Missing values
3. NaN values and sorting
Duplicate rows
Joining datasets


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.


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)