def _unpickle_sparse_frame_compat(self, state): """ original pickle format """ series, cols, idx, fv, kind = state if not isinstance(cols, Index): # pragma: no cover from pandas.io.pickle import _unpickle_array columns = _unpickle_array(cols) else: columns = cols if not isinstance(idx, Index): # pragma: no cover from pandas.io.pickle import _unpickle_array index = _unpickle_array(idx) else: index = idx series_dict = DataFrame() for col, (sp_index, sp_values) in compat.iteritems(series): series_dict[col] = SparseSeries(sp_values, sparse_index=sp_index, fill_value=fv) self._data = to_manager(series_dict, columns, index) self._default_fill_value = fv self._default_kind = kind
def _unpickle_sparse_frame_compat(self, state): """ Original pickle format """ series, cols, idx, fv, kind = state if not isinstance(cols, Index): # pragma: no cover from pandas.io.pickle import _unpickle_array columns = _unpickle_array(cols) else: columns = cols if not isinstance(idx, Index): # pragma: no cover from pandas.io.pickle import _unpickle_array index = _unpickle_array(idx) else: index = idx series_dict = DataFrame() for col, (sp_index, sp_values) in compat.iteritems(series): series_dict[col] = SparseSeries(sp_values, sparse_index=sp_index, fill_value=fv) self._data = to_manager(series_dict, columns, index) self._default_fill_value = fv self._default_kind = kind
def __setstate__(self, state): frames, items, major, minor, fv, kind = state from pandas.io.pickle import _unpickle_array self.default_fill_value = fv self.default_kind = kind self._items = _ensure_index(_unpickle_array(items)) self._major_axis = _ensure_index(_unpickle_array(major)) self._minor_axis = _ensure_index(_unpickle_array(minor)) self._frames = frames