使用 IRONXL FOR PYTHON 如何在 Python 中使用 Excel API 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 the realm of data manipulation and analysis, Excel stands as a stalwart, offering a rich array of features for organizing, analyzing, and visualizing data. Python, on the other hand, has emerged as a powerful language for data science and automation. Combining the capabilities of Microsoft Excel with the flexibility of Python opens up a world of possibilities. In this article, we'll delve into the world of Excel API Python, with a focus on IronXL for Python, a versatile library for working with Excel files in Python applications to automate Excel generation. How to use the Excel API in Python Install the Excel Python packages library using pip install. Import the required dependencies. Create the new workbook Excel object model using WorkBook.Create(). Initialize the worksheet object with the workbook.CreateWorkSheet() Excel function to write Excel files. Populate the cell value using the .Value variable. Save the Excel document with the SaveAs() method. 1. Understanding Excel API for Python Excel API for Python enables developers to access, analyze data, and interact with Excel files programmatically using Python code. Rather than manually performing tasks in Excel tools, such as data manipulation, data analysis, or report generation, developers can automate these processes, saving time and reducing errors. 2. Introducing IronXL for Python Among the various libraries available for Excel manipulation in Python, the IronXL for Python module stands out for its simplicity, performance, and extensive feature set. IronXL for Python library provides a comprehensive set of tools for creating, reading, editing, saving, and writing Excel files seamlessly within Python applications. 2.1. Features of IronXL for Python 2.1.1. Create and Modify Excel Files IronXL allows you to create new Excel files from scratch or manipulate Excel files. You can add worksheets, set cell values, apply formatting, insert charts, perform advanced analytics, and more, all through simple Python code. 2.1.2. Read Data from Excel Files With IronXL, you can extract data from Excel spreadsheet files effortlessly. Whether it's reading specific cells, retrieving entire rows or columns, or parsing complex data structures, IronXL provides intuitive methods to read Excel files. 2.1.3. Write Data to Excel Files IronXL makes it easy to write Excel files programmatically. You can populate cells with values, formulas, or even images, giving you full control over the content of your Excel sheets. 2.1.4. Format Cells and Worksheets Formatting is key to making Excel data visually appealing and easy to understand. IronXL enables you to apply various formatting options, such as font styles, colors, borders, and alignment, to cells and worksheets. 2.1.5. Generate Charts and Graphs Visualizing data is essential for gaining insights from Excel files. IronXL allows you to create various types of charts and graphs, including bar charts, line charts, pie charts, and scatter plots, directly from your Python code. 2.1.6. Support for Excel Formulas Excel's formula language is a powerful tool for performing calculations and data manipulation. IronXL supports Excel formulas, allowing you to evaluate formulas, set formula values in cells, and even create custom functions. 2.1.7. Export Data to Other Formats While Excel is a ubiquitous tool for data analysis, there are times when you need to export data to other formats. IronXL enables you to export Excel data to CSV, PDF, HTML, and other popular formats, making it easy to share or integrate Excel data with other systems. 2.1.8. Performance and Scalability IronXL is designed for performance and scalability, making it suitable for handling large Excel files and complex data sets. Whether you're processing thousands of rows or generating elaborate reports, IronXL delivers consistent performance. 3. Getting Started with IronXL Now that we've explored the features of IronXL, let's dive into how you can start using it in your Python projects. 3.1. Installation To install IronXL and run the Python function, we can use pip, the Python package manager. Simply run the command pip install ironxl in your terminal or command prompt, and IronXL will be installed in your Python code environment. 3.2. Importing the Library Once installed, you can import IronXL into your Python script using the following import statement: from ironxl import * from ironxl import * PYTHON 3.3. Creating and Modifying Excel Files To create a new Excel file with IronXL, you can use the following code snippet: from ironxl import * # Create a new workbook workbook = WorkBook.Create() # Create a new worksheet named "new_sheet" worksheet = workbook.CreateWorkSheet("new_sheet") # Set the value of cell A1 worksheet["A1"].Value = "Hello, IronXL!" # Save the workbook as "output.xlsx" workbook.SaveAs("output.xlsx") from ironxl import * # Create a new workbook workbook = WorkBook.Create() # Create a new worksheet named "new_sheet" worksheet = workbook.CreateWorkSheet("new_sheet") # Set the value of cell A1 worksheet["A1"].Value = "Hello, IronXL!" # Save the workbook as "output.xlsx" workbook.SaveAs("output.xlsx") PYTHON This code creates a new Excel workbook with a single worksheet and writes the text "Hello, IronXL!" to cell A1. The Excel workbook is then saved as "output.xlsx" in the current directory. 