### Python Modules for Reading Excel Files For reading Excel files in Python, several powerful modules are available. One commonly used module is `pandas`, which provides extensive functionalities for data manipulation and analysis including support for reading various formats like Excel. Another dedicated library specifically tailored for handling Microsoft Excel documents is `openpyxl`. This package allows working directly with `.xlsx` files without requiring any external dependencies such as COM servers or Java runtime environments[^1]. Additionally, there exists another option called `xlrd`; however, this one primarily targets older binary format (`xls`) spreadsheets rather than newer XML-based ones(`xlsx`). It's worth noting that starting from version 2.0, xlrd dropped support for new-style Excel (`.xlsx`) files entirely. Here’s how to use both pandas along with openpyxl: #### Using Pandas with OpenPyXL Backend Pandas relies on different backends depending upon the type of excel file being processed; for modern Excel workbooks (.xlsx), it uses either `openpyxl` or `xlsxwriter`. ```python import pandas as pd # Load spreadsheet excel_file = 'path_to_your_spreadsheet.xlsx' # Load a sheet into a DataFrame by name df = pd.read_excel(excel_file, engine='openpyxl') print(df.head()) ``` #### Directly Using OpenPyXL When more granular control over cell operations within worksheets is needed, using `openpyxl` directly might prove beneficial. ```python from openpyxl import load_workbook wb = load_workbook(filename='example.xlsx', read_only=True) ws = wb.active for row in ws.iter_rows(values_only=True): print(row) ```