Get the context data as a pandas DataFrame. Args: selector: dict The key is column name in dataframe, and the value describes how to select values of context. See more details in derived context DAG node class. vertex_range: dict, opti
(self, selector, vertex_range=None)
| 159 | return ResultDAGNode(self, op) |
| 160 | |
| 161 | def to_dataframe(self, selector, vertex_range=None): |
| 162 | """Get the context data as a pandas DataFrame. |
| 163 | |
| 164 | Args: |
| 165 | selector: dict |
| 166 | The key is column name in dataframe, and the value describes how to select |
| 167 | values of context. See more details in derived context DAG node class. |
| 168 | vertex_range: dict, optional, default to None. |
| 169 | Works as slicing. The expression {'begin': m, 'end': n} select a portion |
| 170 | of vertices from `m` to, but not including `n`. Type of `m`, `n` must be |
| 171 | identical with vertices' oid type. |
| 172 | Only the sub-ranges of vertices data will be retrieved. |
| 173 | Note the comparison is not based on numeric order, but on alphabetic order. |
| 174 | |
| 175 | Returns: |
| 176 | :class:`graphscope.framework.context.ResultDAGNode`: |
| 177 | A result holds the `pandas.DataFrame`, evaluated in eager mode. |
| 178 | """ |
| 179 | check_argument( |
| 180 | isinstance(selector, Mapping), "selector of to_dataframe must be a dict" |
| 181 | ) |
| 182 | for _, value in selector.items(): |
| 183 | self._check_selector(value) |
| 184 | _ensure_consistent_label(self.context_type, selector) |
| 185 | selector = json.dumps(selector) |
| 186 | vertex_range = utils.transform_vertex_range(vertex_range) |
| 187 | op = dag_utils.context_to_dataframe(self, selector, vertex_range) |
| 188 | return ResultDAGNode(self, op) |
| 189 | |
| 190 | def to_vineyard_tensor(self, selector=None, vertex_range=None, axis=0): |
| 191 | """Get the context data as a vineyard tensor and return the vineyard object id. |
nothing calls this directly
no test coverage detected