The Data

This week’s data comes from Data for Progress. The data details pride sponsors, such as Fortune 500 companies, that simultaneously donate to pride events and anti-LGTQ+ politicians. A major focus of Data for Progress’s mission is to hold these corporations accountable for their actions.

pride_aggregates <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/pride_aggregates.csv')
fortune_aggregates <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/fortune_aggregates.csv')
static_list <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/static_list.csv')
pride_sponsors <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/pride_sponsors.csv')
corp_by_politicians <-readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/corp_by_politician.csv')
donors <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-06-07/donors.csv')

Creating a Tree Map

I wanted to make a tree map for this week’s Tidy Tuesday where the area a pride-sponsor Fortune 500 company takes up in the the plot is proportional to their donations to anti-LGTQ+ politicians. In order to keep the plot readable, I only included the 20 pride-sponsor Fortune 500 companies that donated the most to anti-LGTQ+ politicians. Much of the data wrangling done in the code blocks below were largely stylistic – done to make the Tree Map prettier.

top_20_new <- fortune_aggregates %>%
  rename(Total.Contributed = `Total Contributed`)%>%
  filter(Company != "Grand Total") %>%
  arrange(desc(Total.Contributed)) %>%
  slice(1:20) %>%
  mutate(Total.Contributed = round(Total.Contributed, digits = 0)) %>%
  mutate(options(scipen = 999)) %>%
  mutate(Company = case_when(Company == "Enterprise Products Partners" ~ "Enterprise Products",
                             Company == "American Electric Power" ~ "American \nElectric",
                             Company == "UnitedHealth Group" ~ "UnitedHealth",
                             Company == "Molina Healthcare" ~ "Molina \nHealthcare",
                             Company == "Berkshire Hathaway" ~ "Berkshire \nHathaway",
                             TRUE ~ Company))

The Plot

ggplot(top_20_new, aes(area = Total.Contributed, fill = Total.Contributed, label = paste(Company, paste("$",Total.Contributed, sep = ""), sep = "\n"), color = Total.Contributed)) +
  geom_treemap()+
  geom_treemap_text(color = "gray97", min.size = 0, fontface = "bold", place = "center")+
  theme_void()+
  theme(legend.position="none") +
  theme(plot.title = element_text(size = 12, face = "bold"))+
  scale_fill_gradient(low = "gray75", high = "gray15", space = "Lab")+
  ggtitle("'Pride Sponsor' Fortune 500 Companies Donating the MOST to Anti-LGBTQ+ Politicians")+
  labs(caption = "Tidy Tuesday 06-07-2022 | GitHub: @scolando")

A Subset of Non-Two-Faced Companies – supporting NYC Pride!

I included a short list of 20 randomly sampled pride sponsors for NYC pride that did not donate to anti_LGBTQ+ politicians. There are 125 such sponsors. Feel free to run the R-code chunk to see more of these pride sponsors.

yay_nottwofaced_companies <- subset(pride_sponsors, !(Company %in% pride_aggregates$Company)) %>%
  select(Company, 'Pride Event Sponsored') %>%
  rename(Pride_Event = 'Pride Event Sponsored') %>%
  filter(Pride_Event == "NYC Pride") %>%
  select(Company)
  

sample_n(yay_nottwofaced_companies, 20)
## # A tibble: 20 × 1
##    Company                                      
##    <chr>                                        
##  1 Chase                                        
##  2 PVH                                          
##  3 sage Advocacy & services for LGBT Elders     
##  4 SKYY Vodka                                   
##  5 TD Bank                                      
##  6 Nexus Radio                                  
##  7 Oscar Wilde Tours                            
##  8 Geeks Out                                    
##  9 Deutsche Bank                                
## 10 NBA                                          
## 11 National Pulse Memorial & Museum             
## 12 NY Botanical Garden                          
## 13 Immigration Equality                         
## 14 New York Life                                
## 15 The Cathedral Church of Saint John the Divine
## 16 CeraVe                                       
## 17 Diet Coke                                    
## 18 IGLTA                                        
## 19 The Ali Forney Center                        
## 20 smithsonian