How do NumPy arrays perform compared to Python lists?

How do NumPy arrays perform compared to Python lists?

NumPy arrays are generally faster and more efficient than Python lists, especially for large datasets. They use less memory and provide better performance for numerical operations.

What makes NumPy arrays faster?

NumPy arrays are implemented in C and optimized for performance. They allow for vectorized operations, which means operations can be applied to entire arrays without the need for explicit loops.

Can you give an example of a performance comparison?

Sure! For instance, adding two large arrays element-wise is significantly faster with NumPy than with Python lists due to the underlying optimizations.

Are there any downsides to using NumPy arrays?

One downside is that NumPy arrays require all elements to be of the same data type, which can be limiting compared to Python lists that can hold mixed types.