Merge pull request #52 from VirtusLab/fix_from_dict

Add tests and modify from_dict DataFrame method

Author: joannasendorek

setup.py

@@ -21,7 +21,7 @@ def list_packages(source_path: str = src_path) -> None:
 setup(
     name="pandas-stubs",
     package_dir={"": src_path},
-    version="1.1.0.9",
+    version="1.1.0.10",
     description="Type annotations for Pandas",
     long_description=(open("README.md").read()
                       if os.path.exists("README.md") else ""),

tests/snippets/test_frame.py

@@ -501,3 +501,12 @@ def test_types_resample() -> None:
     df.resample('M', on='date')
     # origin and offset params added in 1.1.0 https://pandas.pydata.org/docs/whatsnew/v1.1.0.html
     df.resample('20min', origin='epoch', offset=pd.Timedelta(2, 'minutes'), on='date')
+
+
+def test_types_from_dict() -> None:
+    pd.DataFrame.from_dict({'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']})
+    pd.DataFrame.from_dict({1: [3, 2, 1, 0], 2: ['a', 'b', 'c', 'd']})
+    pd.DataFrame.from_dict({'a': {1: 2}, 'b': {3: 4, 1: 4}}, orient="index")
+    pd.DataFrame.from_dict({'a': {'row1': 2}, 'b': {'row2': 4, 'row1': 4}})
+    pd.DataFrame.from_dict({'a': (1, 2, 3), 'b': (2, 4, 5)})
+    pd.DataFrame.from_dict(data={'col_1': {'a': 1}, 'col_2': {'a': 1, 'b': 2}}, orient="columns")

third_party/3/pandas/core/frame.pyi

@@ -92,7 +92,7 @@ class DataFrame(NDFrame):
     def itertuples(self, index: bool = ..., name: str = ...) -> Iterable[Tuple[Any, ...]]: ...
     def dot(self, other: Union[FrameOrSeries, ArrayLike]) -> FrameOrSeries: ...
     @classmethod
-    def from_dict(cls: Any, data: Dict[str, Union[AnyArrayLike, Series, Dict[Column, Dtype]]], orient: Orientation = ..., dtype: Optional[Dtype] = ..., columns: Optional[Sequence[str]] = ...) -> DataFrame: ...
+    def from_dict(cls: Any, data: Dict[Union[Label, Column], Union[Union[AnyArrayLike, Iterable[Any]], Dict[Union[Label, Column], Any]]], orient: Orientation = ..., dtype: Optional[Dtype] = ..., columns: Optional[Sequence[str]] = ...) -> DataFrame: ...
     def to_numpy(self, dtype: Union[str, np.dtype] = ..., copy: bool = ..., na_value: Optional[Any] = ...) -> np.ndarray: ...
     def to_dict(self, orient: ExportOrientation = ..., into: Type[Mapping[Column, Any]] = ...) -> Union[Mapping[Column, Any], List[Any]]: ...
     def to_gbq(self, destination_table: str, project_id: Optional[str] = ..., chunksize: Optional[int] = ..., reauth: bool = ..., if_exists: IfExistStrategy = ..., auth_local_webserver: bool = ..., table_schema: Optional[List[Dict[str, Any]]] = ..., location: Optional[str] = ..., progress_bar: bool = ..., credentials: Optional[GoogleCredentials] = ...) -> None: ...