R Package

The gerda R package provides tools to download and work with GERDA datasets directly in R. Current version: 0.5.0 (CRAN).

Installation

# Install from CRAN
install.packages("gerda")

# Or install development version from GitHub
devtools::install_github("hhilbig/gerda")

Main Functions

Data Loading

gerda_data_list(print_table = TRUE): Lists all available GERDA datasets with descriptions, including federal, state, municipal, European, mayoral, and county elections.
- print_table: If TRUE (default), prints a formatted table and invisibly returns a tibble. If FALSE, returns the tibble directly.
load_gerda_web(file_name, verbose = FALSE, file_format = "rds"): Loads a GERDA dataset from the web.
- file_name: Dataset name (see gerda_data_list() for options).
- verbose: Print loading messages (default FALSE).
- file_format: File format to download, "rds" or "csv" (default "rds").
- Includes fuzzy matching for file names and suggests close matches if exact match isn’t found.

Covariates

add_gerda_covariates(): Appends county-level socioeconomic indicators (population, unemployment, etc.) to election datasets. Use with piped data.
gerda_covariates(): Returns raw covariate data as a standalone dataset for manual merging.
gerda_covariates_codebook(): Returns the codebook with variable descriptions and metadata for all covariates.

Census 2022

add_gerda_census(): Merges municipality-level Census 2022 data with GERDA election data. Works with both municipality-level (direct merge on AGS) and county-level data (aggregated with population-weighted means for shares, sums for counts).
gerda_census(): Returns raw Census 2022 municipality-level data (~10,800 municipalities, 16 variables covering demographics, migration, households, housing, and rents).
gerda_census_codebook(): Returns the data dictionary for Census 2022 variables.

Party Mapping

party_crosswalk(party_gerda, destination): Maps GERDA party names to corresponding values from the ParlGov database.
- party_gerda: Character vector of party names.
- destination: Target column name from ParlGov crosswalk.

Usage Examples

library(gerda)

# List available datasets
gerda_data_list()

# Load harmonized municipal election data
municipal <- load_gerda_web("municipal_harm", verbose = TRUE)

# Load federal county data with socioeconomic covariates
federal_county <- load_gerda_web("federal_cty_harm") |>
  add_gerda_covariates()

# Add Census 2022 demographics to municipality-level data
federal_muni <- load_gerda_web("federal_muni_harm_21") |>
  add_gerda_census()

# Load new datasets
mayoral <- load_gerda_web("mayoral_harm")
european <- load_gerda_web("european_muni_harm")
county <- load_gerda_web("county_elec_harm_21")

# View covariate and census definitions
gerda_covariates_codebook()
gerda_census_codebook()

# Map party names to ParlGov
party_crosswalk(c("cdu_csu", "spd", "gruene"), "party_name_english")

Documentation

Feedback

Feedback is welcome. Please email hhilbig@ucdavis.edu or open an issue on GitHub.