Selecting data with MultiIndex in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the data for the first level index 'A' from the MultiIndex DataFrame.

Pandas

selected = df.loc[[1]]

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A'D'

B'B'

C'C'

D'A'

Attempts:

3 left

💡 Hint

Common Mistakes

Using integer positions instead of labels.

Using .iloc instead of .loc for label-based selection.

Using df.loc['A'] selects all rows where the first level of the MultiIndex is 'A'.

2fill in blank

medium

Complete the code to select data for the MultiIndex where the first level is 'B' and the second level is 'two'.

Pandas

selected = df.loc[([1], 'two')]

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A'D'

B'A'

C'B'

D'C'

Attempts:

3 left

💡 Hint

Common Mistakes

Not using a tuple for multi-level selection.

Swapping the order of levels in the tuple.

Using df.loc[('B', 'two')] selects the row where the first level is 'B' and the second level is 'two'.

3fill in blank

hard

Fix the error in the code to select all rows where the second level index is 'one'.

Pandas

selected = df.xs([1], level=1)

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A'one'

B1

C'two'

D'zero'

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong level number.

Using an integer instead of the label string.

The xs method selects cross sections. Using xs('one', level=1) selects all rows where the second level index is 'one'.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

Pandas

lengths = {word: [1] for word in words if [2]

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Alen(word)

Blen(word) > 3

Cword

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Using the word in the condition instead of its length.

The dictionary comprehension maps each word to its length using len(word). The condition len(word) > 3 filters words longer than 3 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their counts only if the count is greater than 1.

Pandas

result = [1]: [2] for [3], [2] in counts.items() if [2] > 1}}

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Aword.upper()

Bcount

Cword

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong variable names in the loop.

Not converting words to uppercase.

Using the count variable incorrectly.

The comprehension maps each uppercase word (word.upper()) to its count (count) only if the count is greater than 1. The loop variables are word and count.