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TYP: annotations in nanops #33935

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Merged
merged 3 commits into from
May 6, 2020
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TYP: annotations in nanops #33935

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TYP: annotations in nanops
jbrockmendel May 2, 2020
1d5cf06
dummy commit to force CI
jbrockmendel May 2, 2020
062bd5a
Merge branch 'master' of https://github.com/pandas-dev/pandas into ty…
jbrockmendel May 2, 2020
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30 changes: 13 additions & 17 deletions pandas/core/nanops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
from pandas._config import get_option

from pandas._libs import NaT, Timedelta, Timestamp, iNaT, lib
from pandas._typing import ArrayLike, Dtype, F, Scalar
from pandas._typing import ArrayLike, Dtype, DtypeObj, F, Scalar
from pandas.compat._optional import import_optional_dependency

from pandas.core.dtypes.cast import _int64_max, maybe_upcast_putmask
Expand Down Expand Up @@ -133,7 +133,7 @@ def f(
return f


def _bn_ok_dtype(dtype: Dtype, name: str) -> bool:
def _bn_ok_dtype(dtype: DtypeObj, name: str) -> bool:
# Bottleneck chokes on datetime64, PeriodDtype (or and EA)
if not is_object_dtype(dtype) and not needs_i8_conversion(dtype):

Expand Down Expand Up @@ -166,7 +166,7 @@ def _has_infs(result) -> bool:


def _get_fill_value(
dtype: Dtype, fill_value: Optional[Scalar] = None, fill_value_typ=None
dtype: DtypeObj, fill_value: Optional[Scalar] = None, fill_value_typ=None
):
""" return the correct fill value for the dtype of the values """
if fill_value is not None:
Expand Down Expand Up @@ -270,9 +270,9 @@ def _get_values(
Potential copy of input value array
mask : Optional[ndarray[bool]]
Mask for values, if deemed necessary to compute
dtype : dtype
dtype : np.dtype
dtype for values
dtype_max : dtype
dtype_max : np.dtype
platform independent dtype
fill_value : Any
fill value used
Expand Down Expand Up @@ -312,20 +312,20 @@ def _get_values(
# return a platform independent precision dtype
dtype_max = dtype
if is_integer_dtype(dtype) or is_bool_dtype(dtype):
dtype_max = np.int64
dtype_max = np.dtype(np.int64)
elif is_float_dtype(dtype):
dtype_max = np.float64
dtype_max = np.dtype(np.float64)

return values, mask, dtype, dtype_max, fill_value


def _na_ok_dtype(dtype) -> bool:
def _na_ok_dtype(dtype: DtypeObj) -> bool:
if needs_i8_conversion(dtype):
return False
return not issubclass(dtype.type, np.integer)


def _wrap_results(result, dtype: Dtype, fill_value=None):
def _wrap_results(result, dtype: DtypeObj, fill_value=None):
""" wrap our results if needed """
if is_datetime64_any_dtype(dtype):
if fill_value is None:
Expand Down Expand Up @@ -597,7 +597,7 @@ def get_median(x):
return np.nan
return np.nanmedian(x[mask])

values, mask, dtype, dtype_max, _ = _get_values(values, skipna, mask=mask)
values, mask, dtype, _, _ = _get_values(values, skipna, mask=mask)
if not is_float_dtype(values.dtype):
try:
values = values.astype("f8")
Expand Down Expand Up @@ -716,7 +716,7 @@ def nanstd(values, axis=None, skipna=True, ddof=1, mask=None):
1.0
"""
orig_dtype = values.dtype
values, mask, dtype, dtype_max, fill_value = _get_values(values, skipna, mask=mask)
values, mask, _, _, _ = _get_values(values, skipna, mask=mask)

result = np.sqrt(nanvar(values, axis=axis, skipna=skipna, ddof=ddof, mask=mask))
return _wrap_results(result, orig_dtype)
Expand Down Expand Up @@ -910,9 +910,7 @@ def nanargmax(
>>> nanops.nanargmax(arr, axis=1)
array([2, 2, 1, 1], dtype=int64)
"""
values, mask, dtype, _, _ = _get_values(
values, True, fill_value_typ="-inf", mask=mask
)
values, mask, _, _, _ = _get_values(values, True, fill_value_typ="-inf", mask=mask)
result = values.argmax(axis)
result = _maybe_arg_null_out(result, axis, mask, skipna)
return result
Expand Down Expand Up @@ -956,9 +954,7 @@ def nanargmin(
>>> nanops.nanargmin(arr, axis=1)
array([0, 0, 1, 1], dtype=int64)
"""
values, mask, dtype, _, _ = _get_values(
values, True, fill_value_typ="+inf", mask=mask
)
values, mask, _, _, _ = _get_values(values, True, fill_value_typ="+inf", mask=mask)
result = values.argmin(axis)
result = _maybe_arg_null_out(result, axis, mask, skipna)
return result
Expand Down