SenateData: A Functional Tool for the SenateData Dataset

SenateData is a package designed to allow a user with only basic knowledge of R interact with SenateData, a dataset with over 960 variables that compiles information about all US Senators and state-years across 1789-2025, and its codebook. The dataset tracks state characteristics, Senators, and the behavior of those Senators in policymaking. Users can find variables related to state- and member-level demographics, politics, and policy; subset the data across multiple dimensions; create custom aggregations of the dataset; and access citations in both plain text and BibTeX for every variable.

Installing this Package

SenateData is a functional package that interacts with the SenateData dataset via the internet. Install the package from GitHub like so:

# use the devtools library to download the package from GitHub
library(devtools)

# if there are issues or you only want to download SenateData
install_github("ippsr/SenateData")

Finding Variables

get_var_info: Retrieve information regarding variables in SenateData and identify variables of interest with get_var_info. The function allows you to search to codebook to find the years each variable is observed in the data; a short and long description of each variable; and the source and citation/s for each variable. Citations are available in both bibtex and plain text. Use the function to search for broad terms like ‘tax’ with the related_to argument and/or partial-match variable names with var_names.

suppressMessages(library(dplyr))
library(SenateData)
#> Please cite:
#> Yoel, Benjamin, and Iliya Liampert. 2025. SenateData Project. V.1.0. IPPSR. 
#> 
#> Run `SenateData::get_senate_version()` to print the version of SenateData
#> the package is using.

get_var_info returns the following information to simplify using SenateData:

• variable: Variable name
• year: The precise years the variable is observed
• short_desc: A short description of the variable
• long_desc: A long description of the variable
• source: The sources of the data
• category: the variable’s category (not all are coded)
• plaintext_cite[1-4]: Plain text citation(s) for the data
• bibtext_cite[1-4]: BibTeX citation(s) for the data

Accessing SenateData

get_senate_data: Access all or a part of SenateData with get_senate_data. Subset by state names with state and years with years (either a single year or a two-year vector that represents the min/max of what you want). You can also use the related_to argument to search across variable names, short/long descriptions from the codebook, and citations for non-exact matches of a supplied term. For example, searching ‘tax’ will return variables with words like ‘taxes’ and ‘taxable’ in any of those columns.

# load the entire dataset
all_the_dat <- get_senate_data()

# subset by state, topic, and years
sen_subset <- get_senate_data(states = c("Indiana","Kentucky","Michigan")
                             ,related_to = "tax"
                             ,years = c(1960,1980))

Pulling Citations

get_var_info: Each variable in SenateData was collected from external sources, please use get_var_info to obtain their citations (plain text and BibTeX). We’ve made it easy to cite the source of each variable you use with the get_var_info function described above. Supply a vector of variable names to the function with the var_names function and collect the citations provided in the plain text or BibTeX columns. NOTE: Some variables have multiple citations, so do check you have them all.

# bibtex is also available
get_var_info(var_names = "num_bills") %>%
  pull(plaintext_cite)
#> [1] "E. Scott Adler and John Wilkerson, Congressional Bills Project: 1973-2016, NSF 00880066 and 00880061.\n"

# bibtex is also available
get_var_info(var_names = "popfemale") %>%
  pull(plaintext_cite)
#> [1] "CQ Press. ’State Stats: Population under 5 years old.’ http://library.cqpress.com/cqresearcher/index.php."

Dataset and Package Citation

In addition to citing each variable’s source, we ask that you cite SenateData if use this package or the dataset:

Yoel, Benjamin, and Iliya Liampert. 2025. SenateData Project. V.1.0. IPPSR.

Contact

Benjamin Yoel - PhD Candidate, Michigan State University, and Predoctoral Fellow, Johns Hopkins University

Iliya Liampert - PhD Student, Michigan State University