使用 IRONXL FOR PYTHON 如何在 Python 中查看 Excel 文件 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 In this tutorial, we will explore how to use Python for viewing Excel files effectively. Excel files, commonly used for data storage such as storing tabular data, are well-supported by several Python libraries that facilitate reading and manipulation. We will focus on the popular and best library "IronXL" for this purpose. How to View an Excel File in Python Install the IronXL Library. Load the Excel Workbook. Specify the Excel Worksheet. Select a Specific Range of Data. Print the Selected Data Range on the Screen. Read Cell Value. Read Complete Row from Excel File. Read the Complete Column from the Excel file. Introduction to Python Excel Viewer Before diving into the code, let's discuss the benefits of using Python to view Excel files. Python is well known for its simplicity and versatility, making it a powerful and robust programming language. By leveraging Python libraries, we can automate tasks related to data analysis, manipulation, and visualization, including handling Excel files. Why Python for Excel? Automation: Python enables the automation of repetitive tasks associated with Excel, such as data extraction, transformation, and analysis. Integration: Python seamlessly integrates with other data science libraries like NumPy, pandas, and Matplotlib, enabling comprehensive data analysis workflows. Cross-platform: Python, in its latest Python version, runs on multiple platforms, making it suitable for users across different operating systems. Customization: Python provides flexibility to customize Excel workflows according to specific requirements, unlike conventional Excel macros. Before proceeding further, let's understand what IronXL is, what features it provides, and how it is better than others. Why IronXL? IronXL is a Python library developed and maintained by Iron Software that allows software engineers to work with Excel and other spreadsheet files in Python applications and websites. Below are some of its notable key features: Importing Data: IronXL can read data from XLS, XLSX, CSV, and TSV files. Export Work Sheets: You can export data to XLS, XLSX, CSV, TSV, and JSON formats. Encryption and Decryption: IronXL supports encrypting and decrypting XLSX, XLSM, and XLTX files with passwords. Excel Formulas: Every time a sheet is edited, the formulas are recalculated. Intuitive Ranges Setting: You can specify ranges using a syntax like "A1:B10". Sorting: Ranges, columns, and rows can be sorted. Cell Styling: Customize font, size, background pattern, border, and alignment. Cross-Platform Support: IronXL is compatible with Python 3.7+ on Windows, macOS, Linux, Docker, Azure, and AWS. Reading Excel File using IronXL Let's begin step by step to read an Excel file. Step 1: Installing IronXL Library Before working with Excel files in Python, we need to ensure that the IronXL Library is installed. Install it with the following command. pip install IronXL pip install IronXL SHELL This command installs the IronXL Library in our project. Step 2: Load Excel file The next step involves loading an Excel workbook into our project. I will be using the following Excel spreadsheet throughout this tutorial. The following code will load the existing Excel file in the memory stream. from ironxl import * # Supported for XLSX files, XLS, XLSM, XLTX, CSV, and TSV License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-ABC.TRIAL.EXPIRES.27.MAY.2024" workbook = WorkBook.Load("test_excel.xlsx") # Load existing Excel files from ironxl import * # Supported for XLSX files, XLS, XLSM, XLTX, CSV, and TSV License.LicenseKey = "IRONSUITE.ABC.XYZ.COM.15796-ABC.TRIAL.EXPIRES.27.MAY.2024" workbook = WorkBook.Load("test_excel.xlsx") # Load existing Excel files PYTHON The above code demonstrates how to use the IronXL library in Python to load an Excel workbook named "test_excel.xlsx" and access its contents. By setting the LicenseKey attribute with a valid license key, the library enables support for various Excel file formats including XLSX, XLS, XLSM, XLTX, CSV, and TSV. You can get your free license key from here. Step 3: Select Excel Spreadsheet The next step is to select an Excel spreadsheet to work on. Excel files consist of multiple sheets; therefore, it is necessary to select an active spreadsheet. The following code will specify the spreadsheet. # Select worksheet at index 0 worksheet = workbook.WorkSheets[0] # Select worksheet at index 0 worksheet = workbook.WorkSheets[0] PYTHON The above line of code selects the first worksheet with zero-indexed from the loaded Excel workbook, enabling access to the data and properties of that specific sheet for further manipulation or analysis. Step 4: Viewing Data As we have loaded the