# scipy.sparse.coo_array.nanmin

coo_array.nanmin(axis=None, out=None)

  Return the minimum of the matrix or minimum along an axis, ignoring any NaNs. This takes all elements into account, not just the non-zero ones.

  New in version 1.11.0.

  Parameters:
    axis{-2, -1, 0, 1, None} optional

      Axis along which the minimum is computed. The default is to compute the minimum over all the matrix elements, returning a scalar (i.e., axis = None).

    out None, optional

      This argument is in the signature solely for NumPy compatibility reasons. Do not pass in anything except for the default value, as this argument is not used.

  Returns:
    amin coo_matrix or scalar

      Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is a sparse.coo_matrix of dimension `a.ndim - 1`.

  See also

  `nanmax`

    The maximum value of a sparse matrix along a given axis, ignoring NaNs.

  `min`

    The minimum value of a sparse matrix along a given axis, propagating NaNs.

  `numpy.nanmin`

    NumPy’s implementation of ‘nanmin’.