使用 IRONXL FOR PYTHON 在不需要 Pandas 的情況下,使用 Python 讀取 Excel 文件(無需 Interop) Curtis Chau 更新日期:6月 22, 2025 Download IronXL pip 下載 Start Free Trial Copy for LLMs Copy for LLMs Copy page as Markdown for LLMs Open in ChatGPT Ask ChatGPT about this page Open in Gemini Ask Gemini about this page Open in Grok Ask Grok about this page Open in Perplexity Ask Perplexity about this page Share Share on Facebook Share on X (Twitter) Share on LinkedIn Copy URL Email article Reading Microsoft Excel files in Python is an essential skill for various data-related tasks and has become a standard practice in fields like data science, data analysis, business intelligence, and automation. Excel is one of the most commonly used tools for storing and organizing data due to its user-friendly interface and extensive features. When dealing with Microsoft Excel, pandas is the first library that comes to mind, but there are other robust libraries like IronXL which deliver performance and speed. IronXL for Python is a robust library designed to work with Excel files. It allows developers to create, read, analyze data, and manipulate Excel spreadsheets seamlessly. The main advantages of using IronXL include its ease of use, powerful functionalities, and the fact that it does not require Microsoft Excel to be installed on the server. How to Read Excel File in Python Without Pandas Using IronXL Step 1: Import the IronXL Library. Step 2: Add License Key. Step 3: Load the Excel File. Step 4: Read Excel files using IronXL. Introducing IronXL IronXL provides robust features for handling Excel files, including support for multiple sheets, cell formatting, reading and writing different file formats (like .xlsx and .xls), and working with large datasets, making it a versatile tool for data manipulation tasks. Key Features of IronXL for Python Library Easy Excel File Handling: IronXL simplifies the process of reading, writing, and editing Excel files in Python. Using IronXL, you can manipulate Excel files and save them with ease. It also supports CSV files and XLS files. Multiple Sheet Support: IronXL can easily read and write data across multiple sheets within a single Excel workbook. This is ideal when dealing with Excel files that contain different types of data or reports across various sheets. Read and Write Data: Reading Data: IronXL allows you to access individual cells or entire rows and columns in an Excel file. It supports reading values from all types of cells including text, numbers, and dates. Writing Data: The library supports writing Excel files, whether you need to update existing cells or add new data to the file. It also supports CSV format without importing the CSV module, XLSX files. Cell Formatting: IronXL provides the ability to format Excel cells. You can set text color, font size, borders, and other visual styles directly within the Python script. This is useful for creating reports with specific formatting or when you need to highlight certain data points. Compatibility with Various Excel Formats: IronXL can handle multiple Excel file formats, including .xlsx file format, .xls file format, and .csv file format. This makes it a versatile choice for interacting with Excel files that are shared or exported from various systems. Support for Large Files: IronXL is optimized to handle large Excel files with many rows and columns, making it suitable for data analysis tasks that involve massive datasets. Cross-Platform: While IronXL is built on .NET technologies, it is cross-platform and can be used on Windows, macOS, and Linux through Python. Step 1: Import the IronXL Library Import IronXL using the Python package manager for reading Excel spreadsheet data. pip install ironxl pip install ironxl SHELL Next, import the necessary libraries from IronXL: from ironxl import License, WorkBook, WorkSheet from ironxl import License, WorkBook, WorkSheet PYTHON Step 2: Add License Key IronXL needs a license key. Get your free license from here and place the license at the top of the code. License.LicenseKey = "Your Key" License.LicenseKey = "Your Key" PYTHON Step 3: Load the Excel File Load the Excel file using the WorkBook.Load() function. This method returns a Workbook object, which represents the entire Excel file. # Load the workbook workbook = WorkBook.Load('sample.xlsx') # Load the workbook workbook = WorkBook.Load('sample.xlsx') PYTHON Step 4: Read Excel Files Using IronXL Now use the workbook object to read the sheets and then read the data in the sheets. # Iterate over all worksheets for sheet in workbook.WorkSheets: print(f"Sheet Name: {sheet.Name}") for row in sheet.Rows: # Print each row's values print([cell.Value for cell in row]) # excel data # Iterate over all worksheets for sheet in workbook.WorkSheets: print(f"Sheet Name: {sheet.Name}") for row in