ineAtlas

Lifecycle: experimental CRAN status R-CMD-check GitHub release CodeFactor

The goal of ineAtlas is to provide easy access to granular socioeconomic indicators from the Spanish Statistical Office (INE) Atlas de Distribución de Renta de los Hogares (Household Income Distribution Atlas). This dataset combines administrative tax data with population statistics to provide detailed information about the income distribution and related socioeconomic indicators at the municipal, district, and census tract levels.

Data structure

The data is organized into several categories and is available at three geographic levels:

Available datasets

Dataset Description
Income Income indicators including net/gross (equivalised) income per capita
Income sources Income indicators by source (wages, pensions, benefits, etc.)
Demographics Population characteristics including age structure and household composition
Distribution by sex Income distribution indicators disaggregated by sex
Distribution by sex and age Income distribution indicators by sex and age categories
Distribution by sex, age and nationality Income distribution indicators by sex and nationality status
Inequality indicators Inequality metrics including Gini coefficient and P80/P20 ratio

All the data is stored in the accompanying ineAtlas.data repository. You can find the data dictionary and more information about the data structure at https://pablogguz.github.io/ineAtlas.data/.

Installation

You can install the development version of ineAtlas from GitHub with:

# install.packages("pak")
pak::pak("pablogguz/ineAtlas")

Example

Here’s a basic example of fetching census tract-level income data:

library(ineAtlas)

# Get municipality-level income data
income_data <- get_atlas("income", "tract")

# View the first few rows
head(income_data)

Contributing

Contributions are welcome! Please feel free to submit a pull request. For major changes, please open an issue first to discuss what you would like to change.

References

Spanish Statistical Office (2024). Household Income Distribution Atlas. Retrieved from https://www.ine.es/en/experimental/atlas/experimental_atlas_en.htm/ [Accessed October 29, 2024]

Latest data release: October 29, 2024

Author

Pablo García Guzmán
EBRD