Pattern matching with str.contains in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to filter rows where the 'Name' column contains the substring 'John'.

Data Analysis Python

filtered = df[df['Name'].str.[1]('John')]

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Acontains

Bstartswith

Cmatch

Dendswith

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'match' which looks for exact matches at the start.

Using 'startswith' or 'endswith' which only check beginnings or ends.

The str.contains method checks if the string contains the given substring anywhere.

2fill in blank

medium

Complete the code to filter rows where the 'Email' column contains the pattern '@gmail.com' ignoring case.

Data Analysis Python

filtered = df[df['Email'].str.contains('@gmail.com', case=[1])]

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A0

BTrue

CNone

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Using True which makes the search case sensitive.

Using None which is not a valid boolean here.

Setting case=False makes the search ignore uppercase or lowercase differences.

3fill in blank

hard

Fix the error in the code to filter rows where 'City' contains 'York' using regex.

Data Analysis Python

filtered = df[df['City'].str.contains('York', regex=[1])]

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ATrue

B'True'

C1

DFalse

Attempts:

3 left

💡 Hint

Common Mistakes

Passing 'True' as a string causes a TypeError.

Passing 1 instead of True is not accepted.

The regex parameter expects a boolean value, not a string or integer.

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}

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the condition.

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 4.

5fill in blank

hard

Fill all three blanks to create a dictionary of uppercase words with their lengths if length is greater than 3.

Data Analysis Python

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

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Aw.upper()

Blen(w)

C>

Dw

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using '<' instead of '>' in the condition.

The dictionary comprehension uses the uppercase word as key, length as value, and filters words longer than 3.