This is an continuation of the series Data spell (that covers the topics of AI in the most practical and easy to understand terms)
Numpy - Numerical python is used for working with arrays. It becomes very useful while working with large high dimensional arrays for mathematical or logical operations .
How to use in your code ?
You can add NumPy into your python code by just importing it like any other package.
import numpy as np
there is no strict rule that you must use the alias as np , but its a convention around that developers use this , so i highly insist you to follow the same.
Create an array
arr = np.array([1,2,3])
# can also specify the datatype you want by :
# arr = np.array([1,2,3],dtype = float)
Initialise arrays
Create array of zeros
zeros = np.zeros(5) # creates an 1 D array with 5 elements # you can specify the shape which you want
Create arrays of ones
ones = np.ones(10)Create Identity matrix
matrix = np.eye(2) # creates 2 x 2 identity matrix
Create a range array
num = np.range(1,10)
Common operations
assume arr is an array.
| Name of operation | operation | syntax |
| Transpose | interchanging the rows and columns of the original matrix | arr.transpose() or arr.T |
| Mean | Average value of array | arr.mean() |
| Sum | sum of array | arr.sum() |
| Sort | return the given array in sorted order | arr.sort() |
Conclusion
This was a brief introduction to NumPy, and there's much more to explore. For further details, you can read the official documentation here.