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REF: avoid sanitize_to_nanoseconds #49009

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Merged
merged 2 commits into from
Oct 10, 2022
Merged

REF: avoid sanitize_to_nanoseconds #49009

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85a82a1
REF: avoid sanitize_to_nanoseconds
jbrockmendel Oct 8, 2022
980d792
fix test
jbrockmendel Oct 9, 2022
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5 changes: 3 additions & 2 deletions pandas/core/construction.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,7 +45,6 @@
maybe_convert_platform,
maybe_infer_to_datetimelike,
maybe_upcast,
sanitize_to_nanoseconds,
)
from pandas.core.dtypes.common import (
is_datetime64_ns_dtype,
Expand Down Expand Up @@ -782,7 +781,9 @@ def _try_cast(
if is_ndarray:
arr = cast(np.ndarray, arr)
if arr.dtype != object:
return sanitize_to_nanoseconds(arr, copy=copy)
if copy:
return arr.copy()
return arr

out = maybe_infer_to_datetimelike(arr)
if out is arr and copy:
Expand Down
7 changes: 1 addition & 6 deletions pandas/core/dtypes/cast.py
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Expand Up @@ -1423,12 +1423,7 @@ def maybe_cast_to_datetime(
return astype_nansafe(value, dtype) # type: ignore[arg-type]

elif isinstance(value, np.ndarray):
if value.dtype.kind in ["M", "m"]:
# catch a datetime/timedelta that is not of ns variety
# and no coercion specified
value = sanitize_to_nanoseconds(value)

elif value.dtype == _dtype_obj:
if value.dtype == _dtype_obj:
value = maybe_infer_to_datetimelike(value)

elif isinstance(value, list):
Expand Down
10 changes: 6 additions & 4 deletions pandas/core/groupby/grouper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,6 @@
from pandas.util._decorators import cache_readonly
from pandas.util._exceptions import find_stack_level

from pandas.core.dtypes.cast import sanitize_to_nanoseconds
from pandas.core.dtypes.common import (
is_categorical_dtype,
is_list_like,
Expand Down Expand Up @@ -558,9 +557,12 @@ def __init__(
raise AssertionError(errmsg)

if isinstance(self.grouping_vector, np.ndarray):
# if we have a date/time-like grouper, make sure that we have
# Timestamps like
self.grouping_vector = sanitize_to_nanoseconds(self.grouping_vector)
if self.grouping_vector.dtype.kind in ["m", "M"]:
# if we have a date/time-like grouper, make sure that we have
# Timestamps like
# TODO 2022-10-08 we only have one test that gets here and
# values are already in nanoseconds in that case.
self.grouping_vector = Series(self.grouping_vector).to_numpy()
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So Series(...).to_numpy() will coerce to nanos and then output to numpy? Is this a lot slower than sanitize_to_nanoseconds?

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So Series(...).to_numpy() will coerce to nanos and then output to numpy?

Yes.

Is this a lot slower than sanitize_to_nanoseconds?

A bit. Adds about 65 microseconds.

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Okay. I guess that's a fair tradeoff for being able to clean up sanitize_to_nanoseconds in #48670


def __repr__(self) -> str:
return f"Grouping({self.name})"
Expand Down