Add latamdata-py – one-line access to 38 Latin American research datasets

.github/workflows/check-links.yml

@@ -0,0 +1,18 @@
+name: Check for broken links
+on:
+  push:
+    branches: [ main, master ]
+  pull_request:
+    branches: [ main, master ]
+  schedule:
+    - cron: '0 9 * * 1'
+jobs:
+  check-links:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Link Checker
+        uses: lycheeverse/lychee-action@v1.8.0
+        with:
+          args: --verbose --max-retries 3 --timeout 10 '**/*.html' '**/*.md'
+          fail: true

CITATION.cff

@@ -0,0 +1,12 @@
+cff-version: 1.2.0
+message: "If you use this software or dataset, please cite it as below."
+type: software
+authors:
+  - family-names: "de la Serna"
+    given-names: "Juan Moisés"
+    orcid: "https://orcid.org/0000-0002-8401-8018"
+    affiliation: "Universidad Internacional de La Rioja (UNIR)"
+title: "awesome-python-data-science"
+version: "1.0.0"
+date-released: "2026-04-06"
+url: "https://github.com/juanmoisesd/awesome-python-data-science"

README.md

@@ -487,6 +487,7 @@
 * [cleanlab](https://github.com/cleanlab/cleanlab) - The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
 * [snorkel](https://github.com/snorkel-team/snorkel) - A system for quickly generating training data with weak supervision.
 * [dataprep](https://github.com/sfu-db/dataprep) - Collect, clean, and visualize your data in Python with a few lines of code.
+* [latamdata-py](https://github.com/juanmoisesd/latamdata-py) - One-line access to 38 open research datasets from Latin America (health, neuroscience, mental health, economics). Real-world data for research and ML.
 
 ### Synthetic Data
 
@@ -565,3 +566,12 @@ Read the <a href=https://github.com/krzjoa/awesome-python-datascience/blob/maste
 
 ## License
 This work is licensed under the Creative Commons Attribution 4.0 International License - [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+
+## How to Cite
+
+If you use this repository in your research, please cite:
+
+> de la Serna, J. M. (2026). *Awesome Python Data Science*. Universidad Internacional de La Rioja (UNIR).
+> https://github.com/juanmoisesd/awesome-python-data-science 
+
+See `CITATION.cff` for formatted references.