Python, R, Julia & AI for Development

Data Science for
Development Studies

An open collection of computational notebooks and interactive apps that introduce data science methods—from basic statistics to machine learning—in the context of development studies. Run Python, R, and Julia directly in the cloud.

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Zero Installation • Python, R & Julia • Interactive Learning

Data Science for Development Studies

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Notebooks

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Interactive Apps

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Languages

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Cloud-based

Why ds4ds?

An open collection that bridges the gap between modern data science tools and development studies research — making computational methods accessible to researchers, students, and practitioners.

Foundational Concepts

Statistics, econometrics, causal inference, and machine learning with clear explanations and real-world examples.

Computational Notebooks

Run Python, R, and Julia code directly in your browser via Google Colab, with no environment setup required.

Applied Development Studies

Real-world datasets from Brazil, Bolivia, and the Gapminder project. Spatial analysis, growth models, and policy evaluation.

Notebooks & Apps (18 resources)

Interactive computational resources organized by topic.

Basic Statistics and Econometrics (7)

Gapminder introduction to data science

Python

Explore life expectancy, GDP, and population with the Gapminder dataset

Mendez C. (2024)

Open In Colab

Gapminder introduction to data science

Julia

Explore life expectancy, GDP, and population with the Gapminder dataset

Mendez C. (2025)

Open In Colab

Gapminder introduction to data science

R

Explore life expectancy, GDP, and population with the Gapminder dataset

Mendez C. (2026)

Open In Colab

Introduction to statistical differences and relationships

Python

Learn t-tests, chi-squared tests, and correlation analysis

Mendez C. (2025)

Open In Colab

Statistics is about differences, relationships, and predictions

Python

From hypothesis testing to regression predictions in one workflow

Mendez C. (2025)

Open In Colab

Descriptive statistics and multi-boundary mapping

Python

Summary statistics and choropleth maps across administrative boundaries

Mendez C. (2024)

Open In Colab

Use regressions to explore relationships

Python

OLS regression, diagnostics, and interpretation for development data

Mendez C. (2025)

Open In Colab

Economic Growth and Development (4)

Introduction to growth equations

Python

Growth rates, log-linear models, and cross-country comparisons

Mendez C. (2025)

Open In Colab

The Solow growth model and its convergence prediction

Python

Simulate the Solow model and test its convergence prediction

Mendez C. & Leiva F. (2023)

Open In Colab

The Solow growth model and its convergence prediction

R

The same Solow model and convergence analysis implemented in R

Mendez C. (2023)

Open In Colab

Convergence clubs in labor productivity and its proximate sources

R

Identify groups of economies converging to different steady states

Mendez C. (2021)

Open In Colab

Exploratory Data Analysis (1)

Exploratory spatial data analysis of municipal development in Bolivia

Python

Spatial autocorrelation, Moran's I, and LISA maps for Bolivia

Mendez C. (2024)

Open In Colab

Causal Inference (3)

Introduction to directed acyclical graphs (DAGs)

R

Use causal diagrams to identify confounders and guide regression design

Mendez C. (2025)

Open In Colab

Heterogeneous treatment effects via two-stage DID

R

Estimate heterogeneous treatment effects using two-stage DID

Mendez C. (2024)

Open In Colab

Synthetic control explorer

App

Build counterfactuals using weighted combinations of control units

Mendez C. (2025)

Open App

Machine Learning (2)

Introductory machine learning for econometrics: Exploring the Mincer equation

Python

Compare OLS, Lasso, Random Forest, and XGBoost on earnings data

Mendez C. (2025)

Open In Colab

An interactive app to learn SHAP plots with XGBoost predictions

App

Interactively explore SHAP plots to understand XGBoost predictions

Mendez C. (2025)

Open App

Spatial Econometrics

Coming soon

Bayesian Econometrics

Coming soon

Feature Engineering and Geocomputation (1)

Regional dynamics of luminosity-based GDP using Google Earth Engine

GEE

Map regional GDP dynamics using nighttime lights in Google Earth Engine

Mendez C. (2025)

Open in Earth Engine

People

Editors

Carlos Mendez

Carlos Mendez

Associate Professor, Nagoya University, Japan

Visit Website

Contributors

Favio Leiva Cardenas

Favio Leiva Cardenas

PhD Student, Nagoya University, Japan

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Community

We're using Github Discussions as a place to connect with other members of our community. We hope that you:

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Events

We invite community members and newcomers to participate in our public events. Join us to learn, collaborate, and build together:

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How to Cite

Mendez C. (2026) Data Science for Development Studies: An Open Collection of Computational Notebooks and Apps. Zenodo. https://doi.org/10.5281/zenodo.15250204 Website: https://cmg777.github.io/ds4ds

BibTeX

@collection{mendez_2026_ds4ds,
  author       = {Mendez, Carlos},
  title        = {Data Science for Development Studies: An Open Collection of Computational Notebooks and Apps},
  year         = {2026},
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.15250204},
  url          = {https://cmg777.github.io/ds4ds}
}

Resources

Extend your learning with additional materials and tools.

Google Colab

Free cloud-based Jupyter notebooks for Python and R.

Get Started

Our World in Data

Explore global development data and research.

Explore

Google Earth Engine

Cloud-based geospatial analysis platform for satellite data.

Learn More

Art of Stat

Interactive web apps for learning statistics concepts.

Try Apps

QuantEcon

Python Programming Lectures for Economics and Finance by Sargent & Stachurski.

View Lectures

QuantEcon DataScience

Introduction to Economic Modeling and Data Science by Coleman, Lyon & Perla.

View Lectures

QuantEcon Intro

A First Course in Quantitative Economics with Python by Sargent & Stachurski.

View Lectures

QuantEcon Intermediate

Intermediate Quantitative Economics with Python by Sargent & Stachurski.

View Lectures

QuantEcon Julia

Quantitative Economics with Julia by Perla, Sargent & Stachurski.

View Lectures

URFIE

Introductory Econometrics in R, Python & Julia with Code Examples.

Explore

DS4Bolivia

Spatial Data Science Repository for Sustainable Development Analysis in Bolivia.

Explore