This is a full pandas course for the Swiftener Pandas editor. Pandas is already imported as pd. NumPy is np. You type in that tab, press Ctrl+Enter (or Cmd+Enter), and read the console.

You do not install Python, pip, or Jupyter. Code and uploaded files stay in your browser.

Goal

Finish every chapter by running the copy-paste blocks in the workbench. The last chapter is a small sales pipeline you can reuse.

How to take the course

Keep this tutorial tab and the Pandas workbench side by side.
Wait until the workbench status says pandas is ready.
Copy an exercise, paste it as the whole editor, run it, then read the printed table. Each shaded block is a complete script — it does not rely on leftover variables.
When a chapter asks for a file, download it from the buttons above, then click Add files in the workbench.

The workbench Snippets menu is a cheat sheet. Prefer the exercises here — they are written for this editor.

What this editor can and cannot do

Can: DataFrames, Series, CSV / Excel / JSON, print, writes to /uploads, downloads.
Cannot: matplotlib plots, notebooks, installing extra PyPI packages beyond what the app already loads (pandas, numpy, openpyxl).
Always print(...) a result. A bare df at the end of a cell is not displayed the way Jupyter would.

Sample files

Download any of these from the banner, then attach them with Add files:

sales.csv — tiny city × product snapshot (also has a revenue column)
sales_log.csv — dated sales rows, including product C
products.csv — product category and cost
regions.csv — city to region lookup
messy.csv — dirty names, mixed dates, missing scores, a duplicate

Chapter list

Work in order the first time. After that, jump around from the sidebar.