from ironxl import * # Supported for XLSX, XLS, XLSM, XLTX, CSV, and TSV workbook = WorkBook.Load("sample.xlsx") # Select worksheet at index 0 worksheet = workbook.WorkSheets[0] # Get any existing worksheet first_sheet = workbook.DefaultWorkSheet # Select a cell and return the converted value cell_value = worksheet["A2"].IntValue # Read from ranges of cells elegantly. for cell in worksheet["A2:A10"]: print("Cell {} has value '{}'".format(cell.AddressString, cell.Text)) # Calculate aggregate values such as Min, and Sum total_sum = worksheet["A2:A10"].Sum()

Load Excel Files without Interop

The Load feature in IronXL allows Python developers to open and manipulate existing Excel files in a variety of formats including XLSX, XLS, and CSV. Loading a WorkBook provides access to all of its worksheets and cell data, making it easy to extract values, iterate over ranges, and perform calculations such as sums or maximum values. Cells can be accessed individually and their values converted to the appropriate Python data type. This feature simplifies working with Excel data in Python and is ideal for data analysis, report generation, and workflow automation.

5 Steps to Load and Calculate Sum from an Excel File in Python

workbook = WorkBook.Load("sample.xlsx")
worksheet = workbook.WorkSheets[0]
range_ = worksheet["A2:A10"]
total = range_.Sum()
print("The sum of A2:A10 is:", total)

WorkBook.Load is the starting point for working with existing Excel files. By passing a file path, IronXL opens the workbook and makes all of its content available for manipulation—without requiring Microsoft Excel to be installed.

After loading the workbook, WorkSheets[0] selects the first worksheet. In Excel, a workbook can contain multiple sheets, each representing a set of data organized into rows and columns. Targeting the first sheet allows access to the primary data source.

The range variable worksheet["A2:A10"] defines a group of cells spanning rows 2 through 10 in column A. IronXL lets you interact with multiple cells at once, whether reading values, applying formatting, or running aggregate calculations.

The .Sum() method computes the total of all numeric values in the selected range, eliminating the need for manual iteration. IronXL also provides built-in functions including Average(), Min(), and Max() for common data analysis tasks.

Finally, the result is printed to the console. This pattern integrates easily into larger Python workflows for data aggregation, reporting pipelines, or database imports.

Learn to Load and Manipulate Excel Files with IronXL for Python