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Tag Archives: Python-numpy

The numpy.all() function tests whether all array elements along the mentioned axis evaluate to True. Syntax: numpy.all(array, axis = None, out = None, keepdims =… Read More
The numpy.isinf() function tests element-wise whether it is +ve or -ve infinity or not return the result as a boolean array.  Syntax: numpy.isinf(array [, out])… Read More
The numpy.flipud() function flips the array(entries in each column) in up-down direction, shape preserved. Syntax:  numpy.flipud(array) Parameters :  array : [array_like]Input array, we want to… Read More
The numpy.any() function tests whether any array elements along the mentioned axis evaluate to True. Syntax :  numpy.any(a, axis = None, out = None, keepdims… Read More
The numpy.random.rand() function creates an array of specified shape and fills it with random values. Syntax :  numpy.random.rand(d0, d1, ..., dn) Parameters :  d0, d1,… Read More
The numpy.nanargmin() function returns indices of the min element of the array in a particular axis ignoring NaNs. The results cannot be trusted if a slice… Read More
The numpy.isfinite() function tests element-wise whether it is finite or not(not infinity or not Not a Number) and return the result as a boolean array.… Read More
The numpy.isneginf() function tests element-wise whether it is negative infinity or not, and returns the result as a boolean array. Syntax :   numpy.isneginf(array, y = None)… Read More
The numpy.iscomplex() function tests element-wise whether it is a complex number or not(not infinity or not Not a Number) and returns the result as a… Read More
The numpy.isnan() function tests element-wise whether it is NaN or not and returns the result as a boolean array. Syntax :  numpy.isnan(array [, out]) Parameters… Read More
The numpy.isposinf() function tests element-wise whether it is positive infinity or not and returns the result as a boolean array.  Syntax :  numpy.isposinf(array, y =… Read More
The numpy.nanargmax() function returns indices of the max element of the array in a particular axis ignoring NaNs. The results cannot be trusted if a slice… Read More
The numpy.less() : checks whether x1 is lesser than x2 or not. Syntax :  numpy.less(x1, x2[, out]) Parameters :  x1, x2 : [array_like]Input arrays. If… Read More
The numpy.greater() checks whether x1 is greater than x2 or not. Syntax :  numpy.greater(x1, x2[, out]) Parameters :  x1, x2 : [array_like]Input arrays. If x1.shape… Read More
The numpy.not_equal() checks whether two element or unequal or not. Syntax :  numpy.not_equal(x1, x2[, out]) Parameters :  x1, x2 : [array_like]Input Array whose elements we… Read More

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