First, import numpy as np

- np.sqrt() returns non-negative square root of element
- np.square() returns square of the element
- np.absolute() calculates absolute value of the element
- np.maximum() returns max of all array elements
- np.minimum() returns minimum of all array elements


University of Michigan - Ann Arbor

Within the NumPy library, there are several types of mathematical functions built-in. These functions are typically used across elements of a NumPy array.

Types of Mathematical Functions:
- Trigonometric
- Rounding
- Exponents and Logarithms
- Arithmetic
- Other Special Functions

Mathematical Functions in NumPy

https://www.geeksforgeeks.org/numpy-mathematical-function/

Geeks for Geeks NumPy Mathematical Functions

First,
import numpy as np

- np.tan() calculates tangent of element
- np.arcsin() calculates inverse sine of element
- np.arccos() calculates inverse cosine of element
- np.arctan() calculates inverse tangent of element
- np.degrees() converts element from radians to degrees
- np.radians() converts element from degrees to radians

NumPy Trigonometric Functions

First, import numpy as np

- np.rint() rounds element to nearest integer towards zero
- np.floor() returns element rounded down to nearest integer (1.7 returns 1)
- np.ceil() returns element rounded up to nearest integer (1.1 returns 2)
- np.trunc() returns element without decimals (0.5 returns 0., 1.335 returns 1.)


NumPy Rounding Functions

First, import numpy as np

- np.exp() returns e to the power of the element 
- np.expm1() returns e to the power of the element minus 1
- np.exp2() calculates 2 to the power of the element
- np.log10() returns logarithm base 10 of the element
- np.log2() returns the logarithm base 2 of the element
- np.log1p() return the natural logarithm of one plus the element 

NumPy Exponential and Logarithmic Functions

First, import numpy as np

- np.add() adds elements from two arrays
- np.multiply() multiples elements from two arrays
- np.power() elements from first array are to powers from second array
- np.subtract() subtracts elements from two arrays
- np.true_divide() uses true division to divide elements from two arrays
- np.floor_divide() divides elements from two arrays and returns the floor value of the quotient (1 / 3 returns 0)
- np.mod() returns the remainder of the division between two arrays


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