Ascending and descending order in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to sort the DataFrame df by the column 'age' in ascending order.

Pandas

sorted_df = df.sort_values(by='age', ascending=[1])

Drag options to blanks, or click blank then click option'

ATrue

B'yes'

CNone

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'False' instead of True for ascending order.

Passing a string instead of a boolean.

Setting ascending=True sorts the DataFrame in ascending order by the specified column.

2fill in blank

medium

Complete the code to sort the DataFrame df by the column 'score' in descending order.

Pandas

sorted_df = df.sort_values(by='score', ascending=[1])

Drag options to blanks, or click blank then click option'

AFalse

BTrue

C'descending'

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Using True instead of False for descending order.

Passing a string instead of a boolean.

Setting ascending=False sorts the DataFrame in descending order.

3fill in blank

hard

Fix the error in the code to sort df by 'height' in descending order.

Pandas

sorted_df = df.sort_values(by='height', ascending=[1])

Drag options to blanks, or click blank then click option'

A0

BFalse

C'False'

DNone

Attempts:

3 left

💡 Hint

Common Mistakes

Using string 'False' instead of boolean False.

Passing None which defaults to ascending order.

The ascending parameter must be a boolean, not a string or None.

4fill in blank

hard

Fill both blanks to sort df by 'age' ascending and then by 'score' descending.

Pandas

sorted_df = df.sort_values(by=[[1], [2]], ascending=[True, False])

Drag options to blanks, or click blank then click option'

A'age'

B'score'

C'height'

D'name'

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up the order of columns.

Using columns not present in the DataFrame.

We sort first by 'age' ascending, then by 'score' descending.

5fill in blank

hard

Fill all three blanks to create a dictionary with word lengths for words longer than 3 characters.

Pandas

lengths = { [1] : len([2]) for [3] in words if len([2]) > 3 }

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Aword

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names inconsistently.

Using a variable name not defined in the comprehension.

The dictionary comprehension uses 'word' as the variable name for each item in words.