def fillna(self, value=None, method=None, limit=None):
        """
        Fill missing values with `value`.

        Parameters
        ----------
        value : scalar, optional
        method : str, optional

            .. warning::

               Using 'method' will result in high memory use,
               as all `fill_value` methods will be converted to
               an in-memory ndarray

        limit : int, optional

        Returns
        -------
        SparseArray

        Notes
        -----
        When `value` is specified, the result's ``fill_value`` depends on
        ``self.fill_value``. The goal is to maintain low-memory use.

        If ``self.fill_value`` is NA, the result dtype will be
        ``SparseDtype(self.dtype, fill_value=value)``. This will preserve
        amount of memory used before and after filling.

        When ``self.fill_value`` is not NA, the result dtype will be
        ``self.dtype``. Again, this preserves the amount of memory used.
        """
        if ((method is None and value is None) or
                (method is not None and value is not None)):
            raise ValueError("Must specify one of 'method' or 'value'.")

        elif method is not None:
            msg = "fillna with 'method' requires high memory usage."
            warnings.warn(msg, PerformanceWarning)
            filled = interpolate_2d(np.asarray(self), method=method,
                                    limit=limit)
            return type(self)(filled, fill_value=self.fill_value)

        else:
            new_values = np.where(isna(self.sp_values), value, self.sp_values)

            if self._null_fill_value:
                # This is essentially just updating the dtype.
                new_dtype = SparseDtype(self.dtype.subtype, fill_value=value)
            else:
                new_dtype = self.dtype

        return self._simple_new(new_values, self._sparse_index, new_dtype)
def fillna ( self , value = None , method = None , limit = None ) : if ( ( method is None and value is None ) or ( method is not None and value is not None ) ) : raise ValueError ( "Must specify one of 'method' or 'value'." ) elif method is not None : msg = "fillna with 'method' requires high memory usage." warnings . warn ( msg , PerformanceWarning ) filled = interpolate_2d ( np . asarray ( self ) , method = method , limit = limit ) return type ( self ) ( filled , fill_value = self . fill_value ) else : new_values = np . where ( isna ( self . sp_values ) , value , self . sp_values ) if self . _null_fill_value : new_dtype = SparseDtype ( self . dtype . subtype , fill_value = value ) else : new_dtype = self . dtype return self . _simple_new ( new_values , self . _sparse_index , new_dtype )
Fill missing values with `value`.

        Parameters
        ----------
        value : scalar, optional
        method : str, optional

            .. warning::

               Using 'method' will result in high memory use,
               as all `fill_value` methods will be converted to
               an in-memory ndarray

        limit : int, optional

        Returns
        -------
        SparseArray

        Notes
        -----
        When `value` is specified, the result's ``fill_value`` depends on
        ``self.fill_value``. The goal is to maintain low-memory use.

        If ``self.fill_value`` is NA, the result dtype will be
        ``SparseDtype(self.dtype, fill_value=value)``. This will preserve
        amount of memory used before and after filling.

        When ``self.fill_value`` is not NA, the result dtype will be
        ``self.dtype``. Again, this preserves the amount of memory used.