Code for Constitution DAO concentration of ownership graph

constitution.R

library(tidyverse)
# Download Constitution DAO by going to:
#     https://juicebox.money/#/p/constitutiondao
# Then click on "Holders" and then in the modal click the little download 
# button. It misses some transactions since balances will be inaccurate for
# users who unstaked and transferred their tokens. Given the numbers below,
# this seems like a very small problem.
# Assume a US 4000 = 1 ETH Rate.. which is close enough on 11/18/2021
cdao <- read_csv("~/Downloads/juicebox_project-36_holders.csv") %>% 
  mutate(
    dollars = 4000*`Total ETH paid`    
  )

sum(cdao$dollars)
# 46,400,023 raiused. Which seems about right given they DAO raised 40m+

nrow(cdao$dollars)
# 17,454 unique wallets (~people) contributed

summary(cdao$dollars)
# Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
# 0      80     208    2,658     710 4,000,000 

# cdao is sorted from largest to smallest contributor
# So we can focus on first 174 rows to see how much of the 40m comes
# from the top 1% of contributors...
sum(cdao$dollars[1:174])
# 30,898,587 which is 30,898,587/46,400,023 = 66.5% of funds

# And from the next 99%  of contributors
sum(cdao$dollars[175:17454])
# 15,50,1436 which is (duh) only 33.5%!

# By comparison the top 1% of US households by income hold
# "just" 27% of US wealth. 
# https://www.bloomberg.com/news/articles/2021-10-08/
# top-1-earners-hold-more-wealth-than-the-u-s-middle-class

cdao_bar <- data.frame(Contributors=c("Top 1% of contributors", 
                                      "Bottom 99% of contributors"), 
                       `Amount` = c(30898587/1000000, 15501436/1000000))
ggplot(cdao_bar, aes(x=Contributors, y=Amount)) + 
  geom_bar(stat = "identity") + 
  ylab("Amount contributed to Constituation DAO (USD Millions)") + xlab("") +
  theme_bw()