/
datetime.py
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/
datetime.py
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from __future__ import annotations
from typing import TYPE_CHECKING, Iterable
from polars._utils.convert import to_py_date, to_py_datetime
from polars._utils.deprecation import deprecate_function, deprecate_renamed_function
from polars._utils.unstable import unstable
from polars._utils.wrap import wrap_s
from polars.datatypes import Date, Datetime, Duration, Time
from polars.series.utils import expr_dispatch
if TYPE_CHECKING:
import datetime as dt
from polars import Expr, Series
from polars.polars import PySeries
from polars.type_aliases import (
Ambiguous,
EpochTimeUnit,
IntoExpr,
NonExistent,
Roll,
TemporalLiteral,
TimeUnit,
)
@expr_dispatch
class DateTimeNameSpace:
"""Series.dt namespace."""
_accessor = "dt"
def __init__(self, series: Series):
self._s: PySeries = series._s
def __getitem__(self, item: int) -> dt.date | dt.datetime | dt.timedelta:
s = wrap_s(self._s)
return s[item]
def add_business_days(
self,
n: int | IntoExpr,
week_mask: Iterable[bool] = (True, True, True, True, True, False, False),
holidays: Iterable[dt.date] = (),
roll: Roll = "raise",
) -> Expr:
"""
Offset by `n` business days.
Parameters
----------
n
Number of business days to offset by. Can be a single number of an
expression.
week_mask
Which days of the week to count. The default is Monday to Friday.
If you wanted to count only Monday to Thursday, you would pass
`(True, True, True, True, False, False, False)`.
holidays
Holidays to exclude from the count. The Python package
`python-holidays <https://github.com/vacanza/python-holidays>`_
may come in handy here. You can install it with ``pip install holidays``,
and then, to get all Dutch holidays for years 2020-2024:
.. code-block:: python
import holidays
my_holidays = holidays.country_holidays("NL", years=range(2020, 2025))
and pass `holidays=my_holidays` when you call `business_day_count`.
roll
What to do when the start date lands on a non-business day. Options are:
- `'raise'`: raise an error
- `'forward'`: move to the next business day
- `'backward'`: move to the previous business day
Returns
-------
Expr
Data type is preserved.
Examples
--------
>>> from datetime import date
>>> s = pl.Series("start", [date(2020, 1, 1), date(2020, 1, 2)])
>>> s.dt.add_business_days(5)
shape: (2,)
Series: 'start' [date]
[
2020-01-08
2020-01-09
]
You can pass a custom weekend - for example, if you only take Sunday off:
>>> week_mask = (True, True, True, True, True, True, False)
>>> s.dt.add_business_days(5, week_mask)
shape: (2,)
Series: 'start' [date]
[
2020-01-07
2020-01-08
]
You can also pass a list of holidays:
>>> from datetime import date
>>> holidays = [date(2020, 1, 3), date(2020, 1, 6)]
>>> s.dt.add_business_days(5, holidays=holidays)
shape: (2,)
Series: 'start' [date]
[
2020-01-10
2020-01-13
]
Roll all dates forwards to the next business day:
>>> s = pl.Series("start", [date(2020, 1, 5), date(2020, 1, 6)])
>>> s.dt.add_business_days(0, roll="forward")
shape: (2,)
Series: 'start' [date]
[
2020-01-06
2020-01-06
]
"""
def min(self) -> dt.date | dt.datetime | dt.timedelta | None:
"""
Return minimum as Python datetime.
Examples
--------
>>> from datetime import date
>>> s = pl.Series([date(2001, 1, 1), date(2001, 1, 2), date(2001, 1, 3)])
>>> s.dt.min()
datetime.date(2001, 1, 1)
"""
return wrap_s(self._s).min() # type: ignore[return-value]
def max(self) -> dt.date | dt.datetime | dt.timedelta | None:
"""
Return maximum as Python datetime.
Examples
--------
>>> from datetime import date
>>> s = pl.Series([date(2001, 1, 1), date(2001, 1, 2), date(2001, 1, 3)])
>>> s.dt.max()
datetime.date(2001, 1, 3)
"""
return wrap_s(self._s).max() # type: ignore[return-value]
def median(self) -> TemporalLiteral | float | None:
"""
Return median as python DateTime.
