Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Apprendre Extracting Multiple Columns | Fetching Data from DataFrames
Pandas: First Steps

bookExtracting Multiple Columns

We can fetch a single column from a DataFrame using the following syntax:

DataFrame['column name']

Note

When we fetch a single column, it is fetched in the form of a Series. Hence, all the methods and properties of a series are applicable to it.

It's possible to extract multiple columns from a DataFrame using the following syntax:

DataFrame[[column1, column2, ...]]

Where column1, column2, and so on, represent the names of the columns in string format.

The following example demonstrates the usage:

12345678910111213141516
import pandas as pd # Create a sample DataFrame with sales data df = pd.DataFrame({ 'Order ID': [101, 102, 103, 104], 'Customer Name': ['Alice', 'Bob', 'Charlie', 'David'], 'Amount Paid': [50.0, 30.0, 75.0, 40.0], 'Product': ['Laptop', 'Phone', 'Tablet', 'Monitor'], 'Purchase Date': ['2025-04-01', '2025-04-01', '2025-04-01', '2025-04-01'] }) # Extract specific columns from the DataFrame selected_columns = df[['Order ID', 'Customer Name', 'Amount Paid']] # Print the extracted columns print(selected_columns)
copy
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 3. Chapitre 7

Demandez à l'IA

expand

Demandez à l'IA

ChatGPT

Posez n'importe quelle question ou essayez l'une des questions suggérées pour commencer notre discussion

Awesome!

Completion rate improved to 2.7

bookExtracting Multiple Columns

Glissez pour afficher le menu

We can fetch a single column from a DataFrame using the following syntax:

DataFrame['column name']

Note

When we fetch a single column, it is fetched in the form of a Series. Hence, all the methods and properties of a series are applicable to it.

It's possible to extract multiple columns from a DataFrame using the following syntax:

DataFrame[[column1, column2, ...]]

Where column1, column2, and so on, represent the names of the columns in string format.

The following example demonstrates the usage:

12345678910111213141516
import pandas as pd # Create a sample DataFrame with sales data df = pd.DataFrame({ 'Order ID': [101, 102, 103, 104], 'Customer Name': ['Alice', 'Bob', 'Charlie', 'David'], 'Amount Paid': [50.0, 30.0, 75.0, 40.0], 'Product': ['Laptop', 'Phone', 'Tablet', 'Monitor'], 'Purchase Date': ['2025-04-01', '2025-04-01', '2025-04-01', '2025-04-01'] }) # Extract specific columns from the DataFrame selected_columns = df[['Order ID', 'Customer Name', 'Amount Paid']] # Print the extracted columns print(selected_columns)
copy
Tout était clair ?

Comment pouvons-nous l'améliorer ?

Merci pour vos commentaires !

Section 3. Chapitre 7
some-alt