NumPy Mathematics

NumPy provides a variety of mathematical functions that operate on arrays. These functions can be broadly categorized into the following types:

Basic Mathematical Functions:

• np.add(arr1, arr2) performs element-wise addition between arrays arr1 and arr2.
• np.subtract(arr1, arr2) performs element-wise subtraction between arrays arr1 and arr2.

import numpy as np
 
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
 
np.add(arr1, arr2)        # [5 7 9]
np.subtract(arr1, arr2)   # [-3 -3 -3]
np.add(arr1, 10)          # [11, 12, 13]
np.subtract(arr2, 4)      # [0, 1, 2]

• np.multiply(arr1, arr2) performs element-wise multiplication between arrays arr1 and arr2.
• np.divide(arr1, arr2) performs element-wise division between arrays arr1 and arr2.

arr1 = np.array([10, 20, 30])
arr2 = np.array([2, 4, 6])
 
np.multiply(arr1, arr2)  # [20 80 180]
np.divide(arr1, arr2)    # [ 5.  5.  5.]
np.multiply(arr1, 10).   # [100, 200, 300]
np.divide(arr2, 2).      # [1., 2., 3.]

• np.power(arr, power) raises elements of array arr to the power of power.

arr = np.array([2, 3, 4])
 
np.power(arr, 2)  # [ 4  9 16]

• np.sqrt(arr) computes the square root of each element in array arr.

arr = np.array([16, 25, 36])
 
np.sqrt(arr)  # [4. 5. 6.]

Trigonometric Functions:

• np.sin(arr) computes the sine of each element in array arr.
• np.cos(arr) computes the cosine of each element in array arr.
• np.tan(arr) computes the tangent of each element in array arr.

arr = np.array([0, np.pi/4, np.pi/2])
 
np.sin(arr)  # [0. 0.70710678 1.]
np.cos(arr)  # [1. 0.70710678 0.]
np.tan(arr)  # [0. 1. 1.63312394]

Logarithmic and Exponential Functions:

• np.log(arr) calculates the natural logarithm of each element in array arr.
• np.log10(arr) calculates the base-10 logarithm of each element in array arr.

arr = np.array([1, 10, 100])
 
np.log(arr)    # [0. 2.30258509 4.60517019]
np.log10(arr)  # [0. 1. 2.]

• np.exp(arr) calculates the exponential of each element in array arr.

arr = np.array([1, 2, 3])
 
np.exp(arr)  # [ 2.71828183  7.3890561  20.08553692]

Aggregate Functions:

• np.sum(arr) calculates the sum of all elements in array arr.
• np.min(arr) finds the minimum value among the elements in array arr.
• np.max(arr) finds the maximum value among the elements in array arr.
• np.mean(arr) computes the mean (average) value of elements in array arr.
• np.median(arr) calculates the median value of elements in array arr.
• np.std(arr) calculates the standard deviation of elements in array arr.

arr = np.array([10, 20, 30, 40, 50])
 
total_sum = np.sum(arr)      # 150
minimum_value = np.min(arr)  # 10
maximum_value = np.max(arr)  # 50
average_mean = np.mean(arr)  # 30.0
middle_median = np.median(arr)  # 30.0
standard_deviation = np.std(arr)  # 14.14 (approximately)