Indonesia514: A Data Science Repository to Study Regional Development across 514 Districts in Indonesia

Welcome to Indonesia514! This project centralizes geospatial data and regional-economic indicators — including GDP, investment, and government spending — for the 514 districts of Indonesia. All datasets share a single common identifier, districtID, so they can be merged into a unified analytical table.

This repository is organized for researchers and data scientists interested in:

• Regional Economics: Measuring district-level growth, capital formation, and fiscal policy.
• Spatial Analysis: Linking economic indicators to district geometries for mapping and spatial econometrics.
• Reproducible Workflows: Streaming open datasets directly into Python via a single join key.

⚙️ Active development. This repository is an early-stage draft. The district boundaries are complete in GeoJSON format and the bilingual website (English / Bahasa Indonesia) is live, but the economic datasets currently ship sample data for 16 districts — the full 514-district series are pending. Interactive dashboards and analytical notebooks are planned and not yet published.

💾 Datasets

Curated datasets organized into modules, all linked by a unique identifier (districtID).

⚠️ Important Note on Identifiers: The primary key for joining all datasets in this repository is districtID. The GDP, GFCF, and government-spending files currently contain a 16-district sample; the full 514-district data are being added. Always treat districtID consistently (as an int or string) across both dataframes before merging.

🐍 Quick start

Stream the datasets directly from GitHub and merge them on districtID with pandas. You can run the code below in a blank Google Colab scratchpad — no setup or installation required.

import pandas as pd

# -----------------------------------------------------------------------------
# 1. SETUP: Define the raw GitHub URL to stream data directly into Pandas.
# -----------------------------------------------------------------------------
REPO_URL = "https://raw.githubusercontent.com/quarcs-lab/indonesia514/main"

# -----------------------------------------------------------------------------
# 2. LOAD: Read the economic CSVs.
# -----------------------------------------------------------------------------
df_gdp  = pd.read_csv(f"{REPO_URL}/gdp/gdp.csv")
df_gfcf = pd.read_csv(f"{REPO_URL}/gfcf/gfcf.csv")
df_gs   = pd.read_csv(f"{REPO_URL}/gs/gs.csv")

# -----------------------------------------------------------------------------
# 3. MERGE: Combine the indicators on the common district identifier.
# -----------------------------------------------------------------------------
df = pd.merge(df_gdp,  df_gfcf[['districtID', 'gfcf_2022']], on='districtID')
df = pd.merge(df,      df_gs[['districtID', 'gs_2022']],     on='districtID')

📜 Citation

If you use this repository in your research, please cite it using the following metadata.

APA Format

Mendez, C., Abdulah, R., Arvianto, B., & Leiva, F. (2026). Indonesia514: A data science repository to study regional development in Indonesia. GitHub. https://github.com/quarcs-lab/indonesia514

BibTeX Format

@misc{indonesia5142026,
  author = {Mendez, Carlos and Abdulah, Rusli and Arvianto, Bimo and Leiva, Favio},
  title = {{Indonesia514}: A Data Science Repository to Study Regional Development in Indonesia},
  year = {2026},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/quarcs-lab/indonesia514}}
}

License

This repository is released under the MIT License, permitting broad reuse with proper attribution.

🤝 Contributing

We welcome contributions! If you are adding full-district data, fixing a Coordinate Reference System (CRS) issue, building a new notebook, or integrating fresh indicators, please submit a Pull Request.