Deals Of The Week - hours only!Up to 80% off on all courses and bundles.-Close

Wrap course as a gift

Prepare your gift and double-check it looks just right.

Form validation errors

Recipient's Name:
Recipient's Email:
Your Message (Optional):
Proceed to Checkout

Introduction to Python for Data Science

Introduction
Missing values
3. NaN values and sorting
Duplicate rows
Outliers
Joining datasets
Summary

Instruction

Good! You could see some NaN values in the tickets column. NaN stands for "Not a Number". In this case, NaN means that no value was provided in the corresponding "cell" of the CSV file.

Let's see how NaN values behave when we sort the dataset.

Exercise

Sort the values in ticket_statistics by the tickets column in ascending order.

As you can see, some NaN values were put at the very end.

Stuck? Here's a hint!

To sort the values, use the following template:

dataframe.sort_values(by='column name', ascending=1)