Skip to main content
`Ctrl`+`K`
scipy.sparse.coo_array.

# nanmin

coo_array.nanmin(axis=None, out=None, *, explicit=False)

  Return the minimum, ignoring any Nans, along an axis.

  Return the minimum, ignoring any Nans, of the array/matrix along an axis. By default this takes all elements into account, but with explicit set, only stored elements are considered.

  Added 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 elements, returning a scalar (i.e., axis = None).

    outNone, 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.

    explicit{False, True} optional (default: False)

      When set to True, only the stored elements will be considered. If a row/column is empty, the sparse.coo_array returned has no stored element (i.e. an implicit zero) for that row/column.

      Added in version 1.15.0.

  Returns:
    amincoo_array 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_array of dimension `a.ndim - 1`.

  See also

  `nanmax`

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

  `min`

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

  `numpy.nanmin`

    NumPy’s implementation of ‘nanmin’.