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Learn SciPy

How this course works, what the workbench can do, and the chapter list.

This is a SciPy course for the Swiftener SciPy editor. NumPy is np, matplotlib is plt. Arrays belong in Learn NumPy. Models belong in Learn scikit-learn. This course stays on scientific algorithms.

Goal

Finish every chapter by running the copy-paste blocks. The last chapter is a rainfall fit you can reuse.

How to take the course

  1. Keep this tutorial tab and the SciPy workbench side by side.
  2. Wait until the status says SciPy is ready.
  3. Paste each exercise as the whole editor. Always print. Call plt.show() when you plot.

What this editor can and cannot do

  • Can: numpy, scipy, matplotlib, print, CSV uploads, plt.savefig chips.
  • Cannot: pandas tables (use the pandas course), sklearn estimators, fetching URLs.

Sample files

  • signal.csv — x,y for a line plus noise
  • temps.txt — Nairobi-ish daily max °C
  • weights.csv — city rainfall millimetres

Chapter list