In this chapter, we will be discussing some mathematical operations related to NumPy arrays.
Most of the mathematical operations on NumPy arrays are element-wise operations. For example, the element at a particular index in one 2-D Numpy array gets added/subtracted/multiplied/etc. to the element at the same index in another 2- D NumPy array.
Addition
The addition of two NumPy arrays is also element-wise addition.
e.g.
import numpy as np
a = np.array([ 20, 30, 40, 50])
b = np.arange(4)
Values of b will be
array([ 0, 1, 2, 3])
c = a + b
print(c)
Output will be
array([ 20, 31, 42, 53] )
Subtraction
Subtraction between two NumPy arrays is also element-wise.
e.g.
import numpy as np
d = np.array([ 20, 30, 40, 50])
e = np.arange(4)
Values of d will be
array([ 0, 1, 2, 3])
f = d - e
print(f)
Output will be
array([ 20, 29, 38, 47] )
Please follow the following steps:
(1) Import the required libraries
import numpy as np
Addition (element-wise)
(2) Please create a NumPy array a_arr with values (60, 70, 80, 90)
a_arr = np.array(<< your code comes here>>)
b_arr = np.arange(4)
Now, we have two NumPy arrays - a_arr and b_arr
(3) Add these two NumPy arrays (a_arr and b_arr), and store the result in a variable c_arr
<<your code comes here>> = a_arr + b_arr
(4) Print array c_arr to see its values
print(c_arr)
Subtraction (element-wise)
(1) Please create a NumPy array d_arr with values (60, 70, 80, 90)
d_arr = np.array(<< your code comes here>>)
e_arr = np.arange(4)
Now, we have two NumPy arrays - d_arr and e_arr
(2) Subtract NumPy array e_arr from array d_arr, and store the result in a variable called f_arr
<<your code comes here>> = d_arr - e_arr
(3) Print array f_arr to see its values
print(f_arr)
Note - Having trouble with the assessment engine? Follow the steps listed here
Loading comments...