sheet.Rows: # Print each row's values print([cell.Value for cell in row]) # excel data PYTHON Complete Code Input Excel File from ironxl import License, WorkBook, WorkSheet # Set the IronXL license key License.LicenseKey = "Your Key" # Load the Excel workbook workbook = WorkBook.Load('sample.xlsx') # Iterate through the sheets in the workbook for sheet in workbook.WorkSheets: # Print the name of each sheet print(f"Sheet Name: {sheet.Name}") # Iterate through the rows in the current sheet for row in sheet.Rows: # Print each row's values as a list print([cell.Value for cell in row]) from ironxl import License, WorkBook, WorkSheet # Set the IronXL license key License.LicenseKey = "Your Key" # Load the Excel workbook workbook = WorkBook.Load('sample.xlsx') # Iterate through the sheets in the workbook for sheet in workbook.WorkSheets: # Print the name of each sheet print(f"Sheet Name: {sheet.Name}") # Iterate through the rows in the current sheet for row in sheet.Rows: # Print each row's values as a list print([cell.Value for cell in row]) PYTHON Code Explanation The provided code demonstrates how to use IronXL to read data from an Excel file with multiple sheets. Here's an explanation of the code step by step: 1. License Key Setup The first line of the code sets up the IronXL license by specifying the license key using the License.LicenseKey property. This is required for activating the IronXL library and ensuring it can be used without restrictions. 2. Loading the Excel Workbook The second line uses the WorkBook.Load() method to load an Excel file (sample.xlsx) into a WorkBook object. This object represents the entire workbook (i.e., the Excel file) and contains all the sheets and data within the file. 3. Iterating Through Sheets The code then begins a loop through the sheets in the workbook. The WorkBook.WorkSheets property gives access to all the sheets in the loaded workbook. For each sheet, it prints the name of the sheet using sheet.Name. This is useful for identifying which sheet is being processed, especially when working with multiple sheets. 4. Reading and Printing Data from Each Sheet Within each sheet, the code loops through each row using sheet.Rows. Each row is a collection of cells in that specific row. The code then extracts the value of each cell in the row using cell.Value, and prints it as a list for each row. Output IronXL License (Trial Available) IronXL works on a valid license key in the code. Users can easily get a trial license from the license page. To use the license, place the license somewhere in the code as shown below before using the IronXL library. ironxl.License.LicenseKey = "Your License Key" ironxl.License.LicenseKey = "Your License Key" PYTHON Conclusion IronXL is the best alternative to the pandas module when it comes to handling Excel files. It provides a powerful and straightforward way to handle Excel files in Python without the need to import pandas. It supports various Excel formats, making it an excellent choice for developers looking to automate data processing and reporting tasks. Developers looking for a pandas alternative can easily start using IronXL, which has full support for reading, writing, and manipulating Excel sheets. 常見問題解答 如何在Python中不使用pandas讀取Excel文件? 您可以使用IronXL在不使用pandas的情況下在Python中讀取Excel文件。IronXL提供了加載Excel文件和訪問其數據的方法,使其成為一個穩健的替代方案。 在Python中使用IronXL讀取Excel文件的優勢是什麼? IronXL提供性能和速度優勢,無需安裝Microsoft Excel,支持多工作表,並能有效處理大型數據集,對於數據處理任務非常有利。 如何在Python中安裝IronXL? 要在Python中安裝IronXL,使用命令 pip install ironxl 下載並設置在您的Python環境中。 IronXL能處理多個工作表的Excel文件嗎? 可以,IronXL支持在單個Excel工作簿內讀寫多個工作表的數據,使其適合處理複雜數據集。 能否使用IronXL讀取大型Excel文件? IronXL對於擁有大量行和列的大型Excel文件進行了優化,使其適合處理龐大的數據集。 如何在Python中設置IronXL的license? 您可以在Python腳本中使用 License.LicenseKey 屬性設置IronXL的license key。可從IronXL許可證頁面獲得試用許可證。 IronXL能讀取哪些文件格式的Python文件? IronXL支持多種Excel文件格式,包括.xlsx、.xls和.csv,使其適用於不同的數據處理需求。 IronXL是一個跨平台的庫嗎? 是的,IronXL是一個跨平台的庫,可以通過Python在Windows、macOS和Linux上使用,儘管它是基於.NET技術構建的。 在Python中使用IronXL加載Excel文件的過程是什麼? 您可以使用IronXL的 WorkBook.Load() 方法加載Excel文件,該方法返回一個代表整個Excel文件的WorkBook對象。 IronXL進行Excel文件操作的主要功能是什麼? IronXL提供了簡單的Excel文件處理、多工作表支持、數據讀寫功能、單元格格式設置選項、與多種Excel格式的兼容性,以及有效管理大型數據集的能力。 Curtis Chau 立即與工程團隊聊天 技術作家 Curtis Chau 擁有卡爾頓大學計算機科學學士學位,專注於前端開發,擅長於 Node.js、TypeScript、JavaScript 和 React。Curtis 熱衷於創建直觀且美觀的用戶界面,喜歡使用現代框架並打造結構良好、視覺吸引人的手冊。除了開發之外,Curtis 對物聯網 (IoT) 有著濃厚的興趣,探索將硬體和軟體結合的創新方式。在閒暇時間,他喜愛遊戲並構建 Discord 機器人,結合科技與創意的樂趣。 相關文章 更新日期 6月 22, 2025 如何在 Python 中讀取具有多個工作表的 Excel 文件 在這篇文章中,我們將探討如何使用 IronXL for Python 讀取多個 Excel 工作表,包括那些具有多個工作表的文件。 閱讀更多 更新日期 6月 22, 2025 如何使用 Python 將圖片插入 Excel 這篇文章將指導您使用 IronXL 在 Python 中將圖像插入 Excel 的過程。 閱讀更多 更新日期 6月 22, 2025 如何在 Python 中創建 Excel 文件 這是使用 Python 自動化數據管理和報告任務創建 Excel 工作表文件最強大和有效的方法之一。 閱讀更多 如何在 Python 中讀取具有多個工作表的 Excel 文件如何使用 Python 將圖片插入...
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