The need for NumPy arises when we are working with multi-dimensional arrays. The traditional array module does not support multi-dimensional arrays.
Let’s first try to create a single-dimensional array (i.e one row & multiple columns) in Python without installing NumPy Package to get a more clear picture.
Python3
from array import * arr = array('i', [25, 16, 3]) print(arr) |
Output:
array('i', [25, 16, 3])
Now, Let’s try to create a multi-dimensional array by using the array module.
Python3
from array import * arr = array('i', [25, 16, 3], [5, 19, 28]) print(arr) |
Output:
TypeError: array() takes at most 2 arguments (3 given)
We see that the array module does not support multi-dimensional array, this is where we require NumPy. NumPy supports large, multi-dimensional arrays and has a large collection of high-level math functions that can operate on those arrays.
Let’s use NumPy to create a multi-dimensional array.
Python3
from numpy import * arr = array ([[25, 31, 3], [5, 19, 28]]) print(arr) |
Output:
[[25 31 3] [ 5 19 28]]
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