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This article explores multiple methods for executing Python scripts within HTML web pages, focusing on CGI (Common Gateway Interface) as a traditional server-side solution and Pyodide as a modern browser-based technology. By comparing the applicability, learning curves, and implementation complexities of different approaches, it provides comprehensive guidance from basic configuration to advanced integration, helping developers choose the right technical solution based on project requirements.

This article explores various alternatives to Python Pandas in the JavaScript ecosystem. By analyzing key libraries such as d3.js, danfo-js, pandas-js, dataframe-js, data-forge, jsdataframe, SQL Frames, and Jandas, along with emerging technologies like Pyodide, Apache Arrow, and Polars, it provides a comprehensive evaluation based on language compatibility, feature completeness, performance, and maintenance status. The discussion also covers selection criteria, including similarity to the Pandas API, data science integration, and visualization support, to help developers choose the most suitable tool for their needs.