min

min(a, axis=None, out=None, keepdims=False)

Return the minimum of an array or minimum along an axis.

Parameters:

a : ndarray

Input data.

axis : int, optional

Axis along which to operate. By default, flattened input is used.

out : ndarray, optional

Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. See doc.ufuncs (Section “Output arguments”) for more details.

keepdims : bool, 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 original arr.

Returns:

min : ndarray

Minimum of a. If axis is None, the result is an array of dimension 1. If axis is given, the result is an array of dimension a.ndim - 1.

See also

max

The maximum value of an array along a given axis, ignoring any nan.

minimum

Element-wise minimum of two arrays, ignoring any nan.

Notes

NaN in the orginal numpy is denoted as nan and will be ignored.

Don’t use min for element-wise comparison of 2 arrays; when a.shape[0] is 2, minimum(a[0], a[1]) is faster than min(a, axis=0).

Examples

>>> a = np.arange(4).reshape((2,2))
>>> a
array([[0., 1.],
    [2., 3.]])
>>> np.min(a)           # Minimum of the flattened array
array(0.)
>>> np.min(a, axis=0)   # Minima along the first axis
array([0., 1.])
>>> np.min(a, axis=1)   # Minima along the second axis
array([0., 2.])
>>> b = np.arange(5, dtype=np.float32)
>>> b[2] = np.nan
>>> np.min(b)
array(0.) # nan will be ignored