str accessor for string methods in Pandas - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert the 'name' column to lowercase using pandas str accessor.

Pandas

df['name_lower'] = df['name'].str.[1]()

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

Aupper

Btitle

Ccapitalize

Dlower

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'upper' instead of 'lower' changes letters to uppercase.

Using 'capitalize' only changes the first letter to uppercase.

Using 'title' capitalizes the first letter of each word.

The str.lower() method converts all characters in the string to lowercase.

2fill in blank

medium

Complete the code to check if the 'email' column contains '@' using pandas str accessor.

Pandas

df['has_at'] = df['email'].str.[1]('@')

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

Astartswith

Bendswith

Ccontains

Dmatch

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'startswith' checks only the beginning of the string.

Using 'endswith' checks only the end of the string.

Using 'match' is for regex matching, not simple substring check.

The str.contains() method checks if the string contains the specified substring.

3fill in blank

hard

Fix the error in the code to remove whitespace from the 'city' column using pandas str accessor.

Pandas

df['city_clean'] = df['city'].str.[1]()

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

Astrip

Btrim

Cclean

Dremove

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'trim' is not a pandas str method.

Using 'clean' or 'remove' are not valid string methods.

The str.strip() method removes whitespace from both ends of the string.

4fill in blank

hard

Fill both blanks to create a dictionary with words as keys and their lengths as values, only for words longer than 4 characters.

Pandas

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 than 4.

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

The dictionary comprehension uses len(word) as value and filters words with length greater than 4 using >.

5fill in blank

hard

Fill all three blanks to create a dictionary with uppercase keys, values from data, only if value is positive.

Pandas

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

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

Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'k' instead of 'k.upper()' keeps keys lowercase.

Using '<' or other operators changes the filter condition incorrectly.

The dictionary comprehension uses uppercase keys with k.upper(), values as v, and filters for positive values with >.