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test_timefuncs.py
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from __future__ import annotations
import datetime as dt
from typing import (
TYPE_CHECKING,
Any,
Optional,
cast,
)
from dateutil.relativedelta import (
FR,
MO,
SA,
SU,
TH,
TU,
WE,
weekday as WeekdayClass,
)
import numpy as np
from numpy import typing as npt
import pandas as pd
import pytest
import pytz
from typing_extensions import (
assert_never,
assert_type,
)
from pandas._libs import NaTType
from pandas._libs.tslibs import BaseOffset
from pandas._libs.tslibs.offsets import DateOffset
if TYPE_CHECKING:
from pandas._typing import FulldatetimeDict
else:
FulldatetimeDict = Any
from pandas._typing import TimeUnit
from tests import (
PD_LTE_22,
TYPE_CHECKING_INVALID_USAGE,
check,
pytest_warns_bounded,
)
from pandas.tseries.holiday import USFederalHolidayCalendar
from pandas.tseries.offsets import (
BusinessDay,
BusinessHour,
CustomBusinessDay,
CustomBusinessHour,
Day,
)
if TYPE_CHECKING:
from pandas.core.series import PeriodSeries # noqa: F401
from pandas.core.series import TimedeltaSeries # noqa: F401
from pandas.core.series import TimestampSeries # noqa: F401
# Separately define here so pytest works
np_ndarray_bool = npt.NDArray[np.bool_]
def test_types_init() -> None:
ts: pd.Timestamp = pd.Timestamp("2021-03-01T12")
ts1: pd.Timestamp = pd.Timestamp(dt.date(2021, 3, 15))
ts2: pd.Timestamp = pd.Timestamp(dt.datetime(2021, 3, 10, 12))
ts3: pd.Timestamp = pd.Timestamp(pd.Timestamp("2021-03-01T12"))
ts4: pd.Timestamp = pd.Timestamp(1515590000.1, unit="s")
ts5: pd.Timestamp = pd.Timestamp(1515590000.1, unit="s", tz="US/Pacific")
ts6: pd.Timestamp = pd.Timestamp(1515590000100000000) # plain integer (nanosecond)
ts7: pd.Timestamp = pd.Timestamp(2021, 3, 10, 12)
ts8: pd.Timestamp = pd.Timestamp(year=2021, month=3, day=10, hour=12)
ts9: pd.Timestamp = pd.Timestamp(
year=2021, month=3, day=10, hour=12, tz="US/Pacific"
)
def test_types_arithmetic() -> None:
ts: pd.Timestamp = pd.to_datetime("2021-03-01")
ts2: pd.Timestamp = pd.to_datetime("2021-01-01")
delta: pd.Timedelta = pd.to_timedelta("1 day")
tsr: pd.Timedelta = ts - ts2
tsr2: pd.Timestamp = ts + delta
tsr3: pd.Timestamp = ts - delta
tsr4: pd.Timedelta = ts - dt.datetime(2021, 1, 3)
def test_types_comparison() -> None:
ts: pd.Timestamp = pd.to_datetime("2021-03-01")
ts2: pd.Timestamp = pd.to_datetime("2021-01-01")
tsr: bool = ts < ts2
tsr2: bool = ts > ts2
def test_types_timestamp_series_comparisons() -> None:
# GH 27
df = pd.DataFrame(["2020-01-01", "2019-01-01"])
tss = pd.to_datetime(df[0], format="%Y-%m-%d")
ts = pd.to_datetime("2019-02-01", format="%Y-%m-%d")
tssr = tss <= ts
tssr2 = tss >= ts
tssr3 = tss == ts
check(assert_type(tssr, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(tssr2, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(tssr3, "pd.Series[bool]"), pd.Series, np.bool_)
# GH 265
data = pd.date_range("2022-01-01", "2022-01-31", freq="D")
s = pd.Series(data)
ts2 = pd.Timestamp("2022-01-15")
check(assert_type(s, "TimestampSeries"), pd.Series, pd.Timestamp)
check(assert_type(ts2 <= s, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(ts2 >= s, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(ts2 < s, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(ts2 > s, "pd.Series[bool]"), pd.Series, np.bool_)
def test_types_pydatetime() -> None:
ts: pd.Timestamp = pd.Timestamp("2021-03-01T12")
datet: dt.datetime = ts.to_pydatetime()
datet2: dt.datetime = ts.to_pydatetime(False)
datet3: dt.datetime = ts.to_pydatetime(warn=True)
def test_to_timedelta() -> None:
td: pd.Timedelta = pd.to_timedelta(3, "days")
tds: pd.TimedeltaIndex = pd.to_timedelta([2, 3], "minutes")
def test_timedelta_arithmetic() -> None:
td1: pd.Timedelta = pd.to_timedelta(3, "days")
td2: pd.Timedelta = pd.to_timedelta(4, "hours")
td3: pd.Timedelta = td1 + td2
td4: pd.Timedelta = td1 - td2
td5: pd.Timedelta = td1 * 4.3
td6: pd.Timedelta = td3 / 10.2
def test_timedelta_series_arithmetic() -> None:
tds1: pd.TimedeltaIndex = pd.to_timedelta([2, 3], "minutes")
td1: pd.Timedelta = pd.Timedelta("2 days")
r1: pd.TimedeltaIndex = tds1 + td1