Examples
--------
>>> from datetime import datetime
>>> date = pl.datetime_range(
... datetime(2001, 1, 1), datetime(2001, 1, 3), "1d", eager=True
... ).alias("datetime")
>>> date
shape: (3,)
Series: 'datetime' [datetime[μs]]
[
2001-01-01 00:00:00
2001-01-02 00:00:00
2001-01-03 00:00:00
]
>>> date.dt.median()
datetime.datetime(2001, 1, 2, 0, 0)
"""
s = wrap_s(self._s)
out = s.median()
if out is not None:
if s.dtype == Date:
return to_py_date(int(out)) # type: ignore[arg-type]
elif s.dtype in (Datetime, Duration, Time):
return out # type: ignore[return-value]
else:
return to_py_datetime(int(out), s.dtype.time_unit) # type: ignore[arg-type, attr-defined]
return None
def mean(self) -> TemporalLiteral | float | None:
"""
Return mean as python DateTime.
Examples
--------
>>> from datetime import datetime
>>> s = pl.Series(
... [datetime(2001, 1, 1), datetime(2001, 1, 2), datetime(2001, 1, 3)]
... )
>>> s.dt.mean()
datetime.datetime(2001, 1, 2, 0, 0)
"""
s = wrap_s(self._s)
out = s.mean()
if out is not None:
if s.dtype == Date:
return to_py_date(int(out)) # type: ignore[arg-type]
elif s.dtype in (Datetime, Duration, Time):
return out # type: ignore[return-value]
else:
return to_py_datetime(int(out), s.dtype.time_unit) # type: ignore[arg-type, attr-defined]
return None
def to_string(self, format: str) -> Series:
"""
Convert a Date/Time/Datetime column into a String column with the given format.
Similar to `cast(pl.String)`, but this method allows you to customize the
formatting of the resulting string.
Parameters
----------
format
Format to use, refer to the `chrono strftime documentation
<https://docs.rs/chrono/latest/chrono/format/strftime/index.html>`_
for specification. Example: `"%y-%m-%d"`.
Examples
--------
>>> from datetime import datetime
>>> s = pl.Series(
... "datetime",
... [datetime(2020, 3, 1), datetime(2020, 4, 1), datetime(2020, 5, 1)],
... )
>>> s.dt.to_string("%Y/%m/%d")
shape: (3,)
Series: 'datetime' [str]
[
"2020/03/01"
"2020/04/01"
"2020/05/01"
]
If you're interested in the day name / month name, you can use
`'%A'` / `'%B'`:
>>> s.dt.to_string("%A")
shape: (3,)
Series: 'datetime' [str]
[
"Sunday"
"Wednesday"
"Friday"
]
>>> s.dt.to_string("%B")
shape: (3,)
Series: 'datetime' [str]
[
"March"
"April"
"May"
]
"""
def strftime(self, format: str) -> Series:
"""
Convert a Date/Time/Datetime column into a String column with the given format.
Similar to `cast(pl.String)`, but this method allows you to customize the
formatting of the resulting string.
Alias for :func:`to_string`.
Parameters
----------
format
Format to use, refer to the `chrono strftime documentation
<https://docs.rs/chrono/latest/chrono/format/strftime/index.html>`_
for specification. Example: `"%y-%m-%d"`.
See Also
--------
to_string : The identical Series method for which `strftime` is an alias.
Examples
--------
>>> from datetime import datetime
>>> s = pl.Series(
... "datetime",
... [datetime(2020, 3, 1), datetime(2020, 4, 1), datetime(2020, 5, 1)],
... )
>>> s.dt.strftime("%Y/%m/%d")
shape: (3,)
Series: 'datetime' [str]
[
"2020/03/01"
"2020/04/01"
"2020/05/01"
]
If you're interested in the day name / month name, you can use
`'%A'` / `'%B'`:
>>> s.dt.strftime("%A")
shape: (3,)
Series: 'datetime' [str]
[
"Sunday"
"Wednesday"
"Friday"
]
>>> s.dt.strftime("%B")
shape: (3,)
Series: 'datetime' [str]
[
"March"
"April"
"May"
]
"""
return self.to_string(format)
def millennium(self) -> Expr:
"""
Extract the millennium from underlying representation.
