Extracting 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:
12345678910111213141516import 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)
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Extracting Multiple Columns
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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:
12345678910111213141516import 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)
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