r2: pd.TimedeltaIndex = tds1 - td1
r3: pd.TimedeltaIndex = tds1 * 4.3
r4: pd.TimedeltaIndex = tds1 / 10.2
def test_timedelta_series_string() -> None:
seq_list = ["1 day"]
check(assert_type(pd.to_timedelta(seq_list), pd.TimedeltaIndex), pd.TimedeltaIndex)
def test_timestamp_timedelta_series_arithmetic() -> None:
ts1 = pd.to_datetime(pd.Series(["2022-03-05", "2022-03-06"]))
assert isinstance(ts1.iloc[0], pd.Timestamp)
td1 = pd.to_timedelta([2, 3], "seconds")
ts2 = pd.to_datetime(pd.Series(["2022-03-08", "2022-03-10"]))
r1 = ts1 - ts2
check(assert_type(r1, "TimedeltaSeries"), pd.Series, pd.Timedelta)
r2 = r1 / td1
check(assert_type(r2, "pd.Series[float]"), pd.Series, float)
r3 = r1 - td1
check(assert_type(r3, "TimedeltaSeries"), pd.Series, pd.Timedelta)
r4 = pd.Timedelta(5, "days") / r1
check(assert_type(r4, "pd.Series[float]"), pd.Series, float)
sb = pd.Series([1, 2]) == pd.Series([1, 3])
check(assert_type(sb, "pd.Series[bool]"), pd.Series, np.bool_)
r5 = sb * r1
check(assert_type(r5, "TimedeltaSeries"), pd.Series, pd.Timedelta)
r6 = r1 * 4
check(assert_type(r6, "TimedeltaSeries"), pd.Series, pd.Timedelta)
tsp1 = pd.Timestamp("2022-03-05")
dt1 = dt.datetime(2022, 9, 1, 12, 5, 30)
r7 = ts1 - tsp1
check(assert_type(r7, "TimedeltaSeries"), pd.Series, pd.Timedelta)
r8 = ts1 - dt1
check(assert_type(r8, "TimedeltaSeries"), pd.Series, pd.Timedelta)
def test_timestamp_dateoffset_arithmetic() -> None:
ts = pd.Timestamp("2022-03-18")
do = pd.DateOffset(days=366)
r1: pd.Timestamp = ts + do
def test_datetimeindex_plus_timedelta() -> None:
tscheck = pd.Series([pd.Timestamp("2022-03-05"), pd.Timestamp("2022-03-06")])
dti = pd.to_datetime(["2022-03-08", "2022-03-15"])
td_s = pd.to_timedelta(pd.Series([10, 20]), "minutes")
dti_td_s = dti + td_s
check(
assert_type(dti_td_s, "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
td_dti_s = td_s + dti
check(
assert_type(td_dti_s, "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
tdi = pd.to_timedelta([10, 20], "minutes")
dti_tdi_dti = dti + tdi
check(assert_type(dti_tdi_dti, "pd.DatetimeIndex"), pd.DatetimeIndex)
tdi_dti_dti = tdi + dti
check(assert_type(tdi_dti_dti, "pd.DatetimeIndex"), pd.DatetimeIndex)
dti_td_dti = dti + pd.Timedelta(10, "minutes")
check(assert_type(dti_td_dti, "pd.DatetimeIndex"), pd.DatetimeIndex)
ts_tdi_dti = pd.Timestamp("2022-03-05") + tdi
check(assert_type(ts_tdi_dti, pd.DatetimeIndex), pd.DatetimeIndex)
def test_datetimeindex_minus_timedelta() -> None:
# GH 280
tscheck = pd.Series([pd.Timestamp("2022-03-05"), pd.Timestamp("2022-03-06")])
dti = pd.to_datetime(["2022-03-08", "2022-03-15"])
td_s = pd.to_timedelta(pd.Series([10, 20]), "minutes")
dti_td_s = dti - td_s
check(
assert_type(dti_td_s, "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
tdi = pd.to_timedelta([10, 20], "minutes")
dti_tdi_dti = dti - tdi
check(assert_type(dti_tdi_dti, "pd.DatetimeIndex"), pd.DatetimeIndex)
dti_td_dti = dti - pd.Timedelta(10, "minutes")
check(assert_type(dti_td_dti, "pd.DatetimeIndex"), pd.DatetimeIndex)
dti_ts_tdi = dti - pd.Timestamp("2022-03-05")
check(assert_type(dti_ts_tdi, pd.TimedeltaIndex), pd.TimedeltaIndex)
def test_timestamp_plus_timedelta_series() -> None:
tscheck = pd.Series([pd.Timestamp("2022-03-05"), pd.Timestamp("2022-03-06")])
ts = pd.Timestamp("2022-03-05")
td = pd.to_timedelta(pd.Series([10, 20]), "minutes")
r3 = td + ts
check(assert_type(r3, "TimestampSeries"), pd.Series, pd.Timestamp)
r4 = ts + td
check(assert_type(r4, "TimestampSeries"), pd.Series, pd.Timestamp)
def test_timedelta_series_mult() -> None:
df = pd.DataFrame({"x": [1, 3, 5], "y": [2, 2, 6]})
std = (df["x"] < df["y"]) * pd.Timedelta(10, "minutes")
check(
assert_type(std, "TimedeltaSeries"),
pd.Series,
pd.Timedelta,
)
def test_timedelta_series_sum() -> None:
s = pd.Series(pd.to_datetime(["04/05/2022 11:00", "04/03/2022 10:00"])) - pd.Series(
pd.to_datetime(["04/05/2022 08:00", "04/03/2022 09:00"])
)
ssum = s.sum()
ires: int = ssum.days
sf = pd.Series([1.0, 2.2, 3.3])
sfsum: float = sf.sum()
def test_iso_calendar() -> None:
# GH 31
dates = pd.date_range(start="2012-01-01", end="2019-12-31", freq="W-MON")
dates.isocalendar()
def test_fail_on_adding_two_timestamps() -> None:
