Boolean filtering in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to filter rows where the 'age' column is greater than 30.

Data Analysis Python

filtered_data = data[data['age'] [1] 30]

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

A>

B<

C==

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' will select ages less than 30.

Using '==' will select only ages exactly 30.

The '>' operator filters rows where the 'age' is greater than 30.

2fill in blank

medium

Complete the code to filter rows where the 'score' column is equal to 100.

Data Analysis Python

perfect_scores = data[data['score'] [1] 100]

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

A==

B>=

C<

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=' instead of '==' causes syntax errors.

Using '>=' selects scores 100 or higher, not just 100.

The '==' operator checks for exact equality, selecting rows where 'score' is 100.

3fill in blank

hard

Fix the error in the code to filter rows where 'height' is less than or equal to 170.

Data Analysis Python

short_people = data[data['height'] [1] 170]

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

A<

B==

C=>

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '=>' causes syntax errors.

Using '<' excludes rows where height equals 170.

The correct operator for 'less than or equal to' is '<='.

4fill in blank

hard

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

Data Analysis Python

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

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

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

Checking 'word > 3' which compares strings to numbers incorrectly.

The dictionary maps each word to its length using len(word). The filter keeps words with length greater than 3 using len(word) > 3.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase words to their scores only if the score is greater than 0.

Data Analysis Python

result = [1]: [2] for [3], [2] in data.items() if [2] > 0

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

Ak.upper()

Bv

Ck

Dk.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of k.upper() for keys.

Using k as the value instead of v.

Using v as the loop variable instead of k.

The dictionary keys are uppercase versions of k using k.upper(). The values are v. The loop variable is k from data.items(). The filter keeps items where v is greater than 0.