πŸ”– Want just the bare basics for Python?  Β·  See the study guide
πŸ”– BARE BASICS MODE β€” only the highlighted lessons below are your must-knows
LESSON 1

Variables & Data Types

Start here β€” Python stores data in variables.

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Read It Aloud β€” how every lesson works

Every line of code is broken down into plain language. Once you can say it out loud β€” in any language β€” you own it.

df[df['region'] == 'West'].groupby('product')['revenue'].sum()
df['region'] == 'West'β†’build a True/False mask β€” True for every West row
df[...]β†’filter the DataFrame β€” keep only rows where mask is True
.groupby('product')β†’split into groups β€” one group per unique product
['revenue']β†’focus on the revenue column only
.sum()β†’add up revenue within each group

Other Kits

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Lessons

12 lessons across three units. Each ends with a quiz, then drills.

Practice Drills

Five drill types, one per lesson. Mix them up or focus on a weak spot.

Python Terminal

Real Python β€” powered by Pyodide. Write pandas code and run it against the Contoso Coffee dataset.

⏳ Loading Python runtime… (first load ~5s, then cached)
df β€” sales (25 rows) products β€” 8 rows reps β€” 6 rows
contoso_coffee.py
Output will appear here…

Quick references

df.head() df.shape df.info() df.describe() df.dtypes
df['revenue'].sum() df.groupby('region')['revenue'].sum() df[df['units'] > 10] df.sort_values('revenue', ascending=False) df.isnull().sum()

Flashcards

Tap a card to flip it. Arrow through the deck.

Glossary