R & Python for Development

Your first line of code

Two languages run almost everything in development-sector data work: R (loved by statisticians and evaluators) and Python (loved by data scientists and engineers). You do not have to choose — this course teaches both, side by side, so you can read either one and pick what your team uses.

Everything here runs inside this page. Click Run and the code executes in your browser — nothing is installed and nothing is sent to a server.

1 · Make the computer say something

The most basic thing code does is print — show a value on screen. In both languages the command is print(...). Text goes inside quotes. Press Run, then switch the tab from R to Python and Run again.

Notice how similar they are. That similarity is the whole reason we can teach them together — the ideas are the same; only small details of spelling differ.

2 · A tiny piece of real analysis

Say you surveyed five people and recorded their ages. Let's store those numbers and compute the average (mean) — the workhorse of any baseline report.

In R a list of numbers is made with c(...) (for "combine") and the average is mean(...). In Python we use a list [...] and compute sum(...) / len(...). Run both.

3 · Your turn

Change the numbers below to a small dataset of your own — maybe household sizes, or the number of children in five families — then Run. Try it in both R and Python.

Where this course goes

This is the pilot lesson. The full 101 continues with real South Asian datasets — NFHS, ASER, PLFS, Census, Union Budget — building from "hello" to running an actual impact evaluation.