Why do we need NumPy ?
A question arises that why do we need NumPy when python lists are already there. The answer to it is we cannot perform operations on all the elements of two list directly. For example, we cannot multiply two lists directly we will have to do it element-wise. This is where the role of NumPy comes into play.
Example #1:
# Python program to demonstrate a need of NumPy
list1 = [1, 2, 3, 4 ,5, 6]
list2 = [10, 9, 8, 7, 6, 5]
# Multiplying both lists directly would give an error.
print(list1*list2)
Output :
TypeError: can't multiply sequence by non-int of type 'list'
Where as this can easily be done with NumPy arrays.
Example #2:
# Python program to demonstrate the use of NumPy arrays
import numpy as np
list1 = [1, 2, 3, 4, 5, 6]
list2 = [10, 9, 8, 7, 6, 5]
# Convert list1 into a NumPy array
a1 = np.array(list1)
# Convert list2 into a NumPy array
a2 = np.array(list2)
print(a1*a2)
Output :
array([10, 18, 24, 28, 30, 30])
Numpy package of python has a great power of indexing in different ways.
Numpy Array Indexing
NumPy or Numeric Python is a package for computation on homogenous n-dimensional arrays. In numpy dimensions are called as axes.
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