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Merged
merged 7 commits into from
Nov 28, 2021
Merged

Typ numerical ops #44607

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c5e0014
TYP: Type numerical operations
phofl Nov 23, 2021
8b99821
TYP: Type numerical operations
phofl Nov 23, 2021
36aca68
Add assert
phofl Nov 23, 2021
065a2b9
Improve typing
phofl Nov 24, 2021
cb4643f
Revert unnecessary change
phofl Nov 24, 2021
32ce991
Merge branch 'master' of https://github.com/pandas-dev/pandas into ty…
phofl Nov 26, 2021
0b26e97
Merge remote-tracking branch 'upstream/master' into typ_numerical_ops
phofl Nov 28, 2021
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195 changes: 148 additions & 47 deletions pandas/core/generic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10298,7 +10298,14 @@ def pct_change(
return rs

@final
def _agg_by_level(self, name, axis=0, level=0, skipna=True, **kwargs):
def _agg_by_level(
self,
name: str,
axis: Axis = 0,
level: Level = 0,
skipna: bool_t = True,
**kwargs,
):
if axis is None:
raise ValueError("Must specify 'axis' when aggregating by level.")
grouped = self.groupby(level=level, axis=axis, sort=False)
Expand All @@ -10311,8 +10318,15 @@ def _agg_by_level(self, name, axis=0, level=0, skipna=True, **kwargs):

@final
def _logical_func(
self, name: str, func, axis=0, bool_only=None, skipna=True, level=None, **kwargs
):
self,
name: str,
func,
axis: Axis = 0,
bool_only: bool_t | None = None,
skipna: bool_t = True,
level: Level | None = None,
**kwargs,
) -> Series | bool_t:
nv.validate_logical_func((), kwargs, fname=name)
validate_bool_kwarg(skipna, "skipna", none_allowed=False)
if level is not None:
Expand Down Expand Up @@ -10345,18 +10359,40 @@ def _logical_func(
filter_type="bool",
)

def any(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
def any(
self,
axis: Axis = 0,
bool_only: bool_t | None = None,
skipna: bool_t = True,
level: Level | None = None,
**kwargs,
) -> Series | bool_t:
return self._logical_func(
"any", nanops.nanany, axis, bool_only, skipna, level, **kwargs
)

def all(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
def all(
self,
axis: Axis = 0,
bool_only: bool_t | None = None,
skipna: bool_t = True,
level: Level | None = None,
**kwargs,
) -> Series | bool_t:
return self._logical_func(
"all", nanops.nanall, axis, bool_only, skipna, level, **kwargs
)

@final
def _accum_func(self, name: str, func, axis=None, skipna=True, *args, **kwargs):
def _accum_func(
self,
name: str,
func,
axis: Axis | None = None,
skipna: bool_t = True,
*args,
**kwargs,
):
skipna = nv.validate_cum_func_with_skipna(skipna, args, kwargs, name)
if axis is None:
axis = self._stat_axis_number
Expand All @@ -10380,34 +10416,34 @@ def block_accum_func(blk_values):

return self._constructor(result).__finalize__(self, method=name)

def cummax(self, axis=None, skipna=True, *args, **kwargs):
def cummax(self, axis: Axis | None = None, skipna: bool_t = True, *args, **kwargs):
return self._accum_func(
"cummax", np.maximum.accumulate, axis, skipna, *args, **kwargs
)

def cummin(self, axis=None, skipna=True, *args, **kwargs):
def cummin(self, axis: Axis | None = None, skipna: bool_t = True, *args, **kwargs):
return self._accum_func(
"cummin", np.minimum.accumulate, axis, skipna, *args, **kwargs
)

def cumsum(self, axis=None, skipna=True, *args, **kwargs):
def cumsum(self, axis: Axis | None = None, skipna: bool_t = True, *args, **kwargs):
return self._accum_func("cumsum", np.cumsum, axis, skipna, *args, **kwargs)

def cumprod(self, axis=None, skipna=True, *args, **kwargs):
def cumprod(self, axis: Axis | None = None, skipna: bool_t = True, *args, **kwargs):
return self._accum_func("cumprod", np.cumprod, axis, skipna, *args, **kwargs)