Applies to Date and Datetime columns.
Returns the millennium number in the calendar date.
Returns
-------
Expr
Expression of data type :class:`Int32`.
Examples
--------
>>> from datetime import date
>>> s = pl.Series(
... "dt",
... [
... date(999, 12, 31),
... date(1897, 5, 7),
... date(2000, 1, 1),
... date(2001, 7, 5),
... date(3002, 10, 20),
... ],
... )
>>> s.dt.millennium()
shape: (5,)
Series: 'dt' [i32]
[
1
2
2
3
4
]
"""
def century(self) -> Expr:
"""
Extract the century from underlying representation.
Applies to Date and Datetime columns.
Returns the century number in the calendar date.
Returns
-------
Expr
Expression of data type :class:`Int32`.
Examples
--------
>>> from datetime import date
>>> s = pl.Series(
... "dt",
... [
... date(999, 12, 31),
... date(1897, 5, 7),
... date(2000, 1, 1),
... date(2001, 7, 5),
... date(3002, 10, 20),
... ],
... )
>>> s.dt.century()
shape: (5,)
Series: 'dt' [i32]
[
10
19
20
21
31
]
"""
def year(self) -> Series:
"""
Extract the year from the underlying date representation.
Applies to Date and Datetime columns.
Returns the year number in the calendar date.
Returns
-------
Series
Series of data type :class:`Int32`.
Examples
--------
>>> from datetime import date
>>> s = pl.Series("date", [date(2001, 1, 1), date(2002, 1, 1)])
>>> s.dt.year()
shape: (2,)
Series: 'date' [i32]
[
2001
2002
]
"""
def is_leap_year(self) -> Series:
"""
Determine whether the year of the underlying date representation is a leap year.
Applies to Date and Datetime columns.
Returns
-------
Series
Series of data type :class:`Boolean`.
Examples
--------
>>> from datetime import date
>>> s = pl.Series(
... "date", [date(2000, 1, 1), date(2001, 1, 1), date(2002, 1, 1)]
... )
>>> s.dt.is_leap_year()
shape: (3,)
Series: 'date' [bool]
[
true
false
false
]
"""
def iso_year(self) -> Series:
"""
Extract ISO year from underlying Date representation.
Applies to Date and Datetime columns.
Returns the year number according to the ISO standard.
This may not correspond with the calendar year.
Returns
-------
Series
Series of data type :class:`Int32`.
Examples
--------
>>> from datetime import datetime
>>> dt = datetime(2022, 1, 1, 7, 8, 40)
>>> pl.Series([dt]).dt.iso_year()
shape: (1,)
Series: '' [i32]
[
2021
]
"""
def quarter(self) -> Series:
"""
Extract quarter from underlying Date representation.
Applies to Date and Datetime columns.
Returns the quarter ranging from 1 to 4.
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import date
>>> date = pl.date_range(
... date(2001, 1, 1), date(2001, 4, 1), interval="1mo", eager=True
... ).alias("date")
>>> date.dt.quarter()
shape: (4,)
Series: 'date' [i8]
[
1
1
1
2
]
"""
def month(self) -> Series:
"""
Extract the month from the underlying date representation.
Applies to Date and Datetime columns.
Returns the month number starting from 1.
The return value ranges from 1 to 12.
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import date
>>> date = pl.date_range(
... date(2001, 1, 1), date(2001, 4, 1), interval="1mo", eager=True
... ).alias("date")
>>> date.dt.month()
shape: (4,)
Series: 'date' [i8]
[
1
2
3
4
]
"""
def week(self) -> Series:
"""
Extract the week from the underlying date representation.
Applies to Date and Datetime columns.
Returns the ISO week number starting from 1.
The return value ranges from 1 to 53. (The last week of year differs by years.)
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import date
>>> date = pl.date_range(
... date(2001, 1, 1), date(2001, 4, 1), interval="1mo", eager=True
... ).alias("date")
>>> date.dt.week()
shape: (4,)
Series: 'date' [i8]
[
1
5
9
13
]
"""
def weekday(self) -> Series:
"""
Extract the week day from the underlying date representation.
