trumpcongress

IMPORT

data <- readr::read_csv(file = "averages.csv")

## Parsed with column specification:
## cols(
##   congress = col_double(),
##   chamber = col_character(),
##   bioguide = col_character(),
##   last_name = col_character(),
##   state = col_character(),
##   district = col_double(),
##   party = col_character(),
##   votes = col_double(),
##   agree_pct = col_double(),
##   predicted_agree = col_double(),
##   net_trump_vote = col_double()
## )

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

data <- filter(.data = data, congress != 0)

library(ggplot2)
g <- ggplot(
  data = data,
  mapping = aes(x = net_trump_vote, fill = party)
)
g <- g + geom_histogram()
g <- g + scale_fill_manual(
  values = c("R" = "red", "D" = "blue", "I" = "darkgreen")
)
g 

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.