polars.date_range#

Create a range of type Datetime (or Date).

Parameters:

low: Lower bound of the date range, given as a date, datetime, Expr, or column name.
high: Upper bound of the date range, given as a date, datetime, Expr, or column name.
interval: Interval periods. It can be a python timedelta object, like timedelta(days=10), or a polars duration string, such as 3d12h4m25s representing 3 days, 12 hours, 4 minutes, and 25 seconds.
lazy:: Return an expression.
closed{‘both’, ‘left’, ‘right’, ‘none’}: Define whether the temporal window interval is closed or not.
name: Name of the output Series.
time_unit{None, ‘ns’, ‘us’, ‘ms’}: Set the time unit.
time_zone:: Optional timezone

Returns:

A Series of type Datetime or Date.

Notes

If both low and high are passed as date types (not datetime), and the interval granularity is no finer than 1d, the returned range is also of type date. All other permutations return a datetime Series.

Examples

Using polars duration string to specify the interval:

>>> from datetime import date
>>> pl.date_range(date(2022, 1, 1), date(2022, 3, 1), "1mo", name="dtrange")
shape: (3,)
Series: 'dtrange' [date]
[
    2022-01-01
    2022-02-01
    2022-03-01
]

Using timedelta object to specify the interval:

>>> from datetime import datetime, timedelta
>>> pl.date_range(
...     datetime(1985, 1, 1),
...     datetime(1985, 1, 10),
...     timedelta(days=1, hours=12),
...     time_unit="ms",
... )
shape: (7,)
Series: '' [datetime[ms]]
[
    1985-01-01 00:00:00
    1985-01-02 12:00:00
    1985-01-04 00:00:00
    1985-01-05 12:00:00
    1985-01-07 00:00:00
    1985-01-08 12:00:00
    1985-01-10 00:00:00
]

Specify a time zone

>>> pl.date_range(
...     datetime(2022, 1, 1),
...     datetime(2022, 3, 1),
...     "1mo",
...     time_zone="America/New_York",
... )
shape: (3,)
Series: '' [datetime[μs, America/New_York]]
[
    2022-01-01 00:00:00 EST
    2022-02-01 00:00:00 EST
    2022-03-01 00:00:00 EST
]