TYP: pandas/core/frame.py

pandas/core/frame.py

@@ -22,6 +22,7 @@
  TYPE_CHECKING,
  Any,
  AnyStr,
+ Callable,
  Dict,
  FrozenSet,
  Hashable,
@@ -71,6 +72,7 @@
  NpDtype,
  PythonFuncType,
  Renamer,
+ Scalar,
  StorageOptions,
  Suffixes,
  ValueKeyFunc,
@@ -1215,7 +1217,9 @@ def iterrows(self) -> Iterable[Tuple[Hashable, Series]]:
  s = klass(v, index=columns, name=k)
  yield k, s
 
- def itertuples(self, index: bool = True, name: Optional[str] = "Pandas"):
+ def itertuples(
+ self, index: bool = True, name: Optional[str] = "Pandas"
+ ) -> Iterable[Tuple[Any, ...]]:
  """
  Iterate over DataFrame rows as namedtuples.
 
@@ -1459,7 +1463,11 @@ def __rmatmul__(self, other):
 
  @classmethod
  def from_dict(
- cls, data, orient="columns", dtype: Optional[Dtype] = None, columns=None
+ cls,
+ data,
+ orient: str = "columns",
+ dtype: Optional[Dtype] = None,
+ columns=None,
  ) -> DataFrame:
  """
  Construct DataFrame from dict of array-like or dicts.
@@ -1897,7 +1905,7 @@ def from_records(
  exclude=None,
  columns=None,
  coerce_float: bool = False,
- nrows=None,
+ nrows: Optional[int] = None,
  ) -> DataFrame:
  """
  Convert structured or record ndarray to DataFrame.
@@ -3087,7 +3095,7 @@ def info(
  show_counts=show_counts,
  )
 
- def memory_usage(self, index=True, deep=False) -> Series:
+ def memory_usage(self, index: bool = True, deep: bool = False) -> Series:
  """
  Return the memory usage of each column in bytes.
 
@@ -3489,7 +3497,7 @@ def _getitem_multilevel(self, key):
  # loc is neither a slice nor ndarray, so must be an int
  return self._ixs(loc, axis=1)
 
- def _get_value(self, index, col, takeable: bool = False):
+ def _get_value(self, index, col, takeable: bool = False) -> Scalar:
  """
  Quickly retrieve single value at passed column and index.
 
@@ -3657,7 +3665,7 @@ def _iset_item(self, loc: int, value):
  if len(self):
  self._check_setitem_copy()
 
- def _set_item(self, key, value):
+ def _set_item(self, key, value) -> None:
  """
  Add series to DataFrame in specified column.
 
@@ -3682,16 +3690,21 @@ def _set_item(self, key, value):
 
  self._set_item_mgr(key, value)
 
- def _set_value(self, index, col, value, takeable: bool = False):
+ def _set_value(
+ self, index: IndexLabel, col, value: Scalar, takeable: bool = False
+ ) -> None:
  """
  Put single value at passed column and index.
 
  Parameters
  ----------
- index : row label
- col : column label
+ index : Label
+ row label
+ col : Label
+ column label
  value : scalar
- takeable : interpret the index/col as indexers, default False
+ takeable : bool, default False
+ Sets whether or not index/col interpreted as indexers
  """
  try:
  if takeable:
@@ -3715,7 +3728,7 @@ def _set_value(self, index, col, value, takeable: bool = False):
  self.loc[index, col] = value
  self._item_cache.pop(col, None)
 
- def _ensure_valid_index(self, value):
+ def _ensure_valid_index(self, value) -> None:
  """
  Ensure that if we don't have an index, that we can create one from the
  passed value.
@@ -3912,6 +3925,7 @@ def query(self, expr: str, inplace: bool = False, **kwargs):
 
  if inplace:
  self._update_inplace(result)
+ return None
  else:
  return result
 
@@ -4379,7 +4393,9 @@ def _series(self):
  for idx, item in enumerate(self.columns)
  }
 
- def lookup(self, row_labels, col_labels) -> np.ndarray:
+ def lookup(
+ self, row_labels: Sequence[IndexLabel], col_labels: Sequence[IndexLabel]
+ ) -> np.ndarray:
  """
  Label-based "fancy indexing" function for DataFrame.
  Given equal-length arrays of row and column labels, return an
@@ -6574,7 +6590,7 @@ def _arith_method(self, other, op):
 
  _logical_method = _arith_method
 
- def _dispatch_frame_op(self, right, func, axis: Optional[int] = None):
+ def _dispatch_frame_op(self, right, func: Callable, axis: Optional[int] = None):
  """
  Evaluate the frame operation func(left, right) by evaluating
  column-by-column, dispatching to the Series implementation.
@@ -7910,7 +7926,7 @@ def explode(
 
  return result
 
- def unstack(self, level=-1, fill_value=None):
+ def unstack(self, level: Level = -1, fill_value=None):
  """
  Pivot a level of the (necessarily hierarchical) index labels.
 
@@ -7981,7 +7997,7 @@ def melt(
  var_name=None,
  value_name="value",
  col_level: Optional[Level] = None,
- ignore_index=True,
+ ignore_index: bool = True,
  ) -> DataFrame:
 
  return melt(
@@ -8846,7 +8862,9 @@ def merge(
  validate=validate,
  )
 
- def round(self, decimals=0, *args, **kwargs) -> DataFrame:
+ def round(
+ self, decimals: Union[int, Dict[IndexLabel, int], Series] = 0, *args, **kwargs
+ ) -> DataFrame:
  """
  Round a DataFrame to a variable number of decimal places.
 
@@ -8960,7 +8978,11 @@ def _series_round(s, decimals):
  # ----------------------------------------------------------------------
  # Statistical methods, etc.
 
- def corr(self, method="pearson", min_periods=1) -> DataFrame:
+ def corr(
+ self,
+ method: Union[str, Callable[[np.ndarray, np.ndarray], float]] = "pearson",
+ min_periods: int = 1,
+ ) -> DataFrame:
  """
  Compute pairwise correlation of columns, excluding NA/null values.