Lesson 2 of 3

Module 2 · pandas Quick Start

Clean, Filter and Calculate

Fix column types, add a revenue column, filter rows that match a condition and sort the results.

About 15 minutes

Open in ColabEvery example as a notebook you can run, edit and save to your Google Drive.

Fix the date column

Dates loaded as text can't be sorted or grouped by month properly. Convert them:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

order_date is now datetime64. You can pull out parts of the date:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Add a revenue column

Revenue for each line is quantity × unit price, minus the discount:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Total revenue is ₦830,541,245. Notice there's no loop: pandas does the maths for every row at once.

Revenue calculated for three example rows by one line of vectorised maths, and a text date converted to a real date so the year and month can be pulled out — One line of maths fills a whole new column; real dates let you pull out year and month.TapClick the image to see it full size.

Filter rows

Put a condition inside square brackets to keep only the matching rows:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Combine conditions with & (and) or | (or), with brackets around each one:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

A condition on quantity gives True or False for each of five rows, and only the True rows are kept; combining conditions with & and | and brackets — A condition makes a True/False mask; only the True rows are kept.TapClick the image to see it full size.

Sort

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

This shows the five biggest order lines. Use ascending=True (the default) for smallest first.

Check for problems

Real data is rarely this clean. These checks are worth running on any dataset:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

This dataset passes all three, but make it a habit.

Try it

Continue in the same notebook, after adding the year, month and revenue columns.

Practice

How many order lines had a 10% discount?

orders.csv

Practice

How much revenue did those 10%-discount lines bring in? (A rounded figure is fine.)

orders.csv

Practice

What is the revenue of the biggest single order line in 2026?

orders.csv

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Take the module check

Questions on this module. Pass and you earn the Data Cleaning with Python badge, free.

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Lesson 2 of 3

Module 2 · pandas Quick Start

Clean, Filter and Calculate

Fix column types, add a revenue column, filter rows that match a condition and sort the results.

About 15 minutes

Open in ColabEvery example as a notebook you can run, edit and save to your Google Drive.

Fix the date column

Dates loaded as text can't be sorted or grouped by month properly. Convert them:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

order_date is now datetime64. You can pull out parts of the date:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Add a revenue column

Revenue for each line is quantity × unit price, minus the discount:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Total revenue is ₦830,541,245. Notice there's no loop: pandas does the maths for every row at once.

Filter rows

Put a condition inside square brackets to keep only the matching rows:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Combine conditions with & (and) or | (or), with brackets around each one:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

Sort

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

This shows the five biggest order lines. Use ascending=True (the default) for smallest first.

Check for problems

Real data is rarely this clean. These checks are worth running on any dataset:

Python · try it yourself

Edit the code and press Run (Ctrl + Enter). Examples on this page share their variables, like cells in a notebook.

This dataset passes all three, but make it a habit.

Try it

Continue in the same notebook, after adding the year, month and revenue columns.

Practice

How many order lines had a 10% discount?

orders.csv

Practice

How much revenue did those 10%-discount lines bring in? (A rounded figure is fine.)

orders.csv

Practice

What is the revenue of the biggest single order line in 2026?

orders.csv

Earn your badge

Take the module check

Questions on this module. Pass and you earn the Data Cleaning with Python badge, free.

Create a free account to earn the badge