Python | Numpy np.coords() method (original) (raw)

• numpy.cosh() in Python The numpy.cosh() is a mathematical function that helps user to calculate hyperbolic cosine for all x(being the array elements). Equivalent to 1/2 * (np.exp(x) - np.exp(-x)) and np.cos(1j*x). Syntax : numpy.cosh(x[, out]) = ufunc 'cos') Parameters : array : [array_like] elements are in radians. 2pi R 2 min read
• numpy.cos() in Python numpy.cos(x[, out]) = ufunc 'cos') : This mathematical function helps user to calculate trigonometric cosine for all x(being the array elements). Parameters : array : [array_like]elements are in radians. 2pi Radians = 360 degrees Return : An array with trigonometric cosine of x for all x i.e. array 2 min read
• numpy.arccosh() in Python numpy.arccosh() : This mathematical function helps user to calculate inverse hyperbolic cosine, element-wise for all arr. Syntax : numpy.arccosh(arr, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc 'arccosh') Parameters : arr : array_like Input array. out : [ndarray, op 2 min read
• numpy.arccos() in Python numpy.arccos(x[, out]) = ufunc 'arccos') : This mathematical function helps user to calculate inverse cos for all x(being the array elements). Parameters : array : [array_like]elements are in radians. out : [array_like]array of same shape as x. Note : 2pi Radians = 360 degrees The convention is to r 2 min read
• numpy.median() in Python numpy.median(arr, axis = None) : Compute the median of the given data (array elements) along the specified axis. How to calculate median? Given data points. Arrange them in ascending order Median = middle term if total no. of terms are odd. Median = Average of the terms in the middle (if total no. o 2 min read
• Python | numpy.cov() function Covariance provides the measure of strength of correlation between two variable or more set of variables. The covariance matrix element Cij is the covariance of xi and xj. The element Cii is the variance of xi. If COV(xi, xj) = 0 then variables are uncorrelatedIf COV(xi, xj) > 0 then variables po 2 min read
• numpy.argsort() in Python numpy.argsort() is a function in NumPy that returns the indices that would sort an array. In other words, it gives you the indices that you would use to reorder the elements in an array to be in sorted order. Example: [GFGTABS] Python import numpy as geek a = geek.array([2, 0, 1, 5, 4, 1, 9]) print( 3 min read
• numpy.ndarray.ndim() method | Python numpy.ndarray.ndim() function return the number of dimensions of an array. Syntax : numpy.ndarray.ndim(arr) Parameters : arr : [array_like] Input array. If it is not already an ndarray, a conversion is attempted. Return : [int] Return the number of dimensions in arr. Code #1 : # Python program expla 1 min read
• numpy.hypot() in Python This mathematical function helps user to calculate hypotenuse for the right angled triangle, given its side and perpendicular. Result is equivalent to Equivalent to sqrt(x1**2 + x2**2), element-wise. Syntax : numpy.exp2(arr1, arr2[, out]) = ufunc 'hypot') : Parameters : arr1, arr2 : [array_like] Leg 2 min read
• Python | Numpy numpy.ndarray.__mod__() With the help of Numpy numpy.ndarray.__mod__(), every element in an array is operated on binary operator i.e mod(%). Remember we can use any type of values in an array and value for mod is applied as the parameter in ndarray.__mod__(). Syntax: ndarray.__mod__($self, value, /) Return: self%value Exam 1 min read