Week 1: code along

Cultural Data Analysis · Lecture 1: Data Analysis with Python

Interactive tools from this lecture: CPU simulator · Loops in four languages

This week's workshop: Python

Today has three parts. In each part, type the code examples from the slides yourself as we go: keep this page open next to a blank Python Tutor (choose Python 3). One exercise, NumPy, runs in Google Colab instead. The slides show the number of each exercise in their top corner.

At the end of each part, a Let's try slide sends you to the matching section of the lecture notebook: there you run the same ideas in Colab and go a bit further. Open it once now and choose File → Save a copy in Drive, so that your changes are kept. Each part below ends with a link to its section.

There are two kinds of exercise:

Type and trace (Python Tutor): short pieces of plain Python. Predict what will happen, type the code by hand (the typos are part of the lesson), then click Visualize Execution and press Next to step through it.
Copy and run (Google Colab): longer code with libraries such as pandas and scikit-learn. Predict the result, then copy the code into Colab and run it. Read the New note: it explains the lines you have not seen before. You don't need to be able to write the rest yet.

Then check your result against the expected output, and try the follow-up under Then.

Python Tutor runs plain Python only, so it cannot import NumPy or pandas. Use Google Colab for those. Python Tutor: pythontutor.com · Computer Programming Spectrum

Week 1: code along

Contents