s1 = pd.Series(pd.to_datetime(["2022-05-01", "2022-06-01"]))
s2 = pd.Series(pd.to_datetime(["2022-05-15", "2022-06-15"]))
if TYPE_CHECKING_INVALID_USAGE:
ssum: pd.Series = s1 + s2 # type: ignore[operator] # pyright: ignore[reportOperatorIssue]
ts = pd.Timestamp("2022-06-30")
tsum: pd.Series = s1 + ts # type: ignore[operator] # pyright: ignore[reportOperatorIssue]
def test_dtindex_tzinfo() -> None:
# GH 71
dti = pd.date_range("2000-1-1", periods=10)
assert assert_type(dti.tzinfo, Optional[dt.tzinfo]) is None
def test_todatetime_fromnumpy() -> None:
# GH 72
t1 = np.datetime64("2022-07-04 02:30")
check(assert_type(pd.to_datetime(t1), pd.Timestamp), pd.Timestamp)
def test_comparisons_datetimeindex() -> None:
# GH 74
dti = pd.date_range("2000-01-01", "2000-01-10")
ts = pd.Timestamp("2000-01-05")
check(assert_type((dti < ts), np_ndarray_bool), np.ndarray)
check(assert_type((dti > ts), np_ndarray_bool), np.ndarray)
check(assert_type((dti >= ts), np_ndarray_bool), np.ndarray)
check(assert_type((dti <= ts), np_ndarray_bool), np.ndarray)
check(assert_type((dti == ts), np_ndarray_bool), np.ndarray)
check(assert_type((dti != ts), np_ndarray_bool), np.ndarray)
def test_to_datetime_nat() -> None:
# GH 88
check(
assert_type(pd.to_datetime("2021-03-01", errors="raise"), pd.Timestamp),
pd.Timestamp,
)
check(
assert_type(
pd.to_datetime("2021-03-01", errors="coerce"),
"pd.Timestamp | NaTType",
),
pd.Timestamp,
)
check(
assert_type(
pd.to_datetime("not a date", errors="coerce"),
"pd.Timestamp | NaTType",
),
NaTType,
)
def test_series_dt_accessors() -> None:
# GH 131
i0 = pd.date_range(start="2022-06-01", periods=10)
check(assert_type(i0, pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.to_series(), "TimestampSeries"), pd.Series, pd.Timestamp)
s0 = pd.Series(i0)
check(assert_type(s0.dt.date, "pd.Series[dt.date]"), pd.Series, dt.date)
check(assert_type(s0.dt.time, "pd.Series[dt.time]"), pd.Series, dt.time)
check(assert_type(s0.dt.timetz, "pd.Series[dt.time]"), pd.Series, dt.time)
check(assert_type(s0.dt.year, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.month, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.day, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.hour, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.minute, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.second, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.microsecond, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.nanosecond, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.dayofweek, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.day_of_week, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.weekday, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.dayofyear, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.day_of_year, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.quarter, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.is_month_start, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.is_month_end, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.is_quarter_start, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.is_quarter_end, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.is_year_start, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.is_year_end, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.is_leap_year, "pd.Series[bool]"), pd.Series, np.bool_)
check(assert_type(s0.dt.daysinmonth, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s0.dt.days_in_month, "pd.Series[int]"), pd.Series, np.integer)
assert assert_type(s0.dt.tz, Optional[dt.tzinfo]) is None
check(assert_type(s0.dt.freq, Optional[str]), str)
check(assert_type(s0.dt.isocalendar(), pd.DataFrame), pd.DataFrame)
check(assert_type(s0.dt.to_period("D"), "PeriodSeries"), pd.Series, pd.Period)
with pytest_warns_bounded(
FutureWarning,
"The behavior of DatetimeProperties.to_pydatetime is deprecated",
upper="2.2.99",
):
check(
assert_type(s0.dt.to_pydatetime(), np.ndarray),
np.ndarray if PD_LTE_22 else pd.Series,
dt.datetime,
)
s0_local = s0.dt.tz_localize("UTC")
check(
assert_type(s0_local, "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0.dt.tz_localize(None), "TimestampSeries"), pd.Series, pd.Timestamp
