Sorting by values in Pandas - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the pandas method sort_values() do?

It sorts a DataFrame or Series by the values in one or more columns or the Series itself, arranging data in ascending or descending order.

beginner

How do you sort a DataFrame by a single column named 'age' in ascending order?

Use df.sort_values(by='age'). This sorts the DataFrame rows so that the smallest age is first and the largest last.

intermediate

How can you sort a DataFrame by multiple columns, for example 'age' ascending and 'score' descending?

Use df.sort_values(by=['age', 'score'], ascending=[True, False]). This sorts first by age ascending, then by score descending within each age.

beginner

What does the parameter inplace=True do in sort_values()?

It changes the original DataFrame directly without creating a new sorted copy. If inplace=False (default), it returns a new sorted DataFrame.

beginner

How do you sort a pandas Series in descending order?

Use series.sort_values(ascending=False). This arranges the Series values from largest to smallest.

Which pandas method sorts a DataFrame by column values?

A sort_values()

B sort_index()

C groupby()

D filter()

sort_values() sorts data by column or Series values. sort_index() sorts by index labels.

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

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

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

C df.sort_index(ascending=False)

D df.sort(by='score')

Set ascending=False to sort from highest to lowest values.

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

A Sorts the DataFrame and returns the original unsorted DataFrame

B Returns a new sorted DataFrame

C Deletes the DataFrame

D Sorts the DataFrame and returns None

inplace=True sorts the original DataFrame and returns nothing (None).

How do you sort a DataFrame by two columns, 'age' ascending and 'score' descending?

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

B df.sort_values(by=['age', 'score'], ascending=True)

C df.sort_values(by=['score', 'age'], ascending=[False, True])

D df.sort_index()

Use a list for by and a matching list of booleans for ascending to control order per column.

Which of these is NOT a valid argument for sort_values()?

A by

B ascending

C groupby

D inplace

groupby is a separate pandas method, not an argument for sort_values().

Explain how to sort a pandas DataFrame by one or more columns with different ascending/descending orders.

Think about how to control sorting order for each column separately.

Describe the effect of the 'inplace' parameter in the sort_values() method.

Consider whether the original data changes or a copy is made.