How to use Python to read Excel spreadsheets

Effective data management and processing is essential for both individuals and enterprises in the data-driven world of today. Because of its convenience and adaptability, Excel spreadsheets continue to be one of the most widely used file formats for data organization and storage. With its robust libraries, the Python programming language provides an abundance of tools for working with Excel files.

The IronXL library is one of these tools and is one of the most reliable options to read and write Excel files easily. This tutorial will cover the nuances of using IronXL (in Python) to read Excel spreadsheet files, giving users the ability to read Excel files and optimize their workflows for data management.

How to use Python to read Excel spreadsheet

1. Open Visual Studio Code and create a Python file.
2. Use pip to install the IronXL library for Python.
3. Open the Excel document that needs to be read.
4. Iterate through Excel data using loops.
5. Display recurrent data on the console.

IronXL

IronXL is a feature-rich Python library created specifically for use with Excel files. It offers programmers a multitude of options for reading, editing, and modifying spreadsheet data. Built on top of the .NET framework, IronXL provides an effective way to interact with Excel files by combining the performance of .NET with the flexibility of Python.

One of its main features is IronXL's ability to read data from current Excel files with ease. Developers can effortlessly extract data from specific files, such as object cells, rows, lists of column names, numeric columns, or deal with missing values within Excel spreadsheets, enabling seamless integration of Excel data into Python programs. IronXL offers the resources required to efficiently access and manipulate Excel data, whether it be for financial, customer, or sales data retrieval.

Features of IronXL

IronXL facilitates the seamless reading of data from pre-existing Excel files and the writing of data to newly created or pre-existing spreadsheets. This covers a variety of topics such as formulae, formatting, and cell value access.

Key Feature Examples

• Cross-Platform Compatibility: IronXL is an adaptable option for Python developers regardless of their operating system because it is made to function flawlessly across a variety of platforms, including Windows, Linux, and macOS.
• Efficient Processing: IronXL, built on top of the .NET framework, combines the efficiency of .NET with the flexibility of Python to process and manipulate Excel files efficiently, even when dealing with enormous datasets.
• Support for Various Excel Formats: IronXL is compatible with a wide range of Excel files and supports the following formats: .xls (Excel 97-2003), .xlsm (Excel with macros enabled), and .xlsx (Excel 2007 onwards).
• Advanced Data Manipulation: IronXL gives users the ability to manipulate data in Excel spreadsheets in a more sophisticated way, allowing them to extract insightful information from their data through operations like sorting, filtering, and aggregating.
• Cell Formatting: Excel spreadsheets can be made more aesthetically pleasing and readable by using IronXL's cell formatting features, which include font styles, colors, borders, and alignment.
• Formula Calculation: IronXL allows users to work with Excel formulas, including formula evaluation, formula reference updating, and dynamic calculations within Excel spreadsheets.
• Integration with the Python Environment: IronXL easily incorporates into the Python environment, enabling users to combine its features with those of other Python frameworks and packages for in-depth data visualization and analysis.
• Ease of Use: Both inexperienced and seasoned Python developers can utilize IronXL thanks to its user-friendly, straightforward API. Its well-documented interface offers precise instructions on how to make the most of its features.

In summary, IronXL provides a stable and user-friendly way to incorporate Excel features into Python apps, enabling Python developers to overcome the difficulties involved in handling Excel files. Whether you're developing interactive dashboards, automating reporting tasks, or developing data analysis tools, IronXL offers the flexibility and resources required to succeed in manipulating Excel files within the Python ecosystem.

To know more about the IronXL library and all of its features, check here.

Setup Environment

Prerequisites

Make sure you have the following installed on your PC before beginning the tutorial:

• .NET 6.0 SDK: Because IronXL is designed with the .NET 6.0 SDK, your machine must have this installed.
• Python 3.0+: This tutorial assumes that you have installed Python 3.0 or a later version.
• pip: Install pip first, the Python package installer, since IronXL will require it.

Install IronXL

Open Visual Studio Code and create a Python file named ReadSpreadsheet.py. This file will contain our script for reading Excel files with IronXL.

To access the command line in Visual Studio Code, go to the menu and click Terminal > New Terminal.

Installing the library is the first step to take before utilizing IronXL. Using Python's package manager pip, you can quickly install IronXL by running the following command:

pip install ironxl

pip install ironxl

Now that IronXL is installed, you may use its Excel spreadsheet file reading capabilities.

Reading Excel spreadsheet

IronXL makes it easy to conduct data analysis in an Excel spreadsheet. To begin, let us import data from a pre-existing Excel sheet file format into our Python environment:

from ironxl import *     # Import IronXL library for Excel operations

# Load the Excel file
workbook = WorkBook.Load("Demo.xlsx")

# Access the default worksheet (usually the first one)
worksheet = workbook.DefaultWorkSheet

# Access a specific cell value
cell_value = worksheet["A1"].StringValue

# Access row values as a string
row_values = worksheet.Rows[1].StringValue

# Access column values as a string
column_values = worksheet.Columns[0].StringValue

# Iterate over all rows and print their values
for row in worksheet.Rows:
    print(row.StringValue)

from ironxl import *     # Import IronXL library for Excel operations

# Load the Excel file
workbook = WorkBook.Load("Demo.xlsx")

# Access the default worksheet (usually the first one)
worksheet = workbook.DefaultWorkSheet

# Access a specific cell value
cell_value = worksheet["A1"].StringValue

# Access row values as a string
row_values = worksheet.Rows[1].StringValue

# Access column values as a string
column_values = worksheet.Columns[0].StringValue

# Iterate over all rows and print their values
for row in worksheet.Rows:
    print(row.StringValue)

We use the location of our Excel file to instantiate the WorkBook class after importing it from IronXL. In doing so, we generate a workbook object that we can use to access and retrieve the spreadsheet's contents. Once we've loaded it into a workbook object, we can access the Excel spreadsheet's data, including cell values, rows, and columns stored in the object. IronXL Excel workbooks additionally offer simple ways to make and get data from multiple Excel sheets.

We can obtain the value of a single cell (e.g., A1), as well as tabular data such as the values of a specific row, column labels, and a list of column names. Working with data often involves looping through the rows and columns of an Excel spreadsheet. IronXL simplifies this process with its handy iteration techniques. We can easily process and manipulate the data contained within the Excel sheet by iterating over each row, column index, and cell.

By reading the above Excel file, we will get the following output from IronXL.

To learn about IronXL code refer here.

Conclusion

Finally, IronXL for Python allows developers to overcome the difficulties involved in processing Excel files by acting as a bridge between Python and Excel files. IronXL is a feature-rich tool that offers a stable and user-friendly way to include Excel file functionality into Python programs. It can read and write data, format cells, visualize data, work with formulas, and is compatible across multiple platforms. IronXL for Python provides the flexibility and tools required to succeed in Excel file manipulation within the Python ecosystem, regardless of your background as a software developer, data scientist, or business analyst.

Whether you work as a software developer, business analyst, sales data miner, or data scientist, IronXL can help you become an expert spreadsheet reader and open up a world of possibilities for productive data manipulation. Use IronXL to read an Excel file and explore the realm of data management, increasing your Python knowledge.

IronXL's $749 Lite edition comes with a year of software support, upgrade options, and a permanent license. Customers have the opportunity to assess the product in practical settings throughout the trial time. Please visit the license page. Alternatively, to find out more about Iron Software, visit this page.