)
check(
assert_type(
s0.dt.tz_localize(pytz.UTC, nonexistent=dt.timedelta(0)),
"TimestampSeries",
),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0.dt.tz_localize(pytz.timezone("US/Eastern")), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0_local.dt.tz_convert("EST"), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0_local.dt.tz_convert(None), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0_local.dt.tz_convert(pytz.UTC), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(
s0_local.dt.tz_convert(pytz.timezone("US/Eastern")), "TimestampSeries"
),
pd.Series,
pd.Timestamp,
)
check(assert_type(s0.dt.tz, Optional[dt.tzinfo]), type(None))
check(assert_type(s0_local.dt.tz, Optional[dt.tzinfo]), dt.tzinfo)
check(assert_type(s0.dt.normalize(), "TimestampSeries"), pd.Series, pd.Timestamp)
check(assert_type(s0.dt.strftime("%Y"), "pd.Series[str]"), pd.Series, str)
check(
assert_type(s0.dt.round("D", nonexistent=dt.timedelta(1)), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0.dt.floor("D", nonexistent=dt.timedelta(1)), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(
assert_type(s0.dt.ceil("D", nonexistent=dt.timedelta(1)), "TimestampSeries"),
pd.Series,
pd.Timestamp,
)
check(assert_type(s0.dt.month_name(), "pd.Series[str]"), pd.Series, str)
check(assert_type(s0.dt.day_name(), "pd.Series[str]"), pd.Series, str)
check(assert_type(s0.dt.unit, TimeUnit), str)
check(assert_type(s0.dt.as_unit("s"), "TimestampSeries"), pd.Series, pd.Timestamp)
check(assert_type(s0.dt.as_unit("ms"), "TimestampSeries"), pd.Series, pd.Timestamp)
check(assert_type(s0.dt.as_unit("us"), "TimestampSeries"), pd.Series, pd.Timestamp)
check(assert_type(s0.dt.as_unit("ns"), "TimestampSeries"), pd.Series, pd.Timestamp)
i1 = pd.period_range(start="2022-06-01", periods=10)
check(assert_type(i1, pd.PeriodIndex), pd.PeriodIndex)
check(assert_type(i1.to_series(), pd.Series), pd.Series, pd.Period)
s1 = pd.Series(i1)
check(assert_type(s1.dt.qyear, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s1.dt.start_time, "TimestampSeries"), pd.Series, pd.Timestamp)
check(assert_type(s1.dt.end_time, "TimestampSeries"), pd.Series, pd.Timestamp)
i2 = pd.timedelta_range(start="1 day", periods=10)
check(assert_type(i2, pd.TimedeltaIndex), pd.TimedeltaIndex)
check(assert_type(i2.to_series(), "TimedeltaSeries"), pd.Series, pd.Timedelta)
s2 = pd.Series(i2)
check(assert_type(s2.dt.days, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s2.dt.seconds, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s2.dt.microseconds, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s2.dt.nanoseconds, "pd.Series[int]"), pd.Series, np.integer)
check(assert_type(s2.dt.components, pd.DataFrame), pd.DataFrame)
with pytest_warns_bounded(
FutureWarning,
"The behavior of TimedeltaProperties.to_pytimedelta is deprecated",
lower="2.2.99",
):
check(assert_type(s2.dt.to_pytimedelta(), np.ndarray), np.ndarray)
check(assert_type(s2.dt.total_seconds(), "pd.Series[float]"), pd.Series, float)
check(assert_type(s2.dt.unit, TimeUnit), str)
check(assert_type(s2.dt.as_unit("s"), "TimedeltaSeries"), pd.Series, pd.Timedelta)
check(assert_type(s2.dt.as_unit("ms"), "TimedeltaSeries"), pd.Series, pd.Timedelta)
check(assert_type(s2.dt.as_unit("us"), "TimedeltaSeries"), pd.Series, pd.Timedelta)
check(assert_type(s2.dt.as_unit("ns"), "TimedeltaSeries"), pd.Series, pd.Timedelta)
# Checks for general Series other than TimestampSeries and TimedeltaSeries
s4 = cast(
"pd.Series[pd.Timestamp]",
pd.Series([pd.Timestamp("2024-01-01"), pd.Timestamp("2024-01-02")]),
)
check(assert_type(s4.dt.unit, TimeUnit), str)
check(assert_type(s4.dt.as_unit("s"), pd.Series), pd.Series, pd.Timestamp)
check(assert_type(s4.dt.as_unit("ms"), pd.Series), pd.Series, pd.Timestamp)
check(assert_type(s4.dt.as_unit("us"), pd.Series), pd.Series, pd.Timestamp)
check(assert_type(s4.dt.as_unit("ns"), pd.Series), pd.Series, pd.Timestamp)
s5 = cast(
"pd.Series[pd.Timedelta]",
pd.Series([pd.Timedelta("1 day"), pd.Timedelta("2 days")]),
)
check(assert_type(s5.dt.unit, TimeUnit), str)
check(assert_type(s5.dt.as_unit("s"), pd.Series), pd.Series, pd.Timedelta)