Applies to Date and Datetime columns.
Returns the ISO weekday number where monday = 1 and sunday = 7
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import date
>>> s = pl.date_range(date(2001, 1, 1), date(2001, 1, 7), eager=True).alias(
... "date"
... )
>>> s.dt.weekday()
shape: (7,)
Series: 'date' [i8]
[
1
2
3
4
5
6
7
]
"""
def day(self) -> Series:
"""
Extract the day from the underlying date representation.
Applies to Date and Datetime columns.
Returns the day of month starting from 1.
The return value ranges from 1 to 31. (The last day of month differs by months.)
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import date
>>> s = pl.date_range(
... date(2001, 1, 1), date(2001, 1, 9), interval="2d", eager=True
... ).alias("date")
>>> s.dt.day()
shape: (5,)
Series: 'date' [i8]
[
1
3
5
7
9
]
"""
def ordinal_day(self) -> Series:
"""
Extract ordinal day from underlying date representation.
Applies to Date and Datetime columns.
Returns the day of year starting from 1.
The return value ranges from 1 to 366. (The last day of year differs by years.)
Returns
-------
Series
Series of data type :class:`Int16`.
Examples
--------
>>> from datetime import date
>>> s = pl.date_range(
... date(2001, 1, 1), date(2001, 3, 1), interval="1mo", eager=True
... ).alias("date")
>>> s.dt.ordinal_day()
shape: (3,)
Series: 'date' [i16]
[
1
32
60
]
"""
def time(self) -> Series:
"""
Extract (local) time.
Applies to Date/Datetime/Time columns.
Returns
-------
Series
Series of data type :class:`Time`.
Examples
--------
>>> from datetime import datetime
>>> ser = pl.Series([datetime(2021, 1, 2, 5)]).dt.replace_time_zone(
... "Asia/Kathmandu"
... )
>>> ser
shape: (1,)
Series: '' [datetime[μs, Asia/Kathmandu]]
[
2021-01-02 05:00:00 +0545
]
>>> ser.dt.time()
shape: (1,)
Series: '' [time]
[
05:00:00
]
"""
def date(self) -> Series:
"""
Extract (local) date.
Applies to Date/Datetime columns.
Returns
-------
Series
Series of data type :class:`Date`.
Examples
--------
>>> from datetime import datetime
>>> ser = pl.Series([datetime(2021, 1, 2, 5)]).dt.replace_time_zone(
... "Asia/Kathmandu"
... )
>>> ser
shape: (1,)
Series: '' [datetime[μs, Asia/Kathmandu]]
[
2021-01-02 05:00:00 +0545
]
>>> ser.dt.date()
shape: (1,)
Series: '' [date]
[
2021-01-02
]
"""
@deprecate_function("Use `dt.replace_time_zone(None)` instead.", version="0.20.4")
def datetime(self) -> Series:
"""
Extract (local) datetime.
.. deprecated:: 0.20.4
Use `dt.replace_time_zone(None)` instead.
Applies to Datetime columns.
Returns
-------
Series
Series of data type :class:`Datetime`.
Examples
--------
>>> from datetime import datetime
>>> ser = pl.Series([datetime(2021, 1, 2, 5)]).dt.replace_time_zone(
... "Asia/Kathmandu"
... )
>>> ser
shape: (1,)
Series: '' [datetime[μs, Asia/Kathmandu]]
[
2021-01-02 05:00:00 +0545
]
>>> ser.dt.datetime() # doctest: +SKIP
shape: (1,)
Series: '' [datetime[μs]]
[
2021-01-02 05:00:00
]
"""
def hour(self) -> Series:
"""
Extract the hour from the underlying DateTime representation.
Applies to Datetime columns.
Returns the hour number from 0 to 23.
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import datetime
>>> start = datetime(2001, 1, 1)
>>> stop = datetime(2001, 1, 1, 3)
>>> date = pl.datetime_range(start, stop, interval="1h", eager=True).alias(
... "datetime"
... )
>>> date
shape: (4,)
Series: 'datetime' [datetime[μs]]
[
2001-01-01 00:00:00
2001-01-01 01:00:00
2001-01-01 02:00:00
2001-01-01 03:00:00
]
>>> date.dt.hour()
shape: (4,)
Series: 'datetime' [i8]
[
0
1
2
3
]
"""
def minute(self) -> Series:
"""
Extract the minutes from the underlying DateTime representation.
