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使用 IRONXL

如何在 Python 中解析 Excel 文件

Curtis Chau
Curtis Chau
已更新:

Spreadsheets made with Microsoft Excel are widely used in workflows for data processing and analysis in many different sectors. Python is a versatile programming language with several libraries for working with Excel files. One such library, IronXL, was created especially for .NET programs like IronPython and offers a smooth connection with Excel files. This in-depth tutorial will examine how to parse an Excel file in Python using IronXL.

  1. Create a new Python project or create a new file with the .py extension.
  2. Install the IronXL library.
  3. Import the required library.
  4. Import the file which needs to be parsed.
  5. Access the specific sheet and parse the values.
  6. Process the values and close the created objects.

IronXL

With the IronXL Python library, developers can effortlessly read and write Excel files in Python. You can work with several Excel sheets at once in addition to writing Excel files. You can manipulate Excel files using this library without having to install Microsoft Excel on your computer.

IronXL is useful when you need to import data directly into an Excel spreadsheet. Using IronXL simplifies the handling of Excel spreadsheets. It facilitates the simple management of data in an XLSX file across several sheets.

Key characteristics of IronXL

1. Reading and Writing Data to and from Excel Files

IronXL makes it simple for developers to read and write data to and from Excel files. IronXL offers simple ways to read from and manipulate Excel files, whether you're pulling data for analysis or creating reports.

2. Support for a Broad Range of Excel Formats

IronXL is compatible with a number of Excel formats, such as .csv, .xls, .xlsx, .xlsm, .xlsb, .xltx, and .xltm. This adaptability guarantees compatibility with many Excel file formats and versions, enabling smooth working with Excel files of any format.

3. Worksheet and Cell Access

Developers may quickly access specific worksheets and cells in Excel workbooks by using IronXL. This makes it possible to precisely manipulate data at the worksheet and cell levels, making activities like data entry, editing, and extraction easier.

4. Formatting and Style

IronXL offers extensive assistance with the formatting and style of Excel files. Excel files can be made more aesthetically pleasing and readable by developers by applying a variety of formatting choices, including font styles, colors, borders, alignment, and more, to individual cells, rows, and columns.

5. Formula Calculation

IronXL has functionality for calculating Excel formulas, enabling programmers to assess formulas inside Excel documents. This capability is perfect for situations where automated data processing and analysis are needed since it allows complicated calculations and formulas to be executed.

6. Chart Generation

With IronXL, developers may use programming to generate and modify charts inside of Excel files. Developers can use this functionality to show correlations, trends, and patterns in data using a variety of chart formats, including pie charts, bar charts, and line charts.

7. Data Validation

IronXL has data validation capabilities that let developers set limitations and guidelines for entering data into Excel files. By restricting users from entering erroneous or incorrect data, this function helps maintain data integrity and guarantees the quality and dependability of Excel documents.

8. Performance Optimization

IronXL has been designed with performance in mind, making it capable of handling large Excel files and datasets with ease. IronXL's specialized algorithms and data structures offer quick and dependable performance while reading, writing, and modifying data—even when working with large Excel spreadsheets.

9. Thorough Documentation and Support

To assist developers in getting started quickly and making the most of IronXL's features, the tool provides a wealth of documentation that includes tutorials, guides, and API references. In addition, Iron Software offers committed assistance to help developers with any queries or problems they could run across when utilizing the library.

To know more about the IronXL documentation, refer here.

Prerequisites

Make sure the following prerequisites are installed on your machine before beginning the tutorial:

  • .NET framework: Your machine must have the .NET 6.0 SDK installed.
  • Python 3.0+: You must have Python 3.0 or higher installed in order to follow this tutorial.
  • pip: Since IronXL will be installed via pip, make sure pip, the Python package installer, is installed.

Setting Up Your Environment

1. Creating a File in Visual Studio Code

Launch Visual Studio Code, then create the ParseExcel.py Python file. This file will include our IronXL script for reading Excel files.

How to parse an Excel file in Python: Figure 1 - Open Visual Studio Code editor and create a new file

2. Installing IronXL

In Visual Studio Code, choose Terminal > New Terminal from the menu to launch the command line.

