NumPy is a Python Numeric Library

2. NumPy
NumPy is a Python package. It stands for 'Numerical
Python'. It is a library consisting of multidimensional
array objects and a collection of routines for
processing of array.

3. NumPy
Developed By- Jim Hugunin
Since- 2005

4. Why NumPy
 NumPy uses much less memory to store data.
 The NumPy arrays takes significantly less amount of memory as
compared to python lists.
 It also provides a mechanism of specifying the data types of the
contents, which allows further optimisation of the code

5. How to install NumPy in windows
py -m pip install numpy
 Open Command Prompt in windows
 Than set user account
 And run follow command ( When computer is connected to
internet )

6. How to use NumPy
import numpy as np

7. Shapes of Arrays in NumPy
 1 Dimension Array
 2 Dimension Array
 3 Dimension Array

8. 1 Dimension Array
import numpy as np
A=np.array( [30,67,89] )
print(A)
Output:
[30,67,89]

9. 2 Dimension Array
import numpy as np
A=np.array([
(30,67,89),
(30,67,89),
(30,67,89),
])
print(A)
Output: [(30 67 89)
(30 67 89)
(30 67 89)]

10. 3 Dimension Array
import numpy as np
A=np.array([
[[1, 2,3],
[4, 5, 6]],
[[7, 8,9],
[10, 11, 12]]
])
print(A)
Output:
[
[[1, 2,3],
[4, 5, 6]],
[[7, 8,9],
[10, 11, 12]]
]

11. Array attributes in NumPy
import numpy as np
A=np.array( [30,67,89] )
print(A.ndim)
Output:
1
ndim-: This array attribute returns the number of array dimensions.

12. Array attributes in NumPy
import numpy as np
A=np.array( [
[30,67,89],
[38,27,89]
])
print(A.size)
Output:
6
size-: This array attribute returns the total number of elements of array

13. Array attributes in NumPy
import numpy as np
A=np.array( [
[30,67,89],
[38,27,89]
])
print(A.shape)
Output:
(2,3)
shape-: This array attribute returns a tuple consisting of array dimensions. It can
also be used to resize the array.

14. Array attributes in NumPy
import numpy as np
A=np.array( [
[30,67,89], [38,27,89], ])
A.shape = (3,2)
print(A)
Output:
[
[30,7],
[89,38],
[27,89]
]
Change array shape