Universal functions in Numpy are simple mathematical functions. It is just a term that we gave to mathematical functions in the Numpy library. Numpy provides various universal functions that cover a wide variety of operations.
These functions include standard trigonometric functions, functions for arithmetic operations, handling complex numbers, statistical functions, etc. Universal functions have various characteristics which are as follows-
- These functions operates on ndarray (N-dimensional array) i.e Numpy’s array class.
- It performs fast element-wise array operations.
- It supports various features like array broadcasting, type casting etc.
- Numpy, universal functions are objects those belongs to numpy.ufunc class.
- Python functions can also be created as a universal function using frompyfunc library function.
- Some ufuncs are called automatically when the corresponding arithmetic operator is used on arrays. For example when addition of two array is performed element-wise using ‘+’ operator then np.add() is called internally.
Some of the basic universal functions in Numpy are-
These functions work on radians, so angles need to be converted to radians by multiplying by pi/180. Only then we can call trigonometric functions. They take an array as input arguments. It includes functions like-
|sin, cos, tan||compute sine, cosine and tangent of angles|
|arcsin, arccos, arctan||calculate inverse sine, cosine and tangent|
|hypot||calculate hypotenuse of given right triangle|
|sinh, cosh, tanh||compute hyperbolic sine, cosine and tangent|
|arcsinh, arccosh, arctanh||compute inverse hyperbolic sine, cosine and tangent|
|deg2rad||convert degree into radians|
|rad2deg||convert radians into degree|
Sine of angles in the array: [ 0.00000000e+00 5.00000000e-01 7.07106781e-01 8.66025404e-01 1.00000000e+00 1.22464680e-16] Inverse Sine of sine values: [ 0.00000000e+00 3.00000000e+01 4.50000000e+01 6.00000000e+01 9.00000000e+01 7.01670930e-15] Sine hyperbolic of angles in the array: [ 0. 0.54785347 0.86867096 1.24936705 2.3012989 11.54873936] Inverse Sine hyperbolic: [ 0. 0.52085606 0.76347126 0.94878485 0.74483916 -0.85086591] hypotenuse of right triangle is: 5.0
These functions are used to calculate mean, median, variance, minimum of array elements. It includes functions like-
|amin, amax||returns minimum or maximum of an array or along an axis|
|ptp||returns range of values (maximum-minimum) of an array or along an axis|
|percentile(a, p, axis)||calculate pth percentile of array or along specified axis|
|median||compute median of data along specified axis|
|mean||compute mean of data along specified axis|
|std||compute standard deviation of data along specified axis|
|var||compute variance of data along specified axis|
|average||compute average of data along specified axis|
Minimum and maximum weight of the students: 45.0 73.25 Range of the weight of the students: 28.25 Weight below which 70 % student fall: 55.317 Mean weight of the students: 54.3225 Median weight of the students: 51.6 Standard deviation of weight of the students: 8.05277397857 Variance of weight of the students: 64.84716875 Average weight of the students: 54.3225
These functions accept integer values as input arguments and perform bitwise operations on binary representations of those integers. It include functions like-
|bitwise_and||performs bitwise and operation on two array elements|
|bitwies_or||performs bitwise or operation on two array elements|
|bitwise_xor||performs bitwise xor operation on two array elements|
|invert||performs bitwise inversion of an array elements|
|left_shift||shift the bits of elements to left|
|right_shift||shift the bits of elements to left|
bitwise_and of two arrays: [ 0 2 4 6 8 16 32] bitwise_or of two arrays: [ 1 3 5 7 9 17 33] bitwise_xor of two arrays: [1 1 1 1 1 1 1] inversion of even no. array: [ -1 -3 -5 -7 -9 -17 -33] left_shift of even no. array: [ 0 4 8 12 16 32 64] right_shift of even no. array: [ 0 1 2 3 4 8 16]
- Create your own universal function in NumPy
- Create Pandas Series using NumPy functions
- Mathematical Functions in Python | Set 2 (Logarithmic and Power Functions)
- Mathematical Functions in Python | Set 3 (Trigonometric and Angular Functions)
- Mathematical Functions in Python | Set 4 (Special Functions and Constants)
- Mathematical Functions in Python | Set 1 (Numeric Functions)
- Python | Numpy numpy.ndarray.__iadd__()
- Python | Numpy numpy.ndarray.__imul__()
- Python | Numpy numpy.ndarray.__and__()
- Python | Numpy numpy.ndarray.__isub__()
- Python | Numpy numpy.ndarray.__mod__()
- Python | Numpy numpy.ndarray.__lshift__()
- Python | Numpy numpy.ndarray.__xor__()
- Python | Numpy numpy.ndarray.__rshift__()
- Python | Numpy numpy.ndarray.__pow__()
- Python | Numpy numpy.ndarray.__divmod__()
- Python | Numpy numpy.ndarray.__invert__()
- Python | Numpy numpy.ndarray.__or__()
- Python | Numpy numpy.ndarray.__eq__()
- Python | Numpy numpy.ndarray.__ne__()
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