pop80=mean(up80,down80))%>%
  arrange(pop70,pop80)


data <- dat_sf%>%select(county=icpsrnam,
                pop70,pop80)%>%
  mutate(id=case_when(pop70 == 0 ~ 7,
                      pop70 == 1000 ~ 6,
                      pop70 == 2500 ~ 5,
                      pop70 == 5000 ~ 4,
                      pop70 == 10000 ~ 3,
                      pop70 == 15000 ~ 2,
                      pop70 == 20000 ~ 1),
         pop70=case_when(pop70 == 0 ~ "UNDER 1,000",
                         pop70 == 1000 ~ "1000 TO 2,500",
                         pop70 == 2500 ~ "2,500 TO 5,000",
                         pop70 == 5000 ~ "5,000 TO 10,000",
                         pop70 == 10000 ~ "10,000 TO 15,000",
                         pop70 == 15000 ~ "15,000 TO 20,000",
                         pop70 == 20000 ~ "20,000 TO 30,000"))%>%
  # pop80
    mutate(id=case_when(pop80 == 0 ~ 7,
                      pop80 == 1000 ~ 6,
                      pop80 == 2500 ~ 5,
                      pop80 == 5000 ~ 4,
                      pop80 == 10000 ~ 3,
                      pop80 == 15000 ~ 2,
                      pop80 == 20000 ~ 1),
         pop80=case_when(pop80 == 0 ~ "UNDER 1,000",
                         pop80 == 1000 ~ "1000 TO 2,500",
                         pop80 == 2500 ~ "2,500 TO 5,000",
                         pop80 == 5000 ~ "5,000 TO 10,000",
                         pop80 == 10000 ~ "10,000 TO 15,000",
                         pop80 == 15000 ~ "15,000 TO 20,000",
                         pop80 == 20000 ~ "20,000 TO 30,000"))
data%>%count(id,pop80)

Dybois Style

Fonts:

library(sysfonts)
library(showtext)
sysfonts::font_add_google("Public Sans","Public Sans")
# font_add_google("Carter One", "Carter One")
showtext::showtext_auto()
showtext::showtext_opts(dpi=320)

Colors:

Background:

"#e7d6c5"

Text:

c("#483c32","#bbaa98")

legend_colors <- c("#372c59","#7a5039","#c29e84","#d63352",
  "#e79d96","#edb456","#4b5c4f")

Bounding box: xmin: 939223.1 ymin: -701249.8 xmax: 1425004 ymax: -200888.5

pop70_map <- data%>%
  ggplot()+
  geom_sf(aes(fill=pop70),
          show.legend = F,
          color="#483c32",alpha=0.9,
          linewidth=0.1)+
  scale_fill_manual(values=c("UNDER 1,000"="#4b5c4f",
                             "1000 TO 2,500"="#edb456",
                             "2,500 TO 5,000"="#e79d96",
                             "5,000 TO 10,000"="#d63352",
                             "10,000 TO 15,000"="#c29e84",
                             "15,000 TO 20,000"="#7a5039",
                             "20,000 TO 30,000"="#372c59"),na.value = "#e0cebb")+
    annotate("text", x = -84.45, y = 35.1,
           label = "1870",
           size = 3.5,color="#483c32",
           fontface = "bold",
           family =  "Public Sans" ) +
   coord_sf(crs=4326,clip = "off")+
  ggthemes::theme_map()+
  theme(plot.background = element_rect(color="#e7d6c5",fill="#e7d6c5"),
        panel.background = element_rect(color="#e7d6c5",fill="#e7d6c5"))
  
