polars.time_ranges#
- polars.time_ranges(
 - start: time | IntoExprColumn | None = None,
 - end: time | IntoExprColumn | None = None,
 - interval: str | timedelta = '1h',
 - *,
 - closed: ClosedInterval = 'both',
 - eager: Literal[False] = False,
 - polars.time_ranges(
 - start: time | IntoExprColumn | None = None,
 - end: time | IntoExprColumn | None = None,
 - interval: str | timedelta = '1h',
 - *,
 - closed: ClosedInterval = 'both',
 - eager: Literal[True],
 - polars.time_ranges(
 - start: time | IntoExprColumn | None = None,
 - end: time | IntoExprColumn | None = None,
 - interval: str | timedelta = '1h',
 - *,
 - closed: ClosedInterval = 'both',
 - eager: bool,
 Create a column of time ranges.
- Parameters:
 - start
 Lower bound of the time range. If omitted, defaults to
time(0, 0, 0, 0).- end
 Upper bound of the time range. If omitted, defaults to
time(23, 59, 59, 999999).- interval
 Interval of the range periods, specified as a Python
timedeltaobject or using the Polars duration string language (see “Notes” section below).- closed{‘both’, ‘left’, ‘right’, ‘none’}
 Define which sides of the range are closed (inclusive).
- eager
 Evaluate immediately and return a
Series. If set toFalse(default), return an expression instead.
- Returns:
 - Expr or Series
 Column of data type
List(Time).
See also
time_rangeGenerate a single time range.
Notes
intervalis created according to the following string language:1ns (1 nanosecond)
1us (1 microsecond)
1ms (1 millisecond)
1s (1 second)
1m (1 minute)
1h (1 hour)
1d (1 calendar day)
1w (1 calendar week)
1mo (1 calendar month)
1q (1 calendar quarter)
1y (1 calendar year)
Or combine them: “3d12h4m25s” # 3 days, 12 hours, 4 minutes, and 25 seconds
By “calendar day”, we mean the corresponding time on the next day (which may not be 24 hours, due to daylight savings). Similarly for “calendar week”, “calendar month”, “calendar quarter”, and “calendar year”.
Examples
>>> from datetime import time >>> df = pl.DataFrame( ... { ... "start": [time(9, 0), time(10, 0)], ... "end": time(11, 0), ... } ... ) >>> df.with_columns(pl.time_ranges("start", "end")) shape: (2, 3) ┌──────────┬──────────┬────────────────────────────────┐ │ start ┆ end ┆ time_range │ │ --- ┆ --- ┆ --- │ │ time ┆ time ┆ list[time] │ ╞══════════╪══════════╪════════════════════════════════╡ │ 09:00:00 ┆ 11:00:00 ┆ [09:00:00, 10:00:00, 11:00:00] │ │ 10:00:00 ┆ 11:00:00 ┆ [10:00:00, 11:00:00] │ └──────────┴──────────┴────────────────────────────────┘