Indiana elections

What it covers

The Indiana scraper returns General Election results from the Indiana Election Division at enr.indianavoters.in.gov. It covers General Elections only (not primaries or special elections) from 2019 to the present.

Results are fetched from the FirstTuesday archive JSON API and include statewide candidate totals and county-level breakdowns for all Federal, State, and Local office categories.

Note: The Indiana site is a JSON API (no browser required). Scraping is fast relative to Playwright-based states. County-level data covers all 92 Indiana counties.

Indiana is the running example in the Example analyses vignette, which demonstrates filtering by office, counting party wins, margin calculations, and county-level swing analysis.

Arguments

Argument	Default	Description
`state`	—	`"IN"`, `"indiana"`, or `"Indiana"`
`year_from`	`NULL`	Start year, inclusive; `NULL` = no lower bound (clamped to 2019)
`year_to`	`NULL`	End year, inclusive; `NULL` = current calendar year
`level`	`"all"`	`"all"` — statewide + county; `"state"` — statewide only; `"county"` — county-level only

Examples

Statewide + county results for a single year

res <- scrape_elections(state = "IN", year_from = 2024, year_to = 2024)

# Statewide candidate totals
res$state %>%
  filter(office_level == "Federal") %>%
  select(election_year, office, candidate, party, votes, vote_pct, winner)

# County-level breakdown
res$county %>%
  filter(office == "President of the United States") %>%
  select(county_name, candidate, party, votes, vote_pct) %>%
  arrange(county_name, desc(votes))

Statewide totals only (faster — skips county scraping)

state_df <- scrape_elections(
  state     = "IN",
  year_from = 2024,
  year_to   = 2024,
  level     = "state"
)

state_df %>%
  select(election_year, office_level, office, candidate, party, votes, vote_pct, winner)

Multi-year scrape

res <- scrape_elections(
  state     = "IN",
  year_from = 2020,
  year_to   = 2024,
  level     = "state"
)

res %>%
  filter(office == "President of the United States") %>%
  select(election_year, candidate, party, votes, vote_pct, winner)

Filter to a specific county

res <- scrape_elections(state = "IN", year_from = 2024, year_to = 2024)

res$county %>%
  filter(county_name == "Marion") %>%
  select(office, candidate, party, votes, vote_pct) %>%
  arrange(office, desc(votes))

Filter by office level

res <- scrape_elections(state = "IN", year_from = 2024, year_to = 2024)

# Federal races only
res$state %>%
  filter(office_level == "Federal") %>%
  select(office, candidate, party, votes, vote_pct, winner)

# State races only
res$state %>%
  filter(office_level == "State") %>%
  select(office, candidate, party, votes, vote_pct, winner)

Output columns

`$state` (when `level = "all"` or `"state"`)

Column	Description
`state`	State abbreviation (`"IN"`)
`election_year`	Calendar year of the election
`election_date`	Date of the election
`election_type`	Always `"General"`
`office_level`	`"Federal"`, `"State"`, or `"Local"`
`office`	Office name (e.g. `"President of the United States"`)
`district`	District identifier; `NA` when not applicable
`candidate`	Candidate name as printed on the ballot
`party`	Full party name (e.g. `"Republican"`, `"Democrat"`)
`votes`	Statewide vote total
`vote_pct`	Percentage of votes within the contest
`winner`	`TRUE` if the candidate won
`num_seats`	Number of seats available in the contest

`$county` (when `level = "all"` or `"county"`)

Column	Description
`state`	State abbreviation (`"IN"`)
`election_year`	Calendar year of the election
`election_date`	Date of the election
`election_type`	Always `"General"`
`office_level`	`"Federal"`, `"State"`, or `"Local"`
`office`	Office name
`district`	District identifier; `NA` when not applicable
`county_name`	County name
`candidate`	Candidate name as printed on the ballot
`party`	Full party name
`votes`	County-level vote total
`vote_pct`	Percentage of votes within the contest for this county
`county_winner`	`TRUE` if the candidate won within this county
`num_seats`	Number of seats available in the contest

Performance notes

Fast scraper. Indiana uses a JSON API — no headless browser is required. A full statewide + county scrape for one year typically completes in under a minute.
General Elections only. The scraper covers General Elections only. Primary and special election results are not available through this source.
Local races. County-level data includes Local office races (county treasurer, clerk, etc.) in addition to Federal and State races.