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TYP: pandas/core/frame.py (easy: Axis/Level) #38441

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Merged
merged 4 commits into from
Dec 13, 2020
Merged

TYP: pandas/core/frame.py (easy: Axis/Level) #38441

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3a4b971
typing (Axis/Level)
arw2019 Dec 13, 2020
1973968
review comment
arw2019 Dec 13, 2020
3ca989c
replace List[Axis]->Sequence[Axis] in reorder_levels
arw2019 Dec 13, 2020
3a8eab1
rebase
arw2019 Dec 13, 2020
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77 changes: 45 additions & 32 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4050,7 +4050,7 @@ def _reindex_index(
new_index,
method,
copy: bool,
level,
level: Level,
fill_value=np.nan,
limit=None,
tolerance=None,
Expand All @@ -4070,7 +4070,7 @@ def _reindex_columns(
new_columns,
method,
copy: bool,
level,
level: Level,
fill_value=None,
limit=None,
tolerance=None,
Expand Down Expand Up @@ -4110,14 +4110,14 @@ def align(
self,
other,
join: str = "outer",
axis=None,
level=None,
axis: Optional[Axis] = None,
level: Optional[Level] = None,
copy: bool = True,
fill_value=None,
method: Optional[str] = None,
limit=None,
fill_axis=0,
broadcast_axis=None,
fill_axis: Axis = 0,
broadcast_axis: Optional[Axis] = None,
) -> DataFrame:
return super().align(
other,
Expand Down Expand Up @@ -4198,10 +4198,10 @@ def reindex(self, *args, **kwargs) -> DataFrame:
def drop(
self,
labels=None,
axis=0,
axis: Axis = 0,
index=None,
columns=None,
level=None,
level: Optional[Level] = None,
inplace: bool = False,
errors: str = "raise",
):
Expand Down Expand Up @@ -4474,7 +4474,7 @@ def fillna(
self,
value=None,
method: Optional[str] = None,
axis=None,
axis: Optional[Axis] = None,
inplace: bool = False,
limit=None,
downcast=None,
Expand Down Expand Up @@ -4587,7 +4587,7 @@ def _replace_columnwise(

@doc(NDFrame.shift, klass=_shared_doc_kwargs["klass"])
def shift(
self, periods=1, freq=None, axis=0, fill_value=lib.no_default
self, periods=1, freq=None, axis: Axis = 0, fill_value=lib.no_default
) -> DataFrame:
axis = self._get_axis_number(axis)

Expand Down Expand Up @@ -5074,7 +5074,12 @@ def notnull(self) -> DataFrame:
return ~self.isna()

def dropna(
self, axis=0, how: str = "any", thresh=None, subset=None, inplace: bool = False
self,
axis: Axis = 0,
how: str = "any",
thresh=None,
subset=None,
inplace: bool = False,
):
"""
Remove missing values.
Expand Down Expand Up @@ -5454,7 +5459,7 @@ def f(vals):
def sort_values( # type: ignore[override]
self,
by,
axis=0,
axis: Axis = 0,
ascending=True,
inplace: bool = False,
kind: str = "quicksort",
Expand Down Expand Up @@ -5514,8 +5519,8 @@ def sort_values( # type: ignore[override]

def sort_index(
self,
axis=0,
level=None,
axis: Axis = 0,
level: Optional[Level] = None,
ascending: bool = True,
inplace: bool = False,
kind: str = "quicksort",
Expand Down Expand Up @@ -5932,7 +5937,7 @@ def nsmallest(self, n, columns, keep: str = "first") -> DataFrame:
self, n=n, keep=keep, columns=columns
).nsmallest()

def swaplevel(self, i=-2, j=-1, axis=0) -> DataFrame:
def swaplevel(self, i: Axis = -2, j: Axis = -1, axis: Axis = 0) -> DataFrame:
"""
Swap levels i and j in a MultiIndex on a particular axis.

Expand Down Expand Up @@ -5963,7 +5968,7 @@ def swaplevel(self, i=-2, j=-1, axis=0) -> DataFrame:
result.columns = result.columns.swaplevel(i, j)
return result

def reorder_levels(self, order, axis=0) -> DataFrame:
def reorder_levels(self, order: Sequence[Axis], axis: Axis = 0) -> DataFrame:
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This has to be Sequence not List because with List mypy complains

pandas/core/generic.py:8689: error: Argument 1 to "reorder_levels" of "DataFrame" has incompatible type "List[int]"; expected "List[Union[str, int]]"  [arg-type]
pandas/core/generic.py:8689: note: "List" is invariant -- see http://mypy.readthedocs.io/en/latest/common_issues.html#variance
pandas/core/generic.py:8689: note: Consider using "Sequence" instead, which is covariant
pandas/core/generic.py:8691: error: Argument 1 to "reorder_levels" of "DataFrame" has incompatible type "List[int]"; expected "List[Union[str, int]]"  [arg-type]
pandas/core/generic.py:8691: note: "List" is invariant -- see http://mypy.readthedocs.io/en/latest/common_issues.html#variance
pandas/core/generic.py:8691: note: Consider using "Sequence" instead, which is covariant

"""
Rearrange index levels using input order. May not drop or duplicate levels.