check(assert_type(s5.dt.as_unit("ms"), pd.Series), pd.Series, pd.Timedelta)
check(assert_type(s5.dt.as_unit("us"), pd.Series), pd.Series, pd.Timedelta)
check(assert_type(s5.dt.as_unit("ns"), pd.Series), pd.Series, pd.Timedelta)
def test_datetimeindex_accessors() -> None:
# GH 194
x = pd.DatetimeIndex(["2022-08-14", "2022-08-20"])
check(assert_type(x.month, "pd.Index[int]"), pd.Index)
i0 = pd.date_range(start="2022-06-01", periods=10)
check(assert_type(i0, pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.date, np.ndarray), np.ndarray, dt.date)
check(assert_type(i0.time, np.ndarray), np.ndarray, dt.time)
check(assert_type(i0.timetz, np.ndarray), np.ndarray, dt.time)
check(assert_type(i0.year, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.month, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.day, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.hour, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.minute, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.second, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.microsecond, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.nanosecond, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.dayofweek, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.day_of_week, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.weekday, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.dayofyear, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.day_of_year, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.quarter, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.is_month_start, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.is_month_end, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.is_quarter_start, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.is_quarter_end, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.is_year_start, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.is_year_end, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.is_leap_year, npt.NDArray[np.bool_]), np.ndarray, np.bool_)
check(assert_type(i0.daysinmonth, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.days_in_month, "pd.Index[int]"), pd.Index, np.int32)
check(assert_type(i0.tz, Optional[dt.tzinfo]), type(None))
check(assert_type(i0.freq, Optional[BaseOffset]), BaseOffset)
check(assert_type(i0.isocalendar(), pd.DataFrame), pd.DataFrame)
check(assert_type(i0.to_period("D"), pd.PeriodIndex), pd.PeriodIndex, pd.Period)
check(
assert_type(i0.to_pydatetime(), npt.NDArray[np.object_]),
np.ndarray,
dt.datetime,
)
ilocal = i0.tz_localize("UTC")
check(assert_type(ilocal, pd.DatetimeIndex), pd.DatetimeIndex)
check(assert_type(i0.tz_localize(pytz.UTC), pd.DatetimeIndex), pd.DatetimeIndex)
check(
assert_type(i0.tz_localize(pytz.timezone("US/Central")), pd.DatetimeIndex),
pd.DatetimeIndex,
)
check(assert_type(ilocal.tz_convert("EST"), pd.DatetimeIndex), pd.DatetimeIndex)
check(assert_type(ilocal.tz_convert(pytz.UTC), pd.DatetimeIndex), pd.DatetimeIndex)
check(
assert_type(ilocal.tz_convert(pytz.timezone("US/Pacific")), pd.DatetimeIndex),
pd.DatetimeIndex,
)
check(assert_type(ilocal.tz, Optional[dt.tzinfo]), dt.tzinfo)
check(assert_type(i0.normalize(), pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.strftime("%Y"), pd.Index), pd.Index, str)
check(assert_type(i0.round("D"), pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.floor("D"), pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.ceil("D"), pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.month_name(), pd.Index), pd.Index, str)
check(assert_type(i0.day_name(), pd.Index), pd.Index, str)
check(assert_type(i0.is_normalized, bool), bool)
check(assert_type(i0.unit, TimeUnit), str)
check(assert_type(i0.as_unit("s"), pd.DatetimeIndex), pd.DatetimeIndex)
check(assert_type(i0.as_unit("ms"), pd.DatetimeIndex), pd.DatetimeIndex)
check(assert_type(i0.as_unit("us"), pd.DatetimeIndex), pd.DatetimeIndex)
check(assert_type(i0.as_unit("ns"), pd.DatetimeIndex), pd.DatetimeIndex)
def test_timedeltaindex_accessors() -> None:
# GH 292
i0 = pd.date_range("1/1/2021", "1/5/2021") - pd.Timestamp("1/3/2019")
check(assert_type(i0, pd.TimedeltaIndex), pd.TimedeltaIndex)
check(assert_type(i0.days, pd.Index), pd.Index, np.integer)
