Load Excel Files without Interop

VB C#

using IronXL;
using System;
using System.Linq;

// Supported for XLSX, XLS, XLSM, XLTX, CSV and TSV
WorkBook workBook = WorkBook.Load("sample.xlsx");

// Select worksheet at index 0
WorkSheet workSheet = workBook.WorkSheets[0];

// Get any existing worksheet
WorkSheet firstSheet = workBook.DefaultWorkSheet;

// Select a cell and return the converted value
int cellValue = workSheet["A2"].IntValue;

// Read from ranges of cells elegantly.
foreach (var cell in workSheet["A2:A10"])
{
    Console.WriteLine("Cell {0} has value '{1}'", cell.AddressString, cell.Text);
}

// Calculate aggregate values such as Min, Max and Sum
decimal sum = workSheet["A2:A10"].Sum();

// Linq compatible
decimal max = workSheet["A2:A10"].Max(c => c.DecimalValue);

Imports IronXL
Imports System
Imports System.Linq

' Supported for XLSX, XLS, XLSM, XLTX, CSV and TSV
Private workBook As WorkBook = WorkBook.Load("sample.xlsx")

' Select worksheet at index 0
Private workSheet As WorkSheet = workBook.WorkSheets(0)

' Get any existing worksheet
Private firstSheet As WorkSheet = workBook.DefaultWorkSheet

' Select a cell and return the converted value
Private cellValue As Integer = workSheet("A2").IntValue

' Read from ranges of cells elegantly.
For Each cell In workSheet("A2:A10")
	Console.WriteLine("Cell {0} has value '{1}'", cell.AddressString, cell.Text)
Next cell

' Calculate aggregate values such as Min, Max and Sum
Dim sum As Decimal = workSheet("A2:A10").Sum()

' Linq compatible
Dim max As Decimal = workSheet("A2:A10").Max(Function(c) c.DecimalValue)

Install-Package IronXL.Excel

Load Excel Files without Interop

The Load feature in IronXL allows you to easily load and manipulate existing Excel files in various formats (XLSX, XLS, CSV, etc.). By loading a workbook, you gain access to its worksheets and data, enabling you to extract values, loop through cell ranges, and perform calculations like sums or maximum values. You can access specific cells, convert their values to the appropriate data type (e.g., integers, decimals), and even use LINQ for advanced data operations. This feature simplifies working with Excel data in .NET, making it ideal for tasks like data analysis, report generation, and automation.

5 Steps to Load and Calculate Sum from an Excel File

WorkBook workBook = WorkBook.Load("sample.xlsx");
WorkSheet workSheet = workBook.WorkSheets[0];
var range = workSheet["A2:A10"];
decimal sum = range.Sum();
Console.WriteLine("The sum of the range A2:A10 is: " + sum);

The WorkBook object is the key starting point for interacting with Excel files in IronXL. By using the WorkBook.Load("sample.xlsx") method, you open an existing Excel file, gaining access to its content and structure for further manipulation. This allows developers to work with pre-existing data, automate tasks, and update spreadsheets without having to create a new one from scratch.

Next, the WorkSheets[0] property is used to access the first worksheet in the workbook. In Excel, a workbook can contain multiple sheets, each representing a set of data organized into rows and columns. By selecting the first sheet, you're targeting the main area where your data is stored or where you'll perform operations like reading values or calculating results.

The range variable defines a specific group of cells, in this case, the range from A2 to A10. This is where IronXL allows you to interact with multiple cells at once, either by reading values, applying formatting, or performing calculations across ranges. In this example, it captures a column range, making it easy to work with sequential data.

The .Sum() method is used to calculate the sum of the numeric values in the selected range. This highlights how IronXL allows developers to perform quick, built-in calculations on ranges of data, eliminating the need for manual iteration and summing.

Finally, the Console.WriteLine() statement outputs the calculated sum to the console. This is a simple but powerful way to display the result of your operations, such as the sum of values in a range, directly within your application.

With this approach, developers can easily automate data aggregation tasks or integrate them into larger workflows.

Click here to view the How-to Guide, including examples, sample code, and files >