3.3.1. Output 3.4. Reading Data from Excel Files To read data from an existing Excel file, you can use the following code snippet: from ironxl import * # Load an existing workbook workbook = WorkBook.Load("output.xlsx") # Access the first worksheet worksheet = workbook.WorkSheets[0] # Retrieve the value from cell A1 cell_value = worksheet["A1"].Value # Print the cell value print(cell_value) from ironxl import * # Load an existing workbook workbook = WorkBook.Load("output.xlsx") # Access the first worksheet worksheet = workbook.WorkSheets[0] # Retrieve the value from cell A1 cell_value = worksheet["A1"].Value # Print the cell value print(cell_value) PYTHON This code loads an existing Excel file named "output.xlsx", retrieves the value from cell A1, and prints it to the console. 3.4.1. Output 3.5. Formatting Cells and Worksheets IronXL provides various methods for formatting cells and worksheets. For example, you can set the font style and size of Excel worksheets, apply background colors, add borders, and align text within cells. from ironxl import * # Load an existing workbook workbook = WorkBook.Load("output.xlsx") # Access the first worksheet worksheet = workbook.WorkSheets[0] # Retrieve cell A1 cell = worksheet["A1"] # Set the font style to bold cell.Style.Font.Bold = True # Set the background color of the cell cell.Style.SetBackgroundColor("#f0021a") # Save the workbook with applied styles workbook.SaveAs("stylingOptions.xlsx") from ironxl import * # Load an existing workbook workbook = WorkBook.Load("output.xlsx") # Access the first worksheet worksheet = workbook.WorkSheets[0] # Retrieve cell A1 cell = worksheet["A1"] # Set the font style to bold cell.Style.Font.Bold = True # Set the background color of the cell cell.Style.SetBackgroundColor("#f0021a") # Save the workbook with applied styles workbook.SaveAs("stylingOptions.xlsx") PYTHON This code snippet demonstrates to Excel users how to apply various formatting options to cell A1, such as making the text bold and setting the background color to red. 3.5.1. Output 3.6. Generating Charts and Graphs IronXL allows you to create charts and graphs directly from your Python code. For example, you can create a line chart with the following code: from ironxl import * # Load an existing workbook workbook = WorkBook.Load("test.xlsx") # Access the default worksheet worksheet = workbook.DefaultWorkSheet # Create a line chart chart = worksheet.CreateChart(ChartType.Line, 10, 10, 18, 20) # Add a series to the chart series = chart.AddSeries("A1:A5", "B1:B5") series.Title = "Line Chart" # Set legend position chart.SetLegendPosition(LegendPosition.Bottom) # Position the chart on the worksheet chart.Position.LeftColumnIndex = 2 chart.Position.RightColumnIndex = chart.Position.LeftColumnIndex + 3 # Plot the chart chart.Plot() # Save the workbook with the chart workbook.SaveAs("CreateLineChart.xlsx") from ironxl import * # Load an existing workbook workbook = WorkBook.Load("test.xlsx") # Access the default worksheet worksheet = workbook.DefaultWorkSheet # Create a line chart chart = worksheet.CreateChart(ChartType.Line, 10, 10, 18, 20) # Add a series to the chart series = chart.AddSeries("A1:A5", "B1:B5") series.Title = "Line Chart" # Set legend position chart.SetLegendPosition(LegendPosition.Bottom) # Position the chart on the worksheet chart.Position.LeftColumnIndex = 2 chart.Position.RightColumnIndex = chart.Position.LeftColumnIndex + 3 # Plot the chart chart.Plot() # Save the workbook with the chart workbook.SaveAs("CreateLineChart.xlsx") PYTHON This code adds a line chart to the worksheet, using data from cells A1 to A5 as the category labels and data from cells B1 to B5 as the series values. The chart title is set to "Line Chart". 3.6.1. Output 4. Conclusion In conclusion, IronXL for Python is a powerful library for working with Excel files in Python applications. With its intuitive API and extensive feature set, IronXL simplifies the process of creating, reading, modifying, and saving Excel files, enabling developers to automate data manipulation tasks, generate reports, and visualize and analyze data, with ease. Whether you're a data scientist, a business analyst, or a software developer, IronXL empowers you to harness the full potential of Excel in your Python projects. So why wait? Start exploring the possibilities of IronXL today and unlock the power of Excel with Python. 常見問題解答 怎樣在 C# 中將 HTML 轉換為 PDF? 您可以使用 IronPDF 的 RenderHtmlAsPdf 方法將 HTML 字符串轉換為 PDF。您還可以使用 RenderHtmlFileAsPdf 將 HTML 文件轉換為 PDF。 IronXL 為什麼是一個用於 Python 中處理 Excel 文件的多功能庫? IronXL for Python 是一個多功能庫,允許開發者在 Python 應用程序中處理 Excel 文件。它簡化了以程式化方式創建、閱讀、編輯、保存和寫入 Excel 文件的過程。 如何安裝用於處理 Excel 文件的 Python 庫? 要安裝 IronXL,使用 Python 包管理器 pip,在終端或命令提示符中執行命令 pip install ironxl。 在 Python 中以編程方式創建新 Excel 文件的最佳方法是什麼? 您可以使用 WorkBook.Create() 方法創建工作簿,然後使用 workbook.CreateWorkSheet() 添加工作表並填充單元格,然後使用 workbook.SaveAs() 保存文件。 IronXL 能有效處理大型 Excel 文件嗎? 是的,IronXL 是為性能和可擴展性而設計的,適合有效處理大型 Excel 文件和複雜數據集。 IronXL for Python 的一些高級功能是什麼? IronXL 允許您應用各種格式選項,如字體樣式、顏色、邊框和對齊方式,增強 Excel 數據的視覺吸引力和可讀性。它還支持創建圖表、處理公式和導出數據到多種格式。 如何使用 IronXL 從 Excel 文件中讀取數據? 要讀取數據,使用 WorkBook.Load() 加載現有工作簿,訪問所需工作表,並使用工作表對象檢索單元格值。 Python 開發者如何受益於使用 IronXL? IronXL 使數據科學家、軟件開發者和商業分析師能夠在 Python 應用程序中充分利用 Excel 的潛力,便利有效的數據分析和報告。 是否可選擇使用 IronXL 將 Excel 數據導出到其他格式? 是的,IronXL 支持導出數據到多種格式,如 CSV、PDF 和 HTML,提供您管理和共享 Excel 數據的靈活性。 IronXL 可以用來在 Excel 中生成圖表嗎? 是的,IronXL 支持直接從 Python 程式碼創建各種類型的圖表和圖形,包括折線圖、柱狀圖、餅圖和散點圖。 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 如何使用 Python 導出到 Excel 文件如何在 Excel 文件中使用 Pyt...
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