numpy.amax(arr, axis = None, out = None, keepdims = <class numpy._globals._NoValue>) returns maximum of an array or maximum along axis(if mentioned).
- arr : [array_like] input data
- axis : [int or tuples of int] axis along which we want the max value. Otherwise, it will consider arr to be flattened.
- out : [ndarray, optional] alternative output array in which to place the result
- keepdmis : [boolean, optional] if this is set to True, the axes which are reduced are left in
the result as dimensions with size one. With this option, the result will broadcast correctly against
the input array. If the default value is passed, then keepdims will not be passed through to the all
method of sub-classes of ndarray, however any non-default value will be. If the sub-classes sum method
does not implement keepdims any exceptions will be raised.
Return – Maximum of array – arr[ndarray or scalar], scalar if axis is None; the result is an array of dimension a.ndim – 1, if axis is mentioned.
arr : [0 1 2 3 4 5 6 7] Max of arr : 7 arr : [[0 1 2 3 4] [5 6 7 8 9]] Max of arr, axis = None : 9 Max of arr, axis = 0 : [5 6 7 8 9] Max of arr, axis = 1 : [4 9]
These codes won’t run on online-ID. Please run them on your systems to explore the working
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