Parameters —
 arr: [array_like] input data
 axis : axis [int or tuples of int] along which we want to get the minimum value. Otherwise, it will assume that arr will be flattened.
 out: [ndarray, optional] An alternate output array to put the result into
 keepdmis: [boolean, optional] If this parameter is set to True, the downsized axes remain in
the result as dimensions with size one. With this option, the result will translate correctly
the input array. If a default is passed, then keepdims will not be passed to all
ndarray subclasses, however any nondefault will be. If the subclass sum method
does not implement keepdims, exceptions will be thrown.
Return —
Minimum array — arr [ndarray or scalar], scalar if axis is None;
The result is an array of dimensions a.ndim — 1 if axis is specified.
Code —

Exit —
arr: [0 1 2 3 4 5 6 7] Min of arr: 0 arr: [[0 1 2 3 4] [5 6 7 8 9]] Min of arr, axis = None: 0 Min of arr, axis = 0: [0 1 2 3 4] Min of arr, axis = 1: [0 5]
Links —
https://docs.scipy.org/doc/numpy1.13.0/reference/generated/numpy.amin.html#numpy.amin
Note —
These codes will not work for online IDs. Please run them on your systems to see how they work
This article is provided by Mohit Gupta_OMG