The np.where() function is one of the most powerful functions available within NumPy. numpy.mean() in Python NumPy where: Process Array Elements Conditionally • datagy However, np.count_nonzero () is faster than np.sum (). You can also delete column using numpy delete column tutorial. To do this, we’ll call np.where (). Ah, hey, don’t forget: np.where() is useful just when you need to return one or two values given a condition. numpy.median(a, 0): la ligne des médiane, c'est à dire aussi ici array([ 2.5, 3.5, 4.5]) (cas particulier). For example row index 1 of the following matrix has just 2 entries so the mean of [4,0,0,1] equals 5/2 not 5/4: It returns a new numpy array, after filtering based on a condition, which is a numpy-like array of boolean values.. For example, condition can take the value of array([[True, True, True]]), which is a numpy-like boolean array. NumPy where tutorial (With Examples) - Like Geeks When True, yield x, otherwise yield y. x, y: array_like, optional. np. Returns the average of the array elements. Numpy Where - TutorialKart NumPy ufuncs - Simple Arithmetic - W3Schools
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