Category: Numpy

The numpy.size() function in Python returns the number of elements in an array. It can return either the total count of elements in the entire array or, if an axis is specified, the number of elements along that axis. This makes it a simple yet powerful utility for understanding array structure, validating data shapes, and… Continue reading numpy.size() — Count Elements in a NumPy Array (With Examples)

numpy.percentile()function used to compute the nth percentile of the given data (array elements) along the specified axis. Syntax : numpy.percentile(arr, n, axis=None, out=None) Parameters : arr :input array. n : percentile value. axis : axis along which we want to calculate the percentile value. Otherwise, it will consider arr to be flattened(works on all the… Continue reading numpy.percentile() in python

numpy.subtract() function is used when we want to compute the difference of two array.It returns the difference of arr1 and arr2, element-wise. Syntax : numpy.subtract(arr1, arr2, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj], ufunc ‘subtract’) Parameters : arr1 : [array_like or scalar]1st Input array. arr2 : [array_like or scalar]2nd Input array. dtype… Continue reading numpy.subtract() in Python

numpy.argmax() returns the index (or indices) of the maximum element along the specified axis. Syntax – numpy.argmax(a, axis=None, out=None) a : array_like — input array. axis : int or None — axis along which to find the indices of the maximum. None flattens. out : ndarray, optional — alternative output array to store result (must… Continue reading numpy.argmax() in Python