In jw2249a/eavs: Data Tools for the Election Administration and Voting Survey

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%", 
  message = FALSE, warning = FALSE,
  knitr.table.format = 'markdown'
)

library(knitr)
library(eavs)
set.seed(20211014)

`eavs`: Election Administration and Voting Survey (2008-2020)

eavs is intended to help users download, match, and correct the biennial Election Administration and Voting Survey (EAVS), published by the U.S. Election Assistance Commission. This unique survey measures a variety of administrative practices that affect US elections. Currently working on mirroring the project elsewhere.

This package consolidates common questions across the different structures of the eavs. It provides functions that can help coalesce the data types and codes.

Installing and Loading the Package

You can install the development version from the GitHub repository.

remotes::install_github("jw2249a/eavs")
library(eavs)

OR clone the repository and install the script locally

library(devtools)
devtools::install()
library(eavs)

Introduction

To run the multiple functions that will clean and standardize the EAVS (without added corrections), run the create_eavs_years() command:

# Load All Years
# Takes a good deal of time
eavs <- create_eavs_years()  
dim(eavs)

# Just load 2008 and 2012
eavs <- create_eavs_years(years = c(2008, 2012))
dim(eavs)

The create_eavs_years() function is a relatively simple function that highlights the process to create the aggregated eavs. dplyr's bind_rows() function is used here for ease of displaying the function.

create_eavs_years <- function(years = seq(2008, 2020, 2), eavs.dir="data") {

  dplyr::bind_rows(lapply(years, function(year) {
    eavs <- fix_eavs_vars(read_eavs(year, data.dir=eavs.dir)
    eavs <- rename_eavs(eavs)
    eavs <- fix_types(eavs)
  }))
}

create_eavs_years()

This command assumes you have downloaded the EAVS already. IF you have not, then run the download_eavs() command. This will create a folder locally with the copies of the EAVS data (note: we are working on mirroring the repository for stability). You can also specify a directory using the extract.dir argument *note specifying a specific directory will require you to specify the eavs.dir argument in the create_eavs_years() function.

# Just load 2008 and 2012
download_eavs(years = c(2008, 2012), extract.dir = "unique.dir")
eavs2008_12 <- create_eavs_years(years = c(2008, 2012), eavs.dir = "unique.dir")