check(assert_type(i0.seconds, pd.Index), pd.Index, np.integer)
check(assert_type(i0.microseconds, pd.Index), pd.Index, np.integer)
check(assert_type(i0.nanoseconds, pd.Index), pd.Index, np.integer)
check(assert_type(i0.components, pd.DataFrame), pd.DataFrame)
check(assert_type(i0.to_pytimedelta(), np.ndarray), np.ndarray)
check(assert_type(i0.total_seconds(), pd.Index), pd.Index, float)
check(
assert_type(i0.round("D"), pd.TimedeltaIndex), pd.TimedeltaIndex, pd.Timedelta
)
check(
assert_type(i0.floor("D"), pd.TimedeltaIndex), pd.TimedeltaIndex, pd.Timedelta
)
check(assert_type(i0.ceil("D"), pd.TimedeltaIndex), pd.TimedeltaIndex, pd.Timedelta)
check(assert_type(i0.unit, TimeUnit), str)
check(assert_type(i0.as_unit("s"), pd.TimedeltaIndex), pd.TimedeltaIndex)
check(assert_type(i0.as_unit("ms"), pd.TimedeltaIndex), pd.TimedeltaIndex)
check(assert_type(i0.as_unit("us"), pd.TimedeltaIndex), pd.TimedeltaIndex)
check(assert_type(i0.as_unit("ns"), pd.TimedeltaIndex), pd.TimedeltaIndex)
def test_periodindex_accessors() -> None:
# GH 395
i0 = pd.period_range(start="2022-06-01", periods=10)
check(assert_type(i0, pd.PeriodIndex), pd.PeriodIndex, pd.Period)
check(assert_type(i0.year, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.month, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.day, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.hour, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.minute, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.second, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.dayofweek, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.day_of_week, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.weekday, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.dayofyear, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.day_of_year, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.quarter, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.daysinmonth, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.days_in_month, "pd.Index[int]"), pd.Index, np.integer)
check(assert_type(i0.freq, Optional[BaseOffset]), BaseOffset)
check(assert_type(i0.strftime("%Y"), pd.Index), pd.Index, str)
check(assert_type(i0.asfreq("D"), pd.PeriodIndex), pd.PeriodIndex, pd.Period)
check(assert_type(i0.end_time, pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(assert_type(i0.start_time, pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp)
check(
assert_type(i0.to_timestamp(), pd.DatetimeIndex), pd.DatetimeIndex, pd.Timestamp
)
check(assert_type(i0.freqstr, str), str)
def test_some_offsets() -> None:
# GH 222
check(
assert_type(
CustomBusinessDay(calendar=USFederalHolidayCalendar()), CustomBusinessDay
),
CustomBusinessDay,
)
# GH 223
check(
assert_type(pd.date_range("1/1/2022", "2/1/2022", freq="1D"), pd.DatetimeIndex),
pd.DatetimeIndex,
)
check(
assert_type(
pd.date_range("1/1/2022", "2/1/2022", freq=Day()), pd.DatetimeIndex
),
pd.DatetimeIndex,
)
check(
assert_type(
pd.bdate_range("1/1/2022", "2/1/2022", freq=BusinessDay()), pd.DatetimeIndex
),
pd.DatetimeIndex,
)
# GH 224
check(assert_type(dt.date.today() - Day(), dt.date), dt.date)
# GH 235
check(
assert_type(
pd.date_range("1/1/2022", "2/1/2022", freq=dt.timedelta(days=2)),
pd.DatetimeIndex,
),
pd.DatetimeIndex,
)
check(
assert_type(
pd.bdate_range("1/1/2022", "2/1/2022", freq=dt.timedelta(days=2)),
pd.DatetimeIndex,
),
pd.DatetimeIndex,
)
check(
assert_type(
pd.date_range(
dt.date(2022, 1, 1), dt.date(2022, 2, 1), freq=dt.timedelta(days=2)
),
pd.DatetimeIndex,
),
pd.DatetimeIndex,
)
check(
assert_type(
pd.bdate_range(
dt.date(2022, 1, 1), dt.date(2022, 2, 1), freq=dt.timedelta(days=2)
),
pd.DatetimeIndex,
),
pd.DatetimeIndex,
)
check(
assert_type(
pd.date_range("1/1/2022", "2/1/2022", freq=pd.Timedelta(days=5)),
pd.DatetimeIndex,
),
pd.DatetimeIndex,
)
check(
assert_type(
pd.bdate_range("1/1/2022", "2/1/2022", freq=pd.Timedelta(days=5)),
pd.DatetimeIndex,
),
pd.DatetimeIndex,
)
# GH 320
tswm1 = pd.Timestamp("9/23/2022") + pd.offsets.WeekOfMonth(2, True)
check(assert_type(tswm1, pd.Timestamp), pd.Timestamp)
tswm2 = pd.Timestamp("9/23/2022") + pd.offsets.LastWeekOfMonth(2, 3)
