Closed FredeJ closed 4 years ago
Here's 2016 Turnout from David Leip's Election Atlas
# David Leip Data
library(xml2)
library(rvest)
url <- "https://uselectionatlas.org/RESULTS/data.php?year=2016&datatype=national&def=1&f=0&off=0&elect=0"
r <- read_html(url)
tabs <- r %>% html_table(fill = TRUE)
tab <- tabs[[4]]
df <- data.frame(
state = tab$X3,
votes = as.integer(gsub(",", "", tab$X7)),
stringsAsFactors = F
)
df <- df[3:(nrow(df)-2),]
dput(df)
structure(list(state = c("Alabama", "Alaska", "Arizona", "Arkansas",
"California", "Colorado", "Connecticut", "Delaware", "D. C.",
"Florida", "Georgia", "Hawaii", "Idaho", "Illinois", "Indiana",
"Iowa", "Kansas", "Kentucky", "Louisiana", "Maine", "Maryland",
"Massachusetts", "Michigan", "Minnesota", "Mississippi", "Missouri",
"Montana", "Nebraska", "Nevada", "New Hampshire", "New Jersey",
"New Mexico", "New York", "North Carolina", "North Dakota", "Ohio",
"Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", "South Carolina",
"South Dakota", "Tennessee", "Texas", "Utah", "Vermont", "Virginia",
"Washington", "West Virginia", "Wisconsin", "Wyoming"), votes = c(2123372L,
318608L, 2604657L, 1130635L, 14237893L, 2780247L, 1644920L, 443814L,
311268L, 9502747L, 4141447L, 428937L, 690433L, 5594825L, 2757965L,
1566031L, 1194755L, 1924150L, 2029032L, 747927L, 2781446L, 3325046L,
4824542L, 2945233L, 1211088L, 2828266L, 501822L, 844227L, 1125385L,
744296L, 3906723L, 798319L, 7721795L, 4741564L, 344360L, 5536547L,
1452992L, 2001336L, 6166729L, 464144L, 2103027L, 370093L, 2508027L,
8993166L, 1143601L, 315067L, 3982752L, 3316996L, 721233L, 2976150L,
255849L)), row.names = 3:53, class = "data.frame")
Thanks much. I have my own source for turnout, if you check electproject.org :) and that is populated on the % 2016 turnout tab.
It would be nice to see how much turnout is up compared to 2016 at this time. Though I'm not sure if that data is available 🤷♀️