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...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.展开更多
A simple and intuitive manner for solving fluid-structure interaction problem has been developed using Microsoft Excel spreadsheets. By eliminating the need of previous knowledge of any programming language, the metho...A simple and intuitive manner for solving fluid-structure interaction problem has been developed using Microsoft Excel spreadsheets. By eliminating the need of previous knowledge of any programming language, the method appears as an interesting introduction to numerical solutions of partial differential equations, due to the direct and didactic way that it is developed. Proposed procedure enables the analysis of tridimensional geometries using the finite difference method and can be extended to other differential equations or boundary conditions. The author＇s objective in this paper is to develop a simple and reliable preliminary method for solving acoustic fluid-structure interaction problems with application to dam-reservoir interaction phenomena and also contribute in the educational growth for undergraduate students that are beginning research in such matter.展开更多
文摘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.
文摘A simple and intuitive manner for solving fluid-structure interaction problem has been developed using Microsoft Excel spreadsheets. By eliminating the need of previous knowledge of any programming language, the method appears as an interesting introduction to numerical solutions of partial differential equations, due to the direct and didactic way that it is developed. Proposed procedure enables the analysis of tridimensional geometries using the finite difference method and can be extended to other differential equations or boundary conditions. The author＇s objective in this paper is to develop a simple and reliable preliminary method for solving acoustic fluid-structure interaction problems with application to dam-reservoir interaction phenomena and also contribute in the educational growth for undergraduate students that are beginning research in such matter.
