rank() method and ranking methods in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to rank the values in the 'score' column of the DataFrame.

Pandas

df['rank'] = df['score'].[1]()

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

Asort

Brank

Cindex

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using sort() instead of rank()

Using index() which does not rank values

The rank() method assigns ranks to values in a column.

2fill in blank

medium

Complete the code to rank the 'score' column with method 'min' to assign the minimum rank to ties.

Pandas

df['rank_min'] = df['score'].rank(method=[1])

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

A'first'

B'average'

C'max'

D'min'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'average' which assigns average ranks to ties

Using 'max' which assigns maximum ranks to ties

The method='min' assigns the minimum rank to tied values.

3fill in blank

hard

Fix the error in the code to rank the 'score' column in descending order.

Pandas

df['rank_desc'] = df['score'].rank(ascending=[1])

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

AFalse

B'False'

CTrue

D'True'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'False' as a string instead of boolean False

Using True which ranks ascending

To rank in descending order, set ascending=False as a boolean, not a string.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps words to their ranks if their length is greater than 3.

Pandas

{word: df['score'].rank(method=[1])[i] for i, word in enumerate(words) if len(word) [2] 3}

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

A'average'

B>

C<

D'min'

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the condition

Using 'min' instead of 'average' for method

The method='average' assigns average ranks, and the condition len(word) > 3 filters words longer than 3 letters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their ranks where rank is greater than 2.

Pandas

{word[1]: df['score'].rank(method=[2])[i] for i, word in enumerate(words) if df['score'].rank(method=[3])[i] > 2}

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

A.upper()

B'average'

C'min'

D'max'

Attempts:

3 left

💡 Hint

Common Mistakes

Not uppercasing the word

Using the same method for both blanks incorrectly

The first blank uses .upper() to uppercase words. The ranking methods are 'average' for the key and 'min' for the condition.