check(assert_type(tswm2, pd.Timestamp), pd.Timestamp)
# GH 396
check(
assert_type(
BusinessHour(start=dt.time(9, 30), end=dt.time(16, 0)), BusinessHour
),
BusinessHour,
)
check(
assert_type(BusinessHour(start="9:30", end="16:00"), BusinessHour), BusinessHour
)
check(
assert_type(
BusinessHour(
start=["9:30", dt.time(11, 30)], end=[dt.time(10, 30), "13:00"]
),
BusinessHour,
),
BusinessHour,
)
check(
assert_type(
CustomBusinessHour(start=dt.time(9, 30), end=dt.time(16, 0)),
CustomBusinessHour,
),
CustomBusinessHour,
)
check(
assert_type(CustomBusinessHour(start="9:30", end="16:00"), CustomBusinessHour),
CustomBusinessHour,
)
check(
assert_type(
CustomBusinessHour(
start=["9:30", dt.time(11, 30)], end=[dt.time(10, 30), "13:00"]
),
CustomBusinessHour,
),
CustomBusinessHour,
)
def test_timestampseries_offset() -> None:
"""Test that adding an offset to a timestamp series works."""
vv = pd.bdate_range("2024-09-01", "2024-09-10")
shifted_vv = vv + pd.tseries.offsets.YearEnd(0)
check(assert_type(shifted_vv, pd.DatetimeIndex), pd.DatetimeIndex)
def test_types_to_numpy() -> None:
td_s = pd.to_timedelta(pd.Series([10, 20]), "minutes")
check(assert_type(td_s.to_numpy(), np.ndarray), np.ndarray)
check(assert_type(td_s.to_numpy(dtype="int", copy=True), np.ndarray), np.ndarray)
check(assert_type(td_s.to_numpy(na_value=pd.Timedelta(0)), np.ndarray), np.ndarray)
def test_to_timedelta_units() -> None:
check(assert_type(pd.to_timedelta(1, "W"), pd.Timedelta), pd.Timedelta)
with pytest_warns_bounded(FutureWarning, "'w' is deprecated", lower="2.2.99"):
check(assert_type(pd.to_timedelta(1, "w"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "D"), pd.Timedelta), pd.Timedelta)
with pytest_warns_bounded(FutureWarning, "'d' is deprecated", lower="2.2.99"):
check(assert_type(pd.to_timedelta(1, "d"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "days"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "day"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "hours"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "hour"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "hr"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "h"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "m"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "minute"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "min"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "minutes"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "s"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "seconds"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "sec"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "second"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "ms"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "milliseconds"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "millisecond"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "milli"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "millis"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "us"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "microseconds"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "microsecond"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "µs"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "micro"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "micros"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "ns"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "nanoseconds"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "nano"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "nanos"), pd.Timedelta), pd.Timedelta)
check(assert_type(pd.to_timedelta(1, "nanosecond"), pd.Timedelta), pd.Timedelta)
def test_to_timedelta_scalar() -> None:
check(
assert_type(pd.to_timedelta(10, "ms", errors="raise"), pd.Timedelta),
pd.Timedelta,
)
check(
assert_type(
pd.to_timedelta(dt.timedelta(milliseconds=10), errors="coerce"),
pd.Timedelta,
),
pd.Timedelta,
)
def test_to_timedelta_series() -> None:
s = pd.Series([10, 20, 30, 40])
s2 = pd.Series(["10ms", "20ms", "30ms"])
check(assert_type(pd.to_timedelta(s, "ms"), "TimedeltaSeries"), pd.Series)
check(assert_type(pd.to_timedelta(s2), "TimedeltaSeries"), pd.Series)
