Episode 8 — The Data Room
Programming with Python · Tutorial 08
The investor wasn’t impressed by a slide. She was impressed by data. So she slides a USB stick across the table: every order, two full weeks. “Impress me.” That stick is now a real file, orders.csv, with eighty rows: too many to eyeball, too many for a hand-written loop. This week you learn the tool built for exactly this: pandas. You’ll load a whole spreadsheet into one DataFrame, filter it with boolean masks, combine conditions with &, add a derived column on a safe copy, and answer per-zone questions with groupby. Kevin, meanwhile, has discovered AI. Your real job is to supervise it and catch the confident nonsense.
Work on the notebook
Open in browser (recommended): runs entirely on your machine, in this tab: no account, no installation, and after it loads no internet is needed.
This lab loads pandas, which is fetched over the network the first time. If the notebook fails to boot with a network error, reload the page once (Cmd/Ctrl + R). That almost always fixes it.
Your progress lives in this browser tab. If you reload the page (Cmd/Ctrl + R) your work is still there. But if you close the tab and open the link again later, you start from a clean notebook. There is no cross-device sync in the browser, and clearing browser data or private mode also wipes it.
So: download your .py before you leave (menu → Download → Download Python code). That download is the only guaranteed copy. Handing in files works exactly like this in the checkpoints, so you get to practice the motion every week. Note: a downloaded .py is for submission and backup. You can’t upload it back into the browser editor.
Open in molab: marimo’s free cloud (account required). Your copy saves to your account and reopens on any device. Choose this if you know you’ll switch computers or want to be certain nothing is lost. Optional: nothing graded ever requires it.