sort_values() by multiple columns in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the sort_values() function do in pandas?

It sorts the rows of a DataFrame based on the values in one or more columns.

beginner

How do you sort a DataFrame by multiple columns using sort_values()?

Pass a list of column names to the by parameter, like df.sort_values(by=['col1', 'col2']).

intermediate

How can you sort one column ascending and another descending using sort_values()?

Use the ascending parameter with a list of booleans, e.g., df.sort_values(by=['col1', 'col2'], ascending=[True, False]).

beginner

What happens if you don't specify the ascending parameter in sort_values()?

All columns are sorted in ascending order by default.

intermediate

Can sort_values() sort by columns with missing values (NaNs)?

Yes, NaNs are placed at the end by default when sorting ascending, and at the beginning when sorting descending.

How do you sort a DataFrame df by columns 'A' ascending and 'B' descending?

A df.sort_values(by=['A', 'B'])

B df.sort_values(by=['A', 'B'], ascending=[False, True])

C df.sort_values(by=['A', 'B'], ascending=[True, False])

D df.sort_values(by=['B', 'A'], ascending=[True, False])

You specify the columns in order and set ascending to True for 'A' and False for 'B'.

What is the default sort order if you do not specify ascending?

A Ascending for all columns

B Descending for all columns

C Random order

D Depends on the data type

By default, sort_values() sorts all columns in ascending order.

Which parameter do you use to specify the columns to sort by in sort_values()?

A by

B order

C sort_by

D columns

The by parameter takes a column name or list of column names to sort by.

If you want to sort by a single column 'X' in descending order, which is correct?

A df.sort_values(by='X', ascending=True)

B df.sort_values(by='X', ascending=False)

C df.sort_values(by='X')

D df.sort_values(by='X', ascending=[False])

Set ascending=False to sort descending for a single column.

How does sort_values() handle NaN values when sorting ascending?

A NaNs appear at the start

B NaNs are removed

C NaNs cause an error

D NaNs appear at the end

By default, NaNs are placed at the end when sorting ascending.

Explain how to sort a pandas DataFrame by multiple columns with different sort orders.

Think about how you tell pandas which columns and order to use.

Describe what happens to missing values (NaNs) when sorting a DataFrame with sort_values().

Consider where NaNs appear in the sorted result.