sort_values() by single column 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 a single column named 'age' in ascending order?

Use df.sort_values('age'). This sorts the DataFrame rows by the 'age' column from smallest to largest.

beginner

What parameter do you use to sort a column in descending order with sort_values()?

Set ascending=False inside sort_values() to sort in descending order.

intermediate

What happens if you use inplace=True with sort_values()?

The DataFrame is sorted in place, meaning the original DataFrame changes and nothing is returned.

intermediate

Why might you want to reset the index after sorting a DataFrame?

Because sorting changes the row order but keeps original indexes, resetting the index gives a clean, ordered index.

Which code sorts a DataFrame df by the column 'score' in ascending order?

A df.sort('score')

B df.sort_values('score')

C df.sort_values(by='score', ascending=False)

D df.order_by('score')

The correct syntax is df.sort_values('score') to sort ascending by 'score'.

How do you sort a DataFrame by column 'height' in descending order?

A df.sort_values('height', ascending=False)

B df.sort_values('height', ascending=True)

C df.sort('height', descending=True)

D df.sort_values('height', reverse=True)

Use ascending=False to sort descending with sort_values().

What does inplace=True do in sort_values()?

A Returns a new sorted DataFrame

B Sorts the DataFrame without changing the original

C Raises an error

D Sorts the original DataFrame and returns None

With inplace=True, the original DataFrame is sorted and the function returns None.

After sorting a DataFrame, why might you call reset_index(drop=True)?

A To remove the old index and create a new sequential index

B To sort again

C To rename columns

D To filter rows

Sorting keeps original indexes; resetting index cleans them to be sequential.

Which of these is NOT a valid way to specify the column to sort by in sort_values()?

A df.sort_values('age')

B df.sort_values(by='age')

C df.sort_values(columns='age')

D df.sort_values(['age'])

The parameter name is by, not columns.

Explain how to sort a pandas DataFrame by a single column in ascending and descending order.

Think about the parameters of sort_values()

Describe why resetting the index after sorting a DataFrame might be useful.

Consider how DataFrame indexes behave after sorting