def test_to_timedelta_index() -> None:
arg0 = [1.0, 2.0, 3.0]
arg1 = [
dt.timedelta(milliseconds=1),
dt.timedelta(milliseconds=2),
dt.timedelta(milliseconds=3),
]
arg2 = tuple(arg0)
arg3 = tuple(arg1)
arg4 = range(0, 10)
arg5 = np.arange(10)
arg6 = pd.Index(arg5)
check(
assert_type(pd.to_timedelta(arg0, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
check(
assert_type(pd.to_timedelta(arg1, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
check(
assert_type(pd.to_timedelta(arg2, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
check(
assert_type(pd.to_timedelta(arg3, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
check(
assert_type(pd.to_timedelta(arg4, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
check(
assert_type(pd.to_timedelta(arg5, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
check(
assert_type(pd.to_timedelta(arg6, "ms"), pd.TimedeltaIndex), pd.TimedeltaIndex
)
def test_bdate_range_holidays() -> None:
pd.bdate_range("2000-1-1", "2001-1-1", freq="C", holidays=["2000-12-15"])
pd.bdate_range("2000-1-1", "2001-1-1", freq="C", holidays=[dt.date(2000, 12, 15)])
pd.bdate_range(
"2000-1-1", "2001-1-1", freq="C", holidays=[pd.Timestamp(2000, 12, 15)]
)
pd.bdate_range(
"2000-1-1", "2001-1-1", freq="C", holidays=[np.datetime64("2000-12-15")]
)
pd.bdate_range(
"2000-1-1", "2001-1-1", freq="C", holidays=[dt.datetime(2000, 12, 15)]
)
pd.bdate_range(
"2000-1-1", "2001-1-1", freq="C", holidays=[dt.date(2000, 12, 15)], name=("a",)
)
def test_period_range() -> None:
check(
assert_type(
pd.period_range(pd.Period("2001Q1"), end=pd.Period("2010Q1")),
pd.PeriodIndex,
),
pd.PeriodIndex,
)
check(
assert_type(pd.period_range("2001Q1", end=pd.Period("2010Q1")), pd.PeriodIndex),
pd.PeriodIndex,
)
check(
assert_type(
pd.period_range("2001-01-01", end="2010-01-01", freq="Q"), pd.PeriodIndex
),
pd.PeriodIndex,
)
check(
assert_type(pd.period_range("2001Q1", periods=100, freq="Q"), pd.PeriodIndex),
pd.PeriodIndex,
)
check(
assert_type(pd.period_range("2001Q1", periods=100, freq=Day()), pd.PeriodIndex),
pd.PeriodIndex,
)
check(
assert_type(
pd.period_range("2001Q1", periods=100, freq=Day(), name=("A",)),
pd.PeriodIndex,
),
pd.PeriodIndex,
)
check(
assert_type(
pd.period_range(
pd.Timestamp("2001-01-01"), end=pd.Timestamp("2002-01-01"), freq="Q"
),
pd.PeriodIndex,
),
pd.PeriodIndex,
)
check(
assert_type(
pd.period_range(
dt.datetime(2001, 1, 1), end=dt.datetime(2002, 1, 1), freq="Q"
),
pd.PeriodIndex,
),
pd.PeriodIndex,
)
check(
assert_type(
pd.period_range(dt.date(2001, 1, 1), end=dt.date(2002, 1, 1), freq="Q"),
pd.PeriodIndex,
),
pd.PeriodIndex,
)
def test_to_datetime_scalar() -> None:
check(assert_type(pd.to_datetime("2000-01-01"), pd.Timestamp), pd.Timestamp)
check(assert_type(pd.to_datetime(1), pd.Timestamp), pd.Timestamp)
check(assert_type(pd.to_datetime(1.5), pd.Timestamp), pd.Timestamp)
check(
assert_type(pd.to_datetime(dt.datetime(2000, 1, 1)), pd.Timestamp), pd.Timestamp
)
check(assert_type(pd.to_datetime(dt.date(2000, 1, 1)), pd.Timestamp), pd.Timestamp)
check(
assert_type(pd.to_datetime(np.datetime64("2000-01-01")), pd.Timestamp),
pd.Timestamp,
)
def test_to_datetime_scalar_extended() -> None:
check(assert_type(pd.to_datetime("2000-01-01"), pd.Timestamp), pd.Timestamp)
check(assert_type(pd.to_datetime(1), pd.Timestamp), pd.Timestamp)
check(assert_type(pd.to_datetime(1.5), pd.Timestamp), pd.Timestamp)
check(
assert_type(pd.to_datetime(dt.datetime(2000, 1, 1)), pd.Timestamp), pd.Timestamp
)
check(assert_type(pd.to_datetime(dt.date(2000, 1, 1)), pd.Timestamp), pd.Timestamp)
check(
assert_type(pd.to_datetime(np.datetime64("2000-01-01")), pd.Timestamp),
pd.Timestamp,
)
def test_to_datetime_series() -> None:
s = pd.Series(["2000-01-01", "2000-01-02"])
check(assert_type(pd.to_datetime(s), "TimestampSeries"), pd.Series)
d: FulldatetimeDict = {
"year": [2000, 2000, 2000],
"month": [1, 1, 1],
"day": [1, 2, 3],
}
df = pd.DataFrame(d)
d_ex: FulldatetimeDict = {
"year": [2000, 2000, 2000],
"month": [1, 1, 1],
"day": [1, 2, 3],
"hour": [1, 1, 1],
"hours": [1, 1, 1],
"minute": [1, 1, 1],
"minutes": [1, 1, 1],
"second": [1, 1, 1],
"seconds": [1, 1, 1],
"ms": [1, 1, 1],
"us": [1, 1, 1],
"ns": [1, 1, 1],