Downloads and extracts compressed data files from the ineAtlas data repository, providing access to various socioeconomic indicators at different geographic levels.
Usage
get_atlas(category, level, cache = TRUE, cache_dir = tempdir())Arguments
- category
Character string specifying the data category. Must be one of: "income", "income_sources", "demographics", "distribution_sex", "distribution_sex_age", or "distribution_sex_nationality"
- level
Character string specifying the geographic level. Must be one of: "municipality", "district", or "tract"
- cache
Logical indicating whether to cache the extracted data. Default is TRUE. Cached data is stored uncompressed for faster access.
- cache_dir
Character string specifying the cache directory. Default is tempdir().
Value
A tibble containing the requested data. Distribution data will include additional columns for demographic breakdowns (sex, age, nationality). The data is automatically extracted from compressed files and cached locally if requested.
Note
Data files are stored compressed on the repository to reduce size and download times. The function handles decompression automatically.
Examples
# \donttest{
# Get municipality level income data
income_data <- get_atlas("income", "municipality")
#> Downloading data from income_municipality.zip...
#> Caching data to ineatlas_income_municipality.csv
#> Data successfully loaded: 65008 rows, 11 columns
# Get district level demographics without caching
demo_data <- get_atlas("demographics", "district", cache = FALSE)
#> Downloading data from demographics_district.zip...
#> Data successfully loaded: 84128 rows, 13 columns
# Get income distribution indicators by sex
sex_dist <- get_atlas("distribution_sex", "municipality")
#> Downloading data from distribution_sex_municipality.zip...
#> Caching data to ineatlas_distribution_sex_municipality.csv
#> Data successfully loaded: 194235 rows, 15 columns
# Get income distribution indicators by sex and age
age_dist <- get_atlas("distribution_sex_age", "district")
#> Downloading data from distribution_sex_age_district.zip...
#> Caching data to ineatlas_distribution_sex_age_district.csv
#> Data successfully loaded: 753552 rows, 17 columns
# }