How does Python perform in data science compared to other languages?
Python is highly regarded in data science due to its simplicity, extensive libraries, and community support.
What libraries make Python so effective for data science?
Key libraries include Pandas for data manipulation, NumPy for numerical data, and Matplotlib for data visualization.
Are there any performance issues with Python in data science?
While Python is versatile, it can be slower than languages like C++ or Java for certain tasks, but optimizations exist.
What are some best practices to improve Python's performance in data science?
Best practices include using vectorized operations, optimizing data structures, and leveraging libraries like Cython for speed.
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