LESSON 1

Variables & Data Types

Start here — Python stores data in variables.

1

Python Terminal

Run real pandas against the dataset live — the real muscle memory.

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Read It Aloud — how every lesson works

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

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

Other Kits

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Your Path

One step at a time, top to bottom. Nothing ahead is locked — dimmed just means it's coming up. The highlighted node is your next step.

Review

Every recall that's due, in one place — answer from memory first, flip when you can't.

Practice Drills

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

Python Terminal

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

⏳ Loading Python runtime… (first load ~5s, then cached)
df — sales (25 rows) products — 8 rows reps — 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()

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