Boolean indexing in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of Boolean Indexing with Multiple Conditions

What is the output of this code snippet using pandas Boolean indexing?

Pandas

import pandas as pd

df = pd.DataFrame({
    'A': [10, 20, 30, 40, 50],
    'B': [5, 15, 25, 35, 45]
})

result = df[(df['A'] > 20) & (df['B'] < 40)]
print(result)

A

    A   B
2  30  25
4  50  45

B

    A   B
1  20  15
2  30  25
3  40  35

C

    A   B
2  30  25
3  40  35

D Empty DataFrame\nColumns: [A, B]\nIndex: []

💡 Hint

Remember that both conditions must be true for each row to be included.

The code filters rows where column 'A' is greater than 20 and column 'B' is less than 40. Rows with index 2 and 3 satisfy both conditions.

❓ data_output

intermediate

Number of Rows After Boolean Filtering

Given the DataFrame below, how many rows remain after applying the Boolean filter?

Pandas

import pandas as pd

df = pd.DataFrame({
    'score': [88, 92, 79, 93, 85],
    'passed': [True, True, False, False, False]
})

filtered = df[df['passed'] & (df['score'] > 90)]
print(len(filtered))

A 1

B 2

C 3

D 0

💡 Hint

Count rows where 'passed' is true and 'score' is greater than 90.

Only one row (index 1 with score 92 and passed true) meets both conditions.

🔧 Debug

advanced

Identify the Error in Boolean Indexing Code

What error does this code raise when executed?

Pandas

import pandas as pd

df = pd.DataFrame({'X': [1, 2, 3], 'Y': [4, 5, 6]})

result = df[(df['X'] > 1) & (df['Y'] < 6)]
print(result)

A TypeError: 'and' operator cannot be used with Series

B SyntaxError: invalid syntax

C KeyError: 'X'

D No error, prints filtered DataFrame

💡 Hint

Check how to combine multiple Boolean conditions in pandas.

The 'and' operator cannot be used with pandas Series; use '&' instead for element-wise logical AND.

🚀 Application

advanced

Filter DataFrame Rows Based on String Condition

Which option correctly filters rows where the 'city' column contains the substring 'York'?

Pandas

import pandas as pd

df = pd.DataFrame({
    'city': ['New York', 'Los Angeles', 'Yorkshire', 'Boston'],
    'population': [8000000, 4000000, 500000, 700000]
})

A df[df['city'].str.startswith('York')]

B df[df['city'] == 'York']

C df[df['city'].str.match('York')]

D df[df['city'].str.contains('York')]

💡 Hint

Use a method that checks if the substring appears anywhere in the string.

str.contains('York') returns true for any string containing 'York', including 'New York' and 'Yorkshire'.

🧠 Conceptual

expert

Understanding Boolean Indexing with Missing Values

Given this DataFrame with missing values, what is the output of the Boolean indexing operation?

Pandas

import pandas as pd
import numpy as np

df = pd.DataFrame({
    'A': [1, 2, np.nan, 4],
    'B': [np.nan, 2, 3, 4]
})

result = df[df['A'] > 1]
print(result)

A Empty DataFrame\nColumns: [A, B]\nIndex: []

B

     A    B
1  2.0  2.0
3  4.0  4.0

C

     A    B
1  2.0  2.0
2  NaN  3.0
3  4.0  4.0

D

     A    B
0  1.0  NaN
1  2.0  2.0
3  4.0  4.0

💡 Hint

Remember how comparisons with NaN behave in Boolean indexing.

Comparisons with NaN return false, so rows with NaN in 'A' are excluded. Only rows where 'A' > 1 and not NaN are included.