NumPy
NumPy is a Python library used for working with arrays.
NumPy stands for Numerical Python. In Python we have lists that serve the purpose of arrays, but they are slow to process.
NumPy aims to provide an array object that is up to 50x faster than traditional Python lists.
The array object in NumPy is called ndarray, it provides a lot of supporting functions that make working with ndarray very easy.
NumPy Faster Than Lists
NumPy arrays are stored at one continuous place in memory unlike lists, so processes can access
and manipulate them very efficiently.
This behavior is called locality of reference in computer science.
This is the main reason why NumPy is faster than lists. Also it is optimized to work with latest
CPU architectures.
Import NumPy
Once NumPy is installed, import it in your applications by adding the import keyword:
import numpy
Now NumPy is imported and ready to use.
Example
import numpy
arr = numpy.array([1, 2, 3, 4, 5])
print(arr)
import numpy as np
Now the NumPy package can be referred to as np instead of numpy.
Example
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print(arr)
