Selecting Columns

The most everyday thing you do with a DataFrame is pull out a column. Each column comes back as a Series — the same 1-D structure you already know.

1One column at a time

Put the column name in square brackets. You can also use dot notation — but only when the name is a single word with no spaces.

one_column.py

import pandas as pd

df = pd.DataFrame({
    'Name':          ['Rinku', 'Ritu', 'Pankaj', 'Ajay', 'Aditya'],
    'English Marks': [65, 77, 72, 81, 92],
    'IP Marks':      [89, 83, 95, 99, 87],
    'Maths Marks':   [72, 69, 87, 94, 96],
}, index=['ID 1', 'ID 2', 'ID 3', 'ID 4', 'ID 5'])

# Square brackets — always works
print(df['IP Marks'])

# Dot notation — only for single-word names (df.Name here)
print("\nFirst name:", df.Name['ID 1'])

import pandas as pd

df = pd.DataFrame({
    'Name':          ['Rinku', 'Ritu', 'Pankaj', 'Ajay', 'Aditya'],
    'English Marks': [65, 77, 72, 81, 92],
    'IP Marks':      [89, 83, 95, 99, 87],
    'Maths Marks':   [72, 69, 87, 94, 96],
}, index=['ID 1', 'ID 2', 'ID 3', 'ID 4', 'ID 5'])

# Square brackets — always works
print(df['IP Marks'])

# Dot notation — only for single-word names (df.Name here)
print("\nFirst name:", df.Name['ID 1'])

Watch Out

Dot notation fails on multi-word names: df.IP Marks is a syntax error. When in doubt, use df['IP Marks'].

2Several columns at once

Pass a list of column names inside the square brackets. The columns come back in the order you list them — and the result is a DataFrame, not a Series.

many_columns.py

import pandas as pd

df = pd.DataFrame({
    'Name':          ['Rinku', 'Ritu', 'Pankaj', 'Ajay', 'Aditya'],
    'English Marks': [65, 77, 72, 81, 92],
    'IP Marks':      [89, 83, 95, 99, 87],
    'Maths Marks':   [72, 69, 87, 94, 96],
}, index=['ID 1', 'ID 2', 'ID 3', 'ID 4', 'ID 5'])

# A list of names -> a smaller DataFrame
print(df[['Name', 'Maths Marks']])

import pandas as pd

df = pd.DataFrame({
    'Name':          ['Rinku', 'Ritu', 'Pankaj', 'Ajay', 'Aditya'],
    'English Marks': [65, 77, 72, 81, 92],
    'IP Marks':      [89, 83, 95, 99, 87],
    'Maths Marks':   [72, 69, 87, 94, 96],
}, index=['ID 1', 'ID 2', 'ID 3', 'ID 4', 'ID 5'])

# A list of names -> a smaller DataFrame
print(df[['Name', 'Maths Marks']])

Key Takeaway

df['col'] → one column as a Series. df[['a', 'b']] → several columns as a DataFrame. Note the double brackets.

Quick Check

What does df[['Name', 'IP Marks']] return?

Quick Check

Which safely selects a column named 'IP Marks'?

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