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ENH: maybe_convert_objects seen NaT speed-up #27300

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Merged
merged 4 commits into from
Jul 9, 2019
Merged

ENH: maybe_convert_objects seen NaT speed-up #27300

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0f30fc5
Break added
BeforeFlight Jul 7, 2019
56002cd
Asv bench and what's new entry added.
BeforeFlight Jul 7, 2019
790bf8c
Imports order changed. What's new entry changed.
BeforeFlight Jul 7, 2019
e8173c6
Fix imports order, remove what's new entry.
BeforeFlight Jul 7, 2019
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15 changes: 15 additions & 0 deletions asv_bench/benchmarks/algorithms.py
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Expand Up @@ -2,6 +2,8 @@

import numpy as np

from pandas._libs import lib

import pandas as pd
from pandas.util import testing as tm

Expand All @@ -13,6 +15,19 @@
pass


class MaybeConvertObjects:
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Not sure we even need this benchmark since it doesn't indicate anything from end user experience but up to @jreback

Break alone in PR lgtm

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I want to add more tests here later as well - for more generalized cases.

def setup(self):
N = 10 ** 5

data = list(range(N))
data[0] = pd.NaT
data = np.array(data)
self.data = data

def time_maybe_convert_objects(self):
lib.maybe_convert_objects(self.data)


class Factorize:

params = [[True, False], ["int", "uint", "float", "string"]]
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1 change: 0 additions & 1 deletion doc/source/whatsnew/v0.25.0.rst
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Expand Up @@ -940,7 +940,6 @@ Performance improvements
- For :meth:`to_datetime` changed default value of cache parameter to ``True`` (:issue:`26043`)
- Improved performance of :class:`DatetimeIndex` and :class:`PeriodIndex` slicing given non-unique, monotonic data (:issue:`27136`).


.. _whatsnew_0250.bug_fixes:

Bug fixes
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1 change: 1 addition & 0 deletions pandas/_libs/lib.pyx
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Expand Up @@ -1955,6 +1955,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0,
seen.timedelta_ = 1
if not (convert_datetime or convert_timedelta):
seen.object_ = 1
break
elif util.is_bool_object(val):
seen.bool_ = 1
bools[i] = val
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