本文整理汇总了Python中pandas.core.tools.datetimes.to_time方法的典型用法代码示例。如果您正苦于以下问题：Python datetimes.to_time方法的具体用法？Python datetimes.to_time怎么用？Python datetimes.to_time使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pandas.core.tools.datetimes的用法示例。
在下文中一共展示了datetimes.to_time方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_parsers_time
# 需要导入模块: from pandas.core.tools import datetimes [as 别名]
# 或者: from pandas.core.tools.datetimes import to_time [as 别名]
def test_parsers_time(self):
# GH11818
strings = ["14:15", "1415", "2:15pm", "0215pm", "14:15:00", "141500",
"2:15:00pm", "021500pm", time(14, 15)]
expected = time(14, 15)
for time_string in strings:
assert tools.to_time(time_string) == expected
new_string = "14.15"
pytest.raises(ValueError, tools.to_time, new_string)
assert tools.to_time(new_string, format="%H.%M") == expected
arg = ["14:15", "20:20"]
expected_arr = [time(14, 15), time(20, 20)]
assert tools.to_time(arg) == expected_arr
assert tools.to_time(arg, format="%H:%M") == expected_arr
assert tools.to_time(arg, infer_time_format=True) == expected_arr
assert tools.to_time(arg, format="%I:%M%p",
errors="coerce") == [None, None]
res = tools.to_time(arg, format="%I:%M%p", errors="ignore")
tm.assert_numpy_array_equal(res, np.array(arg, dtype=np.object_))
with pytest.raises(ValueError):
tools.to_time(arg, format="%I:%M%p", errors="raise")
tm.assert_series_equal(tools.to_time(Series(arg, name="test")),
Series(expected_arr, name="test"))
res = tools.to_time(np.array(arg))
assert isinstance(res, list)
assert res == expected_arr 示例2: test_parsers_time
# 需要导入模块: from pandas.core.tools import datetimes [as 别名]
# 或者: from pandas.core.tools.datetimes import to_time [as 别名]
def test_parsers_time(self):
# GH11818
_skip_if_has_locale()
strings = ["14:15", "1415", "2:15pm", "0215pm", "14:15:00", "141500",
"2:15:00pm", "021500pm", time(14, 15)]
expected = time(14, 15)
for time_string in strings:
assert tools.to_time(time_string) == expected
new_string = "14.15"
pytest.raises(ValueError, tools.to_time, new_string)
assert tools.to_time(new_string, format="%H.%M") == expected
arg = ["14:15", "20:20"]
expected_arr = [time(14, 15), time(20, 20)]
assert tools.to_time(arg) == expected_arr
assert tools.to_time(arg, format="%H:%M") == expected_arr
assert tools.to_time(arg, infer_time_format=True) == expected_arr
assert tools.to_time(arg, format="%I:%M%p",
errors="coerce") == [None, None]
res = tools.to_time(arg, format="%I:%M%p", errors="ignore")
tm.assert_numpy_array_equal(res, np.array(arg, dtype=np.object_))
with pytest.raises(ValueError):
tools.to_time(arg, format="%I:%M%p", errors="raise")
tm.assert_series_equal(tools.to_time(Series(arg, name="test")),
Series(expected_arr, name="test"))
res = tools.to_time(np.array(arg))
assert isinstance(res, list)
assert res == expected_arr 示例3: indexer_between_time
# 需要导入模块: from pandas.core.tools import datetimes [as 别名]
# 或者: from pandas.core.tools.datetimes import to_time [as 别名]
def indexer_between_time(self, start_time, end_time, include_start=True,
include_end=True):
"""
Return index locations of values between particular times of day
(e.g., 9:00-9:30AM).
Parameters
----------
start_time, end_time : datetime.time, str
datetime.time or string in appropriate format ("%H:%M", "%H%M",
"%I:%M%p", "%I%M%p", "%H:%M:%S", "%H%M%S", "%I:%M:%S%p",
"%I%M%S%p").
include_start : boolean, default True
include_end : boolean, default True
Returns
-------
values_between_time : array of integers
See Also
--------
indexer_at_time, DataFrame.between_time
"""
start_time = tools.to_time(start_time)
end_time = tools.to_time(end_time)
time_micros = self._get_time_micros()
start_micros = _time_to_micros(start_time)
end_micros = _time_to_micros(end_time)
if include_start and include_end:
lop = rop = operator.le
elif include_start:
lop = operator.le
rop = operator.lt
elif include_end:
lop = operator.lt
rop = operator.le
else:
lop = rop = operator.lt
if start_time <= end_time:
join_op = operator.and_
else:
join_op = operator.or_
mask = join_op(lop(start_micros, time_micros),
rop(time_micros, end_micros))
return mask.nonzero()[0]