Selecting multiple columns in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of selecting multiple columns from a DataFrame

What is the output of this code snippet?

Pandas

import pandas as pd

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})

result = df[['A', 'C']]
print(result)

A

   A  B
0  1  4
1  2  5
2  3  6

B KeyError: "['A', 'C'] not in index"

C

   B  C
0  4  7
1  5  8
2  6  9

D

   A  C
0  1  7
1  2  8
2  3  9

💡 Hint

Selecting multiple columns requires passing a list of column names inside double brackets.

The code selects columns 'A' and 'C' from the DataFrame. The output shows only these two columns with their values.

❓ data_output

intermediate

Number of columns selected

How many columns does the resulting DataFrame have after running this code?

Pandas

import pandas as pd

df = pd.DataFrame({
    'X': [10, 20],
    'Y': [30, 40],
    'Z': [50, 60],
    'W': [70, 80]
})

selected = df[['Y', 'W']]
print(len(selected.columns))

A 2

B 3

C 4

D 1

💡 Hint

Count the number of columns inside the list used for selection.

The code selects columns 'Y' and 'W', so the resulting DataFrame has exactly 2 columns.

🔧 Debug

advanced

Identify the error when selecting multiple columns

What error will this code raise?

Pandas

import pandas as pd

df = pd.DataFrame({
    'a': [1, 2],
    'b': [3, 4]
})

result = df['a', 'b']
print(result)

A TypeError: unhashable type: 'list'

B SyntaxError: invalid syntax

C KeyError: "('a', 'b')"

D AttributeError: 'DataFrame' object has no attribute 'a, b'

💡 Hint

Check how multiple columns should be selected using brackets.

Using df['a', 'b'] tries to access a single key which is a tuple ('a', 'b'), causing a KeyError because such a column does not exist.

🚀 Application

advanced

Selecting columns dynamically based on a condition

Given a DataFrame with columns 'temp', 'humidity', 'pressure', and 'wind', which code snippet selects only columns whose names contain the letter 'p'?

Pandas

import pandas as pd

df = pd.DataFrame({
    'temp': [22, 23],
    'humidity': [30, 45],
    'pressure': [1012, 1013],
    'wind': [5, 7]
})

A selected = df[[col for col in df.columns if 'p' in col]]

B selected = df[df.columns.str.contains('p')]

C selected = df.loc[:, df.columns == 'p']

D selected = df[df.columns.filter('p')]

💡 Hint

Use a list comprehension to filter column names containing 'p'.

Option A correctly uses a list comprehension to select columns with 'p' in their names. Other options either use invalid syntax or methods incorrectly.

🧠 Conceptual

expert

Understanding the difference between single and multiple column selection

Which statement correctly explains the difference between selecting a single column and multiple columns in pandas DataFrame?

A Selecting a single column with df['col'] returns a DataFrame, while selecting multiple columns with df[['col1', 'col2']] returns a Series.

B Selecting a single column with df['col'] returns a Series, while selecting multiple columns with df[['col1', 'col2']] returns a DataFrame.

C Both df['col'] and df[['col1', 'col2']] return a Series.

D Both df['col'] and df[['col1', 'col2']] return a DataFrame.

💡 Hint

Think about the data structure type returned by each selection method.

Selecting a single column returns a pandas Series (one-dimensional), while selecting multiple columns returns a DataFrame (two-dimensional).