Python - How to select a column from a Pandas DataFrame

To select a column from a Pandas DataFrame, use square brackets with the column name. This returns a Series object containing all values from that column.

Syntax

dataFrame['ColumnName']

Basic Column Selection

First, let's create a DataFrame and select a single column ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],
      "Units": [100, 150, 110, 80, 110, 90]
   }
)

print("DataFrame ...")
print(dataFrame)

DataFrame ...
      Car  Units
0     BMW    100
1   Lexus    150
2    Audi    110
3 Mustang     80
4 Bentley    110
5  Jaguar     90

Selecting a Single Column

Use square brackets to select the 'Car' column ?

import pandas as pd

# Create DataFrame
dataFrame = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi', 'Mustang', 'Bentley', 'Jaguar'],
      "Units": [100, 150, 110, 80, 110, 90]
   }
)

# Selecting a column
selected_column = dataFrame['Car']
print("Selecting and displaying only a single column:")
print(selected_column)

Selecting and displaying only a single column:
0        BMW
1      Lexus
2       Audi
3    Mustang
4    Bentley
5     Jaguar
Name: Car, dtype: object

Alternative Methods

You can also use dot notation for column selection ?

import pandas as pd

dataFrame = pd.DataFrame(
   {
      "Car": ['BMW', 'Lexus', 'Audi'],
      "Units": [100, 150, 110]
   }
)

# Using dot notation
car_series = dataFrame.Car
print("Using dot notation:")
print(car_series)

Using dot notation:
0      BMW
1    Lexus
2     Audi
Name: Car, dtype: object

Key Points

• Square bracket notation works for all column names
• Dot notation only works if column names are valid Python identifiers
• Both methods return a Pandas Series object
• Column selection preserves the original index

Conclusion

Use square brackets dataFrame['ColumnName'] to select columns from a DataFrame. This returns a Series with the column data and original index preserved.