Selecting columns by name in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Selecting multiple columns by name

What is the output of this code snippet that selects columns 'A' and 'C' from the DataFrame?

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  C
0  1  7
1  2  8
2  3  9

B

   A  B  C
0  1  4  7
1  2  5  8
2  3  6  9

C

   B
0  4
1  5
2  6

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

💡 Hint

Remember to use double brackets to select multiple columns by name.

Using df[['A', 'C']] selects only columns 'A' and 'C' from the DataFrame, returning a new DataFrame with those columns.

❓ data_output

intermediate

Selecting a single column returns a Series

What is the type and output of selecting column 'B' from the DataFrame below?

Pandas

import pandas as pd

df = pd.DataFrame({
    'A': [10, 20],
    'B': [30, 40],
    'C': [50, 60]
})

result = df['B']
print(type(result))
print(result)

A <class 'pandas.core.frame.DataFrame'>\n B\n0 30\n1 40

B <class 'pandas.core.series.Series'>\n0 30\n1 40\nName: B, dtype: int64

C <class 'list'>\n[30, 40]

D KeyError: 'B'

💡 Hint

Selecting a single column by name returns a Series, not a DataFrame.

df['B'] returns a pandas Series object representing the column 'B'. The type confirms this.

🔧 Debug

advanced

Identify the error when selecting columns

What error does this code raise when trying to select columns 'X' and 'Y' from the DataFrame?

Pandas

import pandas as pd

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

result = df[['X', 'Y']]
print(result)

A TypeError: unhashable type: 'list'

B AttributeError: 'DataFrame' object has no attribute 'X'

C IndexError: list index out of range

D KeyError: "['X', 'Y'] not in index"

💡 Hint

Check if the columns exist in the DataFrame before selecting.

Selecting columns that do not exist in the DataFrame raises a KeyError listing the missing columns.

🚀 Application

advanced

Select columns by name using a list variable

Given a list of column names, which option correctly selects those columns from the DataFrame?

Pandas

import pandas as pd

cols = ['A', 'C']
df = pd.DataFrame({
    'A': [5, 6],
    'B': [7, 8],
    'C': [9, 10]
})

result = None  # Fill in the correct selection

A result = df[cols]

B result = df.cols

C result = df[['cols']]

D result = df.loc[:, cols]

💡 Hint

Use the list variable directly inside the brackets to select columns.

Using df[cols] selects the columns named in the list cols. df.loc[:, cols] also works but is not in options as correct here.

🧠 Conceptual

expert

Difference between selecting columns by single vs double brackets

What is the main difference between df['A'] and df[['A']] when selecting columns in pandas?

A Both return a Series but with different index labels

B df['A'] returns a DataFrame, df[['A']] returns a Series

C df['A'] returns a Series, df[['A']] returns a DataFrame

D Both return a DataFrame but with different column order

💡 Hint

Think about the data structure type returned by each selection.

Selecting a single column with single brackets returns a Series. Using double brackets returns a DataFrame with one column.