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

aarray_like

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

axisint 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. The following options are available (default is ‘propagate’):

• ‘propagate’: returns nan

• ‘raise’: throws an error

• ‘omit’: performs the calculations ignoring nan values

Returns

modendarray

Array of modal values.

countndarray

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)
ModeResult(mode=array([[3, 1, 0, 0]]), count=array([[1, 1, 1, 1]]))

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

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