Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers  

作　　者：Osama Magdy Ali Mohamed Breik Tarek Aly Atef Tayh Nour El-Din Raslan Mervat Gheith Osama Magdy Ali;Mohamed Breik;Tarek Aly;Atef Tayh Nour El-Din Raslan;Mervat Gheith(Software Engineering Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt)

机构地区：[1]Software Engineering Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt

出　　处：《Journal of Software Engineering and Applications》2024年第6期530-540,共11页软件工程与应用（英文）

摘　　要：Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.

关 键 词：PYTHON End-User Approach Microsoft Excel Data Analysis Integration SPREADSHEET PROGRAMMING Data Visualization 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]