Creating interaction features in Data Analysis Python - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a new feature by multiplying 'age' and 'income'.

Data Analysis Python

df['age_income'] = df['age'] [1] df['income']

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

A+

B-

C*

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' instead of '*' which adds instead of multiplies.

Using '/' which divides and may cause errors if denominator has zeros.

Multiplying 'age' and 'income' creates an interaction feature that combines both effects.

2fill in blank

medium

Complete the code to create an interaction feature by concatenating 'city' and 'job' as strings.

Data Analysis Python

df['city_job'] = df['city'] [1] df['job']

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

A//

B*

C-

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using '*' which causes an error for strings.

Using '-' which is invalid for strings.

Using '+' concatenates two string columns to create an interaction feature.

3fill in blank

hard

Fix the error in the code to create an interaction feature by multiplying 'height' and 'weight'.

Data Analysis Python

df['height_weight'] = df['height'] [1] df['weight']

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

A*

B-

C+

D/

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' which adds instead of multiplying.

Using '/' which divides and is incorrect here.

Multiplying 'height' and 'weight' creates an interaction feature that combines both effects.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 characters.

Data Analysis Python

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

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' causing wrong filtering.

Using 'word' instead of 'len(word)' for the value.

The dictionary comprehension maps each word to its length if the word length is greater than 3.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys and values greater than zero.

Data Analysis Python

result = { [1]: [2] for k, v in data.items() if v [3] 0}

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using '<' or other operators instead of '>' for filtering.

Using 'k' as value instead of 'v'.

This dictionary comprehension creates keys as uppercase strings and includes only items where the value is greater than zero.