How to Read Excel Multiple Sheets in Python Pandas

Excel files often store related data across multiple sheets. Pandas provides a way to read all these sheets at once using the pd.read_excel() method. This approach allows us to load multiple sheets into Python and work with them as Pandas DataFrames.

Note: For this article a sample multiple sheets "multi_sheet.xlsx" is used, to download click here.

Example: This example shows how Pandas reads all sheets from an Excel file and stores them in a single object.

Output

Explanation:

• pd.read_excel() reads the Excel file and sheet_name=None tells Pandas to load all sheets.
• data becomes a dictionary of DataFrames.
• Each key is a sheet name, and each value is the sheet’s DataFrame.

pd.read_excel()

The pd.read_excel() method is used to read Excel files in Pandas. When multiple sheets are read, it returns a dictionary instead of a single DataFrame. Below is the syntax:

pd.read_excel(excel_file, sheet_name=None)

Parameters:

• excel_file: Name or path of the Excel file
• sheet_name: None - Reads all sheets, List of names - Reads selected sheets and Index number - Reads a specific sheet

Examples

Example 1: This example reads all sheets from an Excel file and prints their contents one by one.

Output

Explanation:

• sheets.items() allows access to each sheet.
• sheet_name stores the name of the sheet.
• df stores the DataFrame of that sheet.

Example 2: This example shows how to get sheet names and work with their DataFrames.

Output

Explanation: sheets.keys() returns all sheet names.

Example 3: This example demonstrates how to extract only one required sheet after loading all sheets.

Output

Explanation:

• sheets["SheetA"] accesses the sheet named SheetA.
• data contains only the DataFrame of that sheet.