scipy.stats.mode#
- scipy.stats.mode(a, axis=0, nan_policy='propagate')[source]#
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]))