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# numpy.nanargmin

`numpy.``nanargmin`(a, axis=None)

  Return the indices of the minimum values in the specified axis ignoring NaNs. For all-NaN slices `ValueError` is raised. Warning: the results cannot be trusted if a slice contains only NaNs and Infs.

  Parameters: | a : array_like Input data. axis : int, optional Axis along which to operate. By default flattened input is used.
  Returns: | index_array : ndarray An array of indices or a single index value.

  See also

  `argmin`, `nanargmax`

  Examples

      >>> a = np.array([[np.nan, 4], [2, 3]])
      >>> np.argmin(a)
      0
      >>> np.nanargmin(a)
      2
      >>> np.nanargmin(a, axis=0)
      array([1, 1])
      >>> np.nanargmin(a, axis=1)
      array([1, 0])