Expand Down Expand Up @@ -6726,8 +6731,8 @@ def update(
def groupby(
self,
by=None,
axis=0,
level=None,
axis: Axis = 0,
level: Optional[Level] = None,
as_index: bool = True,
sort: bool = True,
group_keys: bool = True,
Expand Down Expand Up @@ -7080,7 +7085,7 @@ def pivot_table(
observed=observed,
)

def stack(self, level=-1, dropna: bool = True):
def stack(self, level: Level = -1, dropna: bool = True):
"""
Stack the prescribed level(s) from columns to index.

Expand Down Expand Up @@ -7399,7 +7404,7 @@ def melt(
value_vars=None,
var_name=None,
value_name="value",
col_level=None,
col_level: Optional[Level] = None,
ignore_index=True,
) -> DataFrame:

Expand Down Expand Up @@ -7607,7 +7612,7 @@ def _gotitem(
see_also=_agg_summary_and_see_also_doc,
examples=_agg_examples_doc,
)
def aggregate(self, func=None, axis=0, *args, **kwargs):
def aggregate(self, func=None, axis: Axis = 0, *args, **kwargs):
axis = self._get_axis_number(axis)

relabeling, func, columns, order = reconstruct_func(func, **kwargs)
Expand Down Expand Up @@ -7638,7 +7643,7 @@ def aggregate(self, func=None, axis=0, *args, **kwargs):

return result

def _aggregate(self, arg, axis=0, *args, **kwargs):
def _aggregate(self, arg, axis: Axis = 0, *args, **kwargs):
if axis == 1:
# NDFrame.aggregate returns a tuple, and we need to transpose
# only result
Expand All @@ -7661,7 +7666,9 @@ def transform(
assert isinstance(result, DataFrame)
return result

def apply(self, func, axis=0, raw: bool = False, result_type=None, args=(), **kwds):
def apply(
self, func, axis: Axis = 0, raw: bool = False, result_type=None, args=(), **kwds
):
"""
Apply a function along an axis of the DataFrame.

Expand Down Expand Up @@ -8578,7 +8585,7 @@ def cov(

return self._constructor(base_cov, index=idx, columns=cols)

def corrwith(self, other, axis=0, drop=False, method="pearson") -> Series:
def corrwith(self, other, axis: Axis = 0, drop=False, method="pearson") -> Series:
"""
Compute pairwise correlation.

Expand Down Expand Up @@ -8674,7 +8681,9 @@ def c(x):
# ----------------------------------------------------------------------
# ndarray-like stats methods

def count(self, axis=0, level=None, numeric_only: bool = False):
def count(
self, axis: Axis = 0, level: Optional[Level] = None, numeric_only: bool = False
):
"""
Count non-NA cells for each column or row.

Expand Down Expand Up @@ -8778,7 +8787,7 @@ def count(self, axis=0, level=None, numeric_only: bool = False):

return result.astype("int64")

def _count_level(self, level, axis=0, numeric_only=False):
def _count_level(self, level: Level, axis: Axis = 0, numeric_only=False):
if numeric_only:
frame = self._get_numeric_data()
else:
Expand Down Expand Up @@ -8828,7 +8837,7 @@ def _reduce(
op,
name: str,
*,
axis=0,
axis: Axis = 0,
skipna: bool = True,
numeric_only: Optional[bool] = None,
filter_type=None,
Expand Down Expand Up @@ -8936,7 +8945,7 @@ def _get_data() -> DataFrame:
result = self._constructor_sliced(result, index=labels)
return result

def nunique(self, axis=0, dropna: bool = True) -> Series:
def nunique(self, axis: Axis = 0, dropna: bool = True) -> Series:
"""
Count distinct observations over requested axis.

Expand Down Expand Up @@ -8976,7 +8985,7 @@ def nunique(self, axis=0, dropna: bool = True) -> Series:
"""
return self.apply(Series.nunique, axis=axis, dropna=dropna)

def idxmin(self, axis=0, skipna: bool = True) -> Series:
def idxmin(self, axis: Axis = 0, skipna: bool = True) -> Series:
"""
Return index of first occurrence of minimum over requested axis.

Expand Down Expand Up @@ -9053,7 +9062,7 @@ def idxmin(self, axis=0, skipna: bool = True) -> Series:
result = [index[i] if i >= 0 else np.nan for i in indices]
return self._constructor_sliced(result, index=self._get_agg_axis(axis))

def idxmax(self, axis=0, skipna: bool = True) -> Series:
def idxmax(self, axis: Axis = 0, skipna: bool = True) -> Series:
"""
Return index of first occurrence of maximum over requested axis.

Expand Down Expand Up @@ -9142,7 +9151,7 @@ def _get_agg_axis(self, axis_num: int) -> Index:
raise ValueError(f"Axis must be 0 or 1 (got {repr(axis_num)})")

def mode(
self, axis=0, numeric_only: bool = False, dropna: bool = True
self, axis: Axis = 0, numeric_only: bool = False, dropna: bool = True
) -> DataFrame:
"""
Get the mode(s) of each element along the selected axis.
Expand Down Expand Up @@ -9231,7 +9240,11 @@ def f(s):
return data.apply(f, axis=axis)

def quantile(
self, q=0.5, axis=0, numeric_only: bool = True, interpolation: str = "linear"
self,
q=0.5,
axis: Axis = 0,
numeric_only: bool = True,
interpolation: str = "linear",
):
"""
Return values at the given quantile over requested axis.
Expand Down