How to parse an Excel file in Python: Figure 2

To install IronXL, execute the subsequent command:

pip install ironxl
pip install ironxl
SHELL

How to parse an Excel file in Python: Figure 3 - To install IronXL, use the following command: pip install ironxl

Parse Excel files using IronXL

The process to read Excel files is made easy with the help of the IronXL library. Parsing Excel files in Python can be easily done with a few lines of code.

from ironxl import *

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

# Accessing the first worksheet
worksheet = workbook.WorkSheets[0]

# Iterate over each row and column
for row in range(worksheet.RowCount):
    for col in range(worksheet.ColumnCount):
        # Get the value of each cell
        cell_value = worksheet.Columns[col].Rows[row].Value
        print(cell_value)

# Close the workbook to free up system resources
workbook.Close()
from ironxl import *

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

# Accessing the first worksheet
worksheet = workbook.WorkSheets[0]

# Iterate over each row and column
for row in range(worksheet.RowCount):
    for col in range(worksheet.ColumnCount):
        # Get the value of each cell
        cell_value = worksheet.Columns[col].Rows[row].Value
        print(cell_value)

# Close the workbook to free up system resources
workbook.Close()
PYTHON

The first step is to import the required IronXL modules into your script. Next, use the WorkBook class in IronXL to import Excel files. Replace "Demo.xlsx" with the path to your Excel file, or use a different file format like CSV, XLS, or XLSX. You can access individual Excel sheets inside the workbook once the Excel file has loaded using the WorkBook.Load() method. The IronXL library also allows access to multiple Excel sheets using the index or sheet names.

Next, we extract data from the Excel file by iterating over rows and columns while accessing the worksheet. This code prints the value of each spreadsheet cell as it iterates over them. This logic can be adjusted to meet your unique needs, such as gathering data for additional processing or examination. It is imperative to close the Excel file using the workbook.Close() method once you have completed processing it in order to free up system resources.

Output generated from the above code

How to parse an Excel file in Python: Figure 4 - Output generated using IronXL to read and extract data from an excel file.

To learn more about the IronXL code, refer here.

Conclusion

An efficient way to work with Excel spreadsheets in your Python programs is to parse Excel files using IronXL. Through the combination of IronXL with IronPython, developers may effectively manage data by utilizing the combined capabilities of Excel and .NET. By following the instructions in this article and using the example, you can easily parse Excel files in your Python applications. This opens up a world of possibilities for data analysis and manipulation. IronXL is a useful tool for interacting with Excel files in Python programs because of its user-friendly API and comprehensive documentation.

Recall that there are a plethora of options available for processing and presenting data. Having IronXL in your toolbox gives you the ability to manage a variety of activities linked to Excel in your Python programs.

When ready to commit, users can start using IronXL for free with its trial version. After that, license choices start at $799. To know more about the IronXl license, please refer to the license page.

To know more about other products offered by Iron Software, please check their website.

常见问题解答

如何在Python中解析Excel文件？

要使用IronXL在Python中解析Excel文件，首先导入必要的库，然后使用WorkBook.Load()加载工作簿。访问所需的工作表，遍历行和列，并提取单元格值。

是否可以在不安装Microsoft Excel的情况下在Python中操作Excel文件？

是的，使用IronXL，你可以在不需要安装Microsoft Excel的情况下在Python中操作Excel文件。IronXL允许你直接在Python应用程序中读取、写入和处理Excel文件。

IronXL支持哪些Excel格式？

IronXL支持多种Excel格式，确保在各种文件类型的读写操作中兼容。

IronXL能有效管理大数据集吗？

是的，IronXL优化了性能，可以有效处理大型Excel文件和数据集，使其适用于数据密集型应用程序。

如何为Python开发安装IronXL？

你可以通过pip包管理器在Python环境中安装IronXL，使用命令：pip install ironxl。

IronXL是否支持在Python中进行Excel公式计算？

是的，IronXL支持Excel公式计算，让你可以在Python应用程序中无缝地执行和评估公式。

有哪些文档可以帮助在Python中使用IronXL？

IronXL提供全面的文档，包括教程、指南和API参考，以帮助开发人员有效利用其功能进行Excel文件操作。

IronXL 的许可选项有哪些？

IronXL提供试用版本，并且在试用期后有多种许可选项可供选择，起价为lite版本许可。更多细节可以在IronXL许可页面找到。

IronXL可以用于Excel文件中的数据验证吗？

是的，IronXL包含数据验证功能，允许开发人员在Excel文件中实现检查和规则以确保数据完整性。

Curtis Chau
Curtis Chau
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技术作家

Curtis Chau 拥有卡尔顿大学的计算机科学学士学位，专注于前端开发，精通 Node.js、TypeScript、JavaScript 和 React。他热衷于打造直观且美观的用户界面，喜欢使用现代框架并创建结构良好、视觉吸引力强的手册。

除了开发之外，Curtis 对物联网 (IoT) 有浓厚的兴趣，探索将硬件和软件集成的新方法。在空闲时间，他喜欢玩游戏和构建 Discord 机器人，将他对技术的热爱与创造力相结合。

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