@final
def _stat_function_ddof(
self,
name: str,
func,
axis=None,
skipna=True,
level=None,
ddof=1,
numeric_only=None,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
ddof: int = 1,
numeric_only: bool_t | None = None,
**kwargs,
):
) -> Series | float:
nv.validate_stat_ddof_func((), kwargs, fname=name)
validate_bool_kwarg(skipna, "skipna", none_allowed=False)
if axis is None:
Expand All @@ -10428,22 +10464,40 @@ def _stat_function_ddof(
)

def sem(
self, axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs
):
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
ddof: int = 1,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function_ddof(
"sem", nanops.nansem, axis, skipna, level, ddof, numeric_only, **kwargs
)

def var(
self, axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs
):
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
ddof: int = 1,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function_ddof(
"var", nanops.nanvar, axis, skipna, level, ddof, numeric_only, **kwargs
)

def std(
self, axis=None, skipna=True, level=None, ddof=1, numeric_only=None, **kwargs
):
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
ddof: int = 1,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function_ddof(
"std", nanops.nanstd, axis, skipna, level, ddof, numeric_only, **kwargs
)
Expand All @@ -10453,10 +10507,10 @@ def _stat_function(
self,
name: str,
func,
axis=None,
skipna=True,
level=None,
numeric_only=None,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
):
if name == "median":
Expand All @@ -10483,32 +10537,74 @@ def _stat_function(
func, name=name, axis=axis, skipna=skipna, numeric_only=numeric_only
)

def min(self, axis=None, skipna=True, level=None, numeric_only=None, **kwargs):
def min(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
):
return self._stat_function(
"min", nanops.nanmin, axis, skipna, level, numeric_only, **kwargs
)

def max(self, axis=None, skipna=True, level=None, numeric_only=None, **kwargs):
def max(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
):
return self._stat_function(
"max", nanops.nanmax, axis, skipna, level, numeric_only, **kwargs
)

def mean(self, axis=None, skipna=True, level=None, numeric_only=None, **kwargs):
def mean(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function(
"mean", nanops.nanmean, axis, skipna, level, numeric_only, **kwargs
)

def median(self, axis=None, skipna=True, level=None, numeric_only=None, **kwargs):
def median(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function(
"median", nanops.nanmedian, axis, skipna, level, numeric_only, **kwargs
)

def skew(self, axis=None, skipna=True, level=None, numeric_only=None, **kwargs):
def skew(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function(
"skew", nanops.nanskew, axis, skipna, level, numeric_only, **kwargs
)

def kurt(self, axis=None, skipna=True, level=None, numeric_only=None, **kwargs):
def kurt(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
**kwargs,
) -> Series | float:
return self._stat_function(
"kurt", nanops.nankurt, axis, skipna, level, numeric_only, **kwargs
)
Expand All @@ -10520,11 +10616,11 @@ def _min_count_stat_function(
self,
name: str,
func,
axis=None,
skipna=True,
level=None,
numeric_only=None,
min_count=0,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
min_count: int = 0,
**kwargs,
):
if name == "sum":
Expand Down Expand Up @@ -10565,10 +10661,10 @@ def _min_count_stat_function(

def sum(
self,
axis=None,
skipna=True,
level=None,
numeric_only=None,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
min_count=0,
**kwargs,
):
Expand All @@ -10578,11 +10674,11 @@ def sum(

def prod(
self,
axis=None,
skipna=True,
level=None,
numeric_only=None,
min_count=0,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
numeric_only: bool_t | None = None,
min_count: int = 0,
**kwargs,
):
return self._min_count_stat_function(
Expand All @@ -10598,7 +10694,12 @@ def prod(

product = prod

def mad(self, axis=None, skipna=True, level=None):
def mad(
self,
axis: Axis | None = None,
skipna: bool_t = True,
level: Level | None = None,
) -> Series | float:
"""
{desc}

Expand Down
12 changes: 6 additions & 6 deletions pandas/core/groupby/groupby.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1931,7 +1931,7 @@ def mean(
2 4.0
Name: B, dtype: float64
"""
numeric_only = self._resolve_numeric_only(numeric_only)
numeric_only_bool = self._resolve_numeric_only(numeric_only)

if maybe_use_numba(engine):
from pandas.core._numba.kernels import sliding_mean
Expand All @@ -1940,8 +1940,8 @@ def mean(
else:
result = self._cython_agg_general(
"mean",
alt=lambda x: Series(x).mean(numeric_only=numeric_only),
numeric_only=numeric_only,
alt=lambda x: Series(x).mean(numeric_only=numeric_only_bool),
numeric_only=numeric_only_bool,
)
return result.__finalize__(self.obj, method="groupby")

Expand All @@ -1965,12 +1965,12 @@ def median(self, numeric_only: bool | lib.NoDefault = lib.no_default):
Series or DataFrame
Median of values within each group.
"""
numeric_only = self._resolve_numeric_only(numeric_only)
numeric_only_bool = self._resolve_numeric_only(numeric_only)

result = self._cython_agg_general(
"median",
alt=lambda x: Series(x).median(numeric_only=numeric_only),
numeric_only=numeric_only,
alt=lambda x: Series(x).median(numeric_only=numeric_only_bool),
numeric_only=numeric_only_bool,
)
return result.__finalize__(self.obj, method="groupby")

Expand Down