Applies to Datetime columns.
Returns the minute number from 0 to 59.
Returns
-------
Series
Series of data type :class:`Int8`.
Examples
--------
>>> from datetime import datetime
>>> start = datetime(2001, 1, 1)
>>> stop = datetime(2001, 1, 1, 0, 4, 0)
>>> date = pl.datetime_range(start, stop, interval="2m", eager=True).alias(
... "datetime"
... )
>>> date
shape: (3,)
Series: 'datetime' [datetime[μs]]
[
2001-01-01 00:00:00
2001-01-01 00:02:00
2001-01-01 00:04:00
]
>>> date.dt.minute()
shape: (3,)
Series: 'datetime' [i8]
[
0
2
4
]
"""
def second(self, *, fractional: bool = False) -> Series:
"""
Extract seconds from underlying DateTime representation.
Applies to Datetime columns.
Returns the integer second number from 0 to 59, or a floating
point number from 0 < 60 if `fractional=True` that includes
any milli/micro/nanosecond component.
Parameters
----------
fractional
Whether to include the fractional component of the second.
Returns
-------
Series
Series of data type :class:`Int8` or :class:`Float64`.
Examples
--------
>>> from datetime import datetime
>>> s = pl.Series(
... "datetime",
... [
... datetime(2000, 1, 1, 0, 0, 0, 456789),
... datetime(2000, 1, 1, 0, 0, 3, 111110),
... datetime(2000, 1, 1, 0, 0, 5, 765431),
... ],
... )
>>> s.dt.second()
shape: (3,)
Series: 'datetime' [i8]
[
0
3
5
]
>>> s.dt.second(fractional=True)
shape: (3,)
Series: 'datetime' [f64]
[
0.456789
3.11111
5.765431
]
"""
def millisecond(self) -> Series:
"""
Extract the milliseconds from the underlying DateTime representation.
Applies to Datetime columns.
Returns
-------
Series
Series of data type :class:`Int32`.
Examples
--------
>>> from datetime import datetime
>>> start = datetime(2001, 1, 1)
>>> stop = datetime(2001, 1, 1, 0, 0, 4)
>>> s = pl.datetime_range(start, stop, interval="500ms", eager=True).alias(
... "datetime"
... )
>>> s.dt.millisecond()
shape: (9,)
Series: 'datetime' [i32]
[
0
500
0
500
0
500
0
500
0
]
"""
def microsecond(self) -> Series:
"""
Extract the microseconds from the underlying DateTime representation.
Applies to Datetime columns.
Returns
-------
Series
Series of data type :class:`Int32`.
Examples
--------
>>> from datetime import datetime
>>> start = datetime(2001, 1, 1)
>>> stop = datetime(2001, 1, 1, 0, 0, 4)
>>> date = pl.datetime_range(start, stop, interval="500ms", eager=True).alias(
... "datetime"
... )
>>> date
shape: (9,)
Series: 'datetime' [datetime[μs]]
[
2001-01-01 00:00:00
2001-01-01 00:00:00.500
2001-01-01 00:00:01
2001-01-01 00:00:01.500
2001-01-01 00:00:02
2001-01-01 00:00:02.500
2001-01-01 00:00:03
2001-01-01 00:00:03.500
2001-01-01 00:00:04
]
>>> date.dt.microsecond()
shape: (9,)
Series: 'datetime' [i32]
[
0
500000
0
500000
0
500000
0
500000
0
]
"""
def nanosecond(self) -> Series:
"""
Extract the nanoseconds from the underlying DateTime representation.
Applies to Datetime columns.
Returns
-------
Series
Series of data type :class:`Int32`.
Examples
--------
>>> from datetime import datetime
>>> start = datetime(2001, 1, 1)
>>> stop = datetime(2001, 1, 1, 0, 0, 4)
>>> date = pl.datetime_range(start, stop, interval="500ms", eager=True).alias(
... "datetime"
... )
>>> date
shape: (9,)
Series: 'datetime' [datetime[μs]]
[
2001-01-01 00:00:00