Abstract
This research provides a comprehensive comparison & analysis between Java and Python, focusing on their application in data science. Key aspects such as encapsulation, AI capabilities, software complexity metrics (Halstead), data statistics, and algorithmic performance (Bubble Sort) are analyzed. This study aims to guide developers in choosing the appropriate language for their data science projects by evaluating performance, memory management, multithreading, and ecosystem richness. The findings are supported by empirical data, benchmarks, and detailed analysis, emphasizing when and how each language excels.
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