merge master

pandas/_typing.py

@@ -85,10 +85,8 @@
 FrameOrSeries = TypeVar("FrameOrSeries", bound="NDFrame")
 
 Axis = Union[str, int]
-Frequency = Optional[str]
-Label = Optional[Hashable]
-IndexLabel = Union[Label, Sequence[Label]]
-Level = Union[Label, int]
+IndexLabel = Union[Hashable, Sequence[Hashable]]
+Level = Union[Hashable, int]
 Shape = Tuple[int, ...]
 Suffixes = Tuple[str, str]
 Ordered = Optional[bool]

pandas/core/frame.py

@@ -60,7 +60,6 @@
  FloatFormatType,
  FormattersType,
  FrameOrSeriesUnion,
- Frequency,
  IndexKeyFunc,
  IndexLabel,
  Level,
@@ -1328,7 +1327,7 @@ def from_dict(
  data,
  orient: str = "columns",
  dtype: Optional[Dtype] = None,
- columns: Optional[List[Label]] = None,
+ columns: Optional[IndexLabel] = None,
  ) -> DataFrame:
  """
  Construct DataFrame from dict of array-like or dicts.
@@ -1409,9 +1408,9 @@ def from_dict(
 
  def to_numpy(
  self,
- dtype=None,
+ dtype: Optional[NpDtype] = None,
  copy: bool = False,
- na_value: Scalar = lib.no_default,
+ na_value=lib.no_default,
  ) -> np.ndarray:
  """
  Convert the DataFrame to a NumPy array.
@@ -3338,7 +3337,7 @@ def _set_item(self, key, value) -> None:
  self._set_item_mgr(key, value)
 
  def _set_value(
- self, index: Label, col, value: Scalar, takeable: bool = False
+ self, index: IndexLabel, col, value: Scalar, takeable: bool = False
  ) -> None:
  """
  Put single value at passed column and index.
@@ -4019,7 +4018,7 @@ def _sanitize_column(self, value):
  return value
 
  @property
- def _series(self) -> Dict[Label, Series]:
+ def _series(self) -> Dict[IndexLabel, Series]:
  return {
  item: Series(
  self._mgr.iget(idx), index=self.index, name=item, fastpath=True
@@ -4028,7 +4027,7 @@ def _series(self) -> Dict[Label, Series]:
  }
 
  def lookup(
- self, row_labels: Sequence[Label], col_labels: Sequence[Label]
+ self, row_labels: Sequence[IndexLabel], col_labels: IndexLabel
  ) -> np.ndarray:
  """
  Label-based "fancy indexing" function for DataFrame.
@@ -4653,7 +4652,7 @@ def _replace_columnwise(
  def shift(
  self,
  periods=1,
- freq: Frequency = None,
+ freq=None,
  axis: Axis = 0,
  fill_value=lib.no_default,
  ) -> DataFrame:
@@ -8377,7 +8376,7 @@ def merge(
  )
 
  def round(
- self, decimals: Union[int, Dict[Label, int], Series] = 0, *args, **kwargs
+ self, decimals: Union[int, Dict[IndexLabel, int], Series] = 0, *args, **kwargs
  ) -> DataFrame:
  """
  Round a DataFrame to a variable number of decimal places.
@@ -9473,7 +9472,7 @@ def quantile(
  @doc(NDFrame.asfreq, **_shared_doc_kwargs)
  def asfreq(
  self,
- freq: Frequency,
+ freq,
  method=None,
  how: Optional[str] = None,
  normalize: bool = False,
@@ -9520,7 +9519,7 @@ def resample(
 
  def to_timestamp(
  self,
- freq: Frequency = None,
+ freq=None,
  how: str = "start",
  axis: Axis = 0,
  copy: bool = True,
@@ -9556,9 +9555,7 @@ def to_timestamp(
  setattr(new_obj, axis_name, new_ax)
  return new_obj
 
- def to_period(
- self, freq: Frequency = None, axis: Axis = 0, copy: bool = True
- ) -> DataFrame:
+ def to_period(self, freq=None, axis: Axis = 0, copy: bool = True) -> DataFrame:
  """
  Convert DataFrame from DatetimeIndex to PeriodIndex.