Why engineered features improve analysis in Data Analysis Python - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a new feature that is the square of the 'age' column.

Data Analysis Python

df['age_squared'] = df['age'] [1] 2

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

A*

B+

C**

D//

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' adds 2 instead of squaring.

Using '*' multiplies by 2, not square.

Using '//' does integer division.

Using ** raises the 'age' values to the power of 2, creating the squared feature.

2fill in blank

medium

Complete the code to filter rows where the new feature 'age_squared' is greater than 1000.

Data Analysis Python

filtered_df = df[df['age_squared'] [1] 1000]

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

A>

B<

C==

D<=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' selects smaller values.

Using '==' selects only values equal to 1000.

Using '<=' includes values less or equal, not greater.

The operator > selects rows where 'age_squared' is greater than 1000.

3fill in blank

hard

Fix the error in the code to create a feature that is the ratio of 'income' to 'age'.

Data Analysis Python

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

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

A+

B/

C*

D-

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' or '-' adds or subtracts instead of dividing.

Using '*' multiplies instead of dividing.

The ratio means dividing income by age, so use the division operator /.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 4 characters.

Data Analysis Python

lengths = {word: [1] for word in words if len(word) [2] 4}

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

Alen(word)

B<=

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<=' selects words shorter or equal to 4.

Using 'word' as value stores the word, not its length.

The dictionary stores the length of each word, so use len(word). We want words longer than 4, so use >.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words and their lengths for words longer than 3 characters.

Data Analysis Python

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

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

Aw.upper()

Blen(w)

C>

Dw.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using w.lower() for keys instead of uppercase.

Using '<=' instead of '>' for filtering.

Using the word itself as value instead of length.

The keys are uppercase words (w.upper()), values are lengths (len(w)), and filter words longer than 3 (>).