# getting_started

# Getting started with countyhealthR

    library(countyhealthR)

# — 1. Explore available measures —

# See all County Health Rankings & Roadmaps measures for a given release year

    list_chrr_measures(release_year = 2024)  # useful for discovering measure IDs or names

# — 2. Pull county-level data —

# Examine ALL health measures for a specified location

# Example: county-level data for Dane County, Wisconsin

    county_data <- get_chrr_county_data(
      state = "WI",
      county = "Dane",
      release_year = 2025
    )
    head(county_data)

# — 3. Pull measure-level data —

# Examine one health measure across a specified geographic unit

# Example: “Uninsured adults” across all US counties

    measure_data <- get_chrr_measure_data(
      geography = "county",
      measure = "uninsured adults",
      release_year = 2022
    )
    head(measure_data)

# — 4. Get metadata for a measure —

# See details about a measure including description, precision, and years represented

    meta_data <- get_chrr_measure_metadata(
      measure = "Uninsured adults",
      release_year = 2024
    )
    head(meta_data)

# Note:

All functions are build to interact with Zenodo and therefore require internet access. As a result, examples are wrapped in `\donttest{}` so that CRAN checks do not depend on external network access.