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Code Studio

Code Studio

Learn the languages and tools of development data work by doing it. Write and run R, Python and SQL in your browser with nothing to install, then follow guided courses for the desktop software your organisation already uses.

Two kinds of course. The first group runs real code in your browser: R through WebR, Python through Pyodide, SQL through SQLite. The engine downloads once, on your first Run, and stays loaded while the page is open. The second group teaches software that cannot run in a browser, such as Stata and QGIS. Those courses show you the commands and the steps, and tell you what to look for on your own screen; they do not pretend to run the software for you.

Run code in your browser

Nothing to install. A small illustrative household survey is loaded into every environment.

Runs in your browser

R & Python for Development

Both languages side by side, from your first line of code to a regression on a household survey.

Runs in your browser

Tidyverse for Development Data

dplyr, tidyr, readr and ggplot2 on a 240-household survey: filter, summarise, join to districts, reshape indicator tables, weight and chart.

Runs in your browser

pandas for Development Data

DataFrames, groupby, merge, melt and pivot, weights with numpy and matplotlib charts on a 240-household survey.

Runs in your browser

SQL for Development Data

Query household and district tables with SQLite in your browser, from SELECT to window functions.

Runs in your browser

Shiny Dashboards for Development Data

Build a filterable district dashboard in R and Python Shiny, opened in Shinylive.

Guided tool courses

Step-by-step courses for software you install or use online, with the commands written out.

Stata

Stata Syntax for Development Data

Do-files from import to svyset and margins, on a household survey you can download and follow along with.

SPSS

SPSS Syntax for Development Data

Syntax files from GET DATA to Complex Samples and REGRESSION, with every step you can paste from a menu.

jamovi and JASP

jamovi and JASP: Free Point-and-Click Statistics

Free, open-source alternatives to SPSS, built on R: from opening a CSV to regression and Bayes factors.

OpenRefine

OpenRefine: Cleaning Messy Survey and MIS Data

Facets, clustering for district and village names spelt five ways, GREL, and a cleaning you can replay.

Open Data Editor

Open Data Editor: Checking a Dataset Before You Share It

A no-code check of a CSV before you share it: error report, fixes, metadata rules and export.

QGIS

QGIS: Maps for Development Data

District boundaries, a CSV join that survives spelling differences, honest classes and legends, and a print layout.

KoboToolbox and ODK

KoboToolbox and ODK: Building Survey Forms with XLSForm

XLSForm from the ground up: skip logic, constraints, Hindi labels, rosters, offline collection and encryption.

Excel and Google Sheets

Spreadsheets for M&E

Tidy sheets, validation, XLOOKUP, COUNTIFS indicator tables, pivots, weighted means, with R and Python checks.

Git and Quarto

Git and Quarto: Reproducible Reports

Commit, branch and push; keep personal data out of Git; render one Quarto template into ten district profiles.