scipy.stats.mode

scipy.stats.mode(a, axis=0, nan_policy='propagate')

Return an array of the modal (most common) value in the passed array.

If there is more than one such value, only the smallest is returned. The bin-count for the modal bins is also returned.

Parameters:

a : array_like

n-dimensional array of which to find mode(s).

axis : int or None, optional

Axis along which to operate. Default is 0. If None, compute over the whole array a.

nan_policy : {‘propagate’, ‘raise’, ‘omit’}, optional

Defines how to handle when input contains nan. ‘propagate’ returns nan, ‘raise’ throws an error, ‘omit’ performs the calculations ignoring nan values. Default is ‘propagate’.

Returns:

mode : ndarray

Array of modal values.

count : ndarray

Array of counts for each mode.

Examples

>>> a = np.array([[6, 8, 3, 0],
...               [3, 2, 1, 7],
...               [8, 1, 8, 4],
...               [5, 3, 0, 5],
...               [4, 7, 5, 9]])
>>> from scipy import stats
>>> stats.mode(a)
(array([[3, 1, 0, 0]]), array([[1, 1, 1, 1]]))

To get mode of whole array, specify axis=None:

>>> stats.mode(a, axis=None)
(array([3]), array([3]))