Page 228 - AI Ver 1.0 Class 10
P. 228
* import numpy as np [35 48 20 28]
(Multiplication) marks1 = np.array([7,8,5,4]) 2 marks multiplied : [14 16 10 8]
marks2=np.array([5,6,4,7])
print(marks1*marks2)
print(“2 marks multiplied:”,marks1*2)
/ import numpy as np [ 5. 5. 10. 8.]
(Divide) marks1 = np.array([10,20,30,40]) 2 marks divided : [ 5. 10. 15. 20.]
marks2=np.array([2,4,3,5])
print(marks1/marks2)
print(“2 marks divided:”,marks1/2)
// import numpy as np [ 5 5 10 8]
(Floor division) marks1 = np.array([10,20,30,40]) 2 marks divided using floor
division : [ 5 10 15 20]
marks2=np.array([2,4,3,5])
print(marks1//marks2)
print(“2 marks divided using floor
division:”,marks1//2)
% import numpy as np [0 0 0 0]
(Remainder of marks1 = np.array([10,20,30,40]) remainder of division: [1 2 0 1]
division) marks2=np.array([1,2,3,4])
print(marks1%marks2)
print(“remainder of
division:”,marks1%3)
Some Important Functions
Type Function Example Output
Type of an object type(ARR) import numpy as np <class ‘numpy.
i.e. array ARR = np.array([1,2,3,4]) ndarray’>
print(type(ARR))
Check the ARR.ndim import numpy as np 2
dimensions of ARR =
an array
np.array([[1,2,3,4],[3,4,5,6]])
print(ARR.ndim)
Shape of an array ARR.shape import numpy as np (2, 4)
i.e. length of the ARR =
array dimensions
np.array([[1,2,3,4],[3,4,5,6]])
print(ARR.shape)
226 Touchpad Artificial Intelligence-X