workbook and selected the spreadsheet, let's write code to read an Excel file and print its data. # Read from ranges of cells elegantly. for cell in worksheet["A1:H10"]: print("Cell {} has value '{}'".format(cell.AddressString, cell.Text)) # Read from ranges of cells elegantly. for cell in worksheet["A1:H10"]: print("Cell {} has value '{}'".format(cell.AddressString, cell.Text)) PYTHON This code snippet demonstrates a sophisticated method for reading from cell ranges in an Excel worksheet using the IronXL library. It iterates over the specified range of cells (from A1 to H10 in this case) and prints out each cell's address and value. This provides a concise and effective method for accessing and processing data within the specified range of cells. Step 5: Read Cell Value IronXL provides simpler methods to read cell values. We can efficiently read specific cell values from large datasets. The following code reads the cell value and prints it on the screen. # Read Integer value int_cell_value = worksheet["H2"].IntValue print(int_cell_value) # Read String value text_cell_value = worksheet["B2"].StringValue print(text_cell_value) # Read Integer value int_cell_value = worksheet["H2"].IntValue print(int_cell_value) # Read String value text_cell_value = worksheet["B2"].StringValue print(text_cell_value) PYTHON This code snippet demonstrates how to extract an integer value from cell H2 and a string value from cell B2 in an Excel worksheet using the IronXL library. It then prints out the extracted values, providing clear and organized output for further processing or display. Step 6: Select Complete Row IronXL provides a method to select a specific row from an Excel file. The following code will read a specific row from the Excel file and print it on the screen. # Get row from worksheet row_1 = worksheet.GetRow(1) print(row_1) # Get row from worksheet row_1 = worksheet.GetRow(1) print(row_1) PYTHON This code snippet demonstrates how to retrieve a specific row from an Excel worksheet using the IronXL library. It selects the first row (row index 1) from the worksheet and then prints it out, allowing for further processing or analysis of the row's data. In this way, we can get all the rows from the Excel sheet. Step 7: Select Complete Column IronXL provides a method to select a specific Column from an Excel file. The following code will read a specific Column from the Excel file and print it on the screen. # Get Column from worksheet column_a = worksheet.GetColumn(1) print(column_a) # Get Column from worksheet column_a = worksheet.GetColumn(1) print(column_a) PYTHON This code snippet illustrates how to extract a specific column from an Excel worksheet using the IronXL library. It retrieves the data from column A (column index 1) and prints it out, providing access to the column's contents for further manipulation or analysis. Conclusion In this tutorial, we explored how to use Python for Excel file viewing, focusing on the IronXL library. Python's versatility makes it ideal for automating Excel-related tasks, and IronXL enhances this capability by providing features like importing options for individual developers and organizations. With IronXL and Python, handling Excel files becomes more efficient, enabling developers to unlock the full potential of Excel data within their applications. 常見問題解答 我如何使用 Python 檢視 Excel 文件? 您可以使用 IronXL 庫在 Python 中檢視 Excel 文件。它提供加載工作簿、選擇工作表、讀取特定數據範圍或單元格值的功能。 要使用 Python 檢視 Excel 文件,我需要安裝什麼? 要使用 Python 檢視 Excel 文件,需安裝 IronXL 庫,可使用 pip 命令安裝:`pip install IronXL`。 我如何在 Python 中加載 Excel 工作簿? 使用 IronXL,您可以使用如下代碼加載 Excel 工作簿:workbook = WorkBook.Load('test_excel.xlsx'),該代碼將指定的 Excel 文件加載到內存中。 IronXL 支持哪些 Excel 操作的檔案格式? IronXL 支持各種文件格式,包括 XLSX、XLS、CSV 和 TSV,這使其在不同的 Excel 操作中非常靈活。 我如何使用 Python 從 Excel 文件中讀取特定的單元格值? 要使用 IronXL 讀取特定的單元格值,您可以使用 worksheet['H2'].IntValue 讀取整數或 worksheet['B2'].StringValue 讀取字符串值。 IronXL 能夠處理 Excel 文件的加密和解密嗎? 是的,IronXL 可以處理 Excel 文件的加密和解密,為您的數據提供了額外的安全層。 IronXL 是否與不同的操作系統兼容? 是的,IronXL 與 Python 3.7 及更高版本兼容,並支持在 Windows、macOS、Linux、Docker、Azure 和 AWS 上進行跨平台操作。 我如何使用 Python 從工作簿中選擇特定的工作表? 要使用 IronXL 從工作簿中選擇特定的工作表,您可以使用代碼 worksheet = workbook.WorkSheets[0] 選擇第一個工作表。 使用 IronXL 進行 Excel 文件操作的好處是什麼? IronXL 提供了便於集成到 Python 應用程序中的功能,對各種文件格式的強大支持,先進的數據處理能力,以及跨平台兼容性。 我如何使用 Python 自動化 Excel 任務? Python 配合像 IronXL 這樣的庫,可以讓您自動化如數據分析、可視化和操作的 Excel 任務,提升生產力和效率。 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 在不需要 Pandas 的情況下,使用 Python 讀取 Excel 文件(無需 Interop) 處理 Microsoft Excel 時,pandas 是首先想到的庫,但還有其他強大的庫如 IronXL,提供性能和速度。 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 如何在 Python 中讀取 Excel 文件Python 保護 Excel(開發者教程)
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 在不需要 Pandas 的情況下,使用 Python 讀取 Excel 文件(無需 Interop) 處理 Microsoft Excel 時,pandas 是首先想到的庫,但還有其他強大的庫如 IronXL,提供性能和速度。 閱讀更多