What are the differences between NumPy and SciPy?

What are the differences between NumPy and SciPy?

NumPy is primarily used for numerical computations and array manipulations, while SciPy builds on NumPy and provides additional functionality for scientific computing, such as optimization, integration, and statistics.

Can you give me an example of when to use SciPy instead of NumPy?

Sure! If you need to perform optimization tasks, like finding the minimum of a function, you would use SciPy's optimize module, which is not available in NumPy.

Are there any performance differences between the two?

Generally, NumPy is faster for basic array operations since it's optimized for those tasks. SciPy may be slower for some operations due to its additional features, but it provides more advanced algorithms.

Is it common to use both libraries together?

Yes, it's very common! Many projects use NumPy for array handling and SciPy for more complex scientific computations.