pop70_map

pop80_map <- data%>%
  ggplot()+
  geom_sf(aes(fill=pop80),
          show.legend = F,
          color="#483c32",alpha=0.9,
          linewidth=0.1)+
  scale_fill_manual(values=c("UNDER 1,000"="#4b5c4f",
                             "1000 TO 2,500"="#edb456",
                             "2,500 TO 5,000"="#e79d96",
                             "5,000 TO 10,000"="#d63352",
                             "10,000 TO 15,000"="#c29e84",
                             "15,000 TO 20,000"="#7a5039",
                             "20,000 TO 30,000"="#372c59"),na.value = "#e0cebb")+
      annotate("text", x = -84.45, y = 35.1,
           label = "1880",
           size = 3.5,color="#483c32",
           fontface = "bold",
           family =  "Public Sans" ) +
  coord_sf(crs=4326,clip = "off")+
  ggthemes::theme_map()+
  theme(plot.background = element_rect(color="#e7d6c5",fill="#e7d6c5"),
        panel.background = element_rect(color="#e7d6c5",fill="#e7d6c5"))
  
pop80_map

Plot layout

source: https://ggplot2-book.org/arranging-plots

pop70_map+ ggplot() + ggplot()+ pop80_map + plot_layout(ncol = 2,nrow = 2)

legend1 <- tibble(x=0,y=c(4,3,2,1),
       label=c("5,000 TO 10,000",
                   "2,500 TO 5,000",
                    "1000 TO 2,500",
                   "UNDER 1,000"),
       pal=c("#d63352","#e79d96","#edb456","#4b5c4f"))%>%
  mutate(pal=as.factor(pal))
legend1

legend1_plot <- legend1%>%
  ggplot(aes(x,y))+
  geom_point(aes(fill=label),
             shape=21,stroke=0.1,
             size=8.5,
             show.legend = F)+
  scale_fill_manual(values=c("5,000 TO 10,000"="#d63352",
                                "2,500 TO 5,000"="#e79d96",
                                "1000 TO 2,500"="#edb456",
                                "UNDER 1,000"="#4b5c4f"))+
  geom_text(aes(label=label),
            family="Public Sans",
            size=3.5,color="#7a5039",
            nudge_x = 0,hjust=-0.2)+
  coord_cartesian(xlim=c(-0.2,1),ylim =c(-0,5) )+
  ggthemes::theme_map()+
  theme(plot.background = element_rect(color="#e7d6c5",fill="#e7d6c5"),
        panel.background = element_rect(color="#e7d6c5",fill="#e7d6c5"))
legend1_plot

legend2 <- tibble(x=0,y=c(1,2,3),
       label=c("10,000 TO 15,000",
               "15,000 TO 20,000",
               "BETWEEN 20,000 AND 30,000"),
       color=c("#c29e84","#7a5039","#372c59"))

legend2_plot <- legend2%>%
  ggplot(aes(x,y))+
  geom_point(aes(fill=label),
             shape=21,stroke=0.1,
             size=8.5,
             show.legend = F)+
  scale_fill_manual(values=c("10,000 TO 15,000"="#c29e84",
                             "15,000 TO 20,000"="#7a5039",
                             "BETWEEN 20,000 AND 30,000"="#372c59"))+
  geom_text(aes(label=label),
            size=3.5,color="#7a5039",
            family="Public Sans",
            nudge_x = 0.5,hjust=0)+
  coord_cartesian(xlim=c(-0.2,7),ylim =c(-1,4) )+
  ggthemes::theme_map()+
  theme(plot.background = element_rect(color="#e7d6c5",fill="#e7d6c5"),
        panel.background = element_rect(color="#e7d6c5",fill="#e7d6c5"))


legend2_plot

pop70_map+ legend2_plot + legend1_plot+ pop80_map + plot_layout(ncol = 2,nrow = 2)+plot_annotation(
  title = "NEGRO POPULATION OF GEORGIA BY COUNTIES.",
  caption="#DuboisChallenge24| Week1 | by Federica Gazzelloni",
  theme = theme_void(base_family = "Public Sans"))&
  theme(text=element_text(color="#483c32",face="bold"),
        plot.title = element_text(hjust=0.5),
        plot.caption = element_text(size=9),
        plot.background = element_rect(color="#e7d6c5",fill="#e7d6c5"),
        panel.background = element_rect(color="#e7d6c5",fill="#e7d6c5"))

ggsave("challenge01.png",bg="#e7d6c5",height = 8.8)

Materials

Fri, 05 Dec 2025 20:37:33 GMT

Slides

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