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# scipy.stats.mode

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

  Returns 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]))