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README.Rmd
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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# politicaldata
[](https://travis-ci.com/elliottmorris/politicaldata)
[](https://cran.r-project.org/package=politicaldata)
[](https://cran.r-project.org/package=politicaldata)
[](https://cran.r-project.org/package=politicaldata)
[](https://cran.r-project.org/package=politicaldata) Dev: v0.1.3
A R package for acquiring and analyzing political data — including polls, election results, legislator information, and demographic data.
Author: [G. Elliott Morris](https://www.thecrosstab.com)
For more, visit the package documentation website [here ](https://elliottmorris.github.io/politicaldata/), especially the [the vignette](https://elliottmorris.github.io/politicaldata/articles/politicaldata.html).
For _even_ more, see [the package’s project description my blog](https://www.thecrosstab.com/project/politicaldata-package/) or [view the vignettes](https://github.com/elliottmorris/politicaldata) *(vignettes area work in progress)*. You can find many examples of how these data are used in the real world via my interactive R course at DataCamp.com, [“Analyzing Election and Polling Data in R”](https://www.datacamp.com/courses/analyzing-election-and-polling-data-in-r).
For _even even_ more, I'm in the process of writing a detailed guide on using R for analyzing political data, [*Analyzing Political Data in R *](https://elliottmorris.github.io/R-political-data-book/), that uses many of the functions and datasets from this package. The example use cases extend beyond those in the function documentation and this readme.
# Installation
Install the `politicaldata` package from CRAN:
```r
# install politicaldata from CRAN
install.packages('politicaldata')
# load the politicaldata package
library(politicaldata)
```
As the landscape of online data and API calls is constantly changing, the development version is likely to contain quicker bug fixes and integration of new data. You can instill the dev version using the `remotes::install_github()` workflow outlined here:
To get the current development version from GitHub:
```r
# install the remotes package if it's not already
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
# install dev version of politicaldata from github
remotes::install_github("elliottmorris/politicaldata")
# load the politicaldata package
library(politicaldata)
```
# Usage
This package provides a variety of functions for quickly accessing different data sources used in political science and analytics. For example, you can download a data.frame of the DW-NOMINATE scores of congressional ideology computed by the [VoteView](https://voteview.com) project at UCLA:
```{r example}
# import the package
library(politicaldata)
# download the NOMINATE scores for the 116th House
house_ideo <- get_house_nominate(congress = 116)
# download the NOMINATE scores for the Senate in the 116th Congress
senate_ideo <- get_senate_nominate(congress = 116)
# take a look with dplyr::head()
suppressMessages(library(dplyr))
head(house_ideo[1:5])
```
**A list of functions:**
- `get_house_nominate()` returns [DW-NOMINATE](https://www.voteview.com/about) ideology scores for each member of the U.S. House of Representatives for a specified congress, else every Representative ever.
- `get_senate_nominate()` returns [DW-NOMINATE](https://www.voteview.com/about) ideology scores for each member of the U.S. Senate for a specified congress, else every Senator ever.
- `trump_approval_polls_538()` returns a dataset of approval polls [aggregated by](https://projects.fivethirtyeight.com/trump-approval-ratings/) the folks over at FiveThirtyEight.
- `get_cap_mip()` returns a historical dataset of the aggregated responses to Gallup's Most Important Problem questions, coded by major topic. Part of a suite of functions for obtaining data from the [Comparative Agendas Project](https://www.comparativeagendas.net).
**A list of datasets:**
- `house_116` is a saved copy of the output from `get_house_nominate(congress=116)` run on the last day the package was updated (and thus should only be used for demos, unless you want outdated data).
- `senate_116` is the same as the above, bur for the Senate. Downloaded via `get_senate_nominate(congress=116)`.
- `us_polls_history` is a dataset of US presidential election polling from the 1980 through 2016 elections.
- `house_results` is a dataset of results for elections to the US House of Representatives that occurred from 1976 to 2018
- `pres_results_by_cd` is a dataset of results for presidential elections broken down by congressional district from 1990 to 2016
# Vignettes
There are vignettes. They are in the package documentation. You can see them online in this repository or the docs [website](https://elliottmorris.github.io/politicaldata/).
# Suggested related packages:
- `Rvoteview` provides functions for obtaining roll call voting data, which can thus be analyzed using algorithms from the `pscl` package.
- `ropercenter` allows you import data from the Roper Center's iPoll directly in R, given that you know the slug of the interested poll.
- `fivethirtyeight` was developed to distribute the data behind the popular data journalism website, and thus will have some overlap. FiveThirtyEight also releases most of their data [on GitHub](https://github.com/fivethirtyeight/data).
- `pollstR` provides a way to access the aggregate toplines from Huffington Post Pollster, which is sadly no longer being updated.
# Contributions
You should feel free to suggest more data and/or functions to add, open issues, submit pull requests, etc.
# Contact
You can reach me by opening an issue, on [Twitter](https://www.twitter.com/gelliottmorris), or via email (but I'd prefer you to communicate primarily via GitHub).
# License
This package is open source and released under the MIT License, which only stipulates that you must distribute the License alongside the package. For more details, click on "See License" at the top right of the repository.