polars.Expr.str.strptime#

Expr.str.strptime(
dtype: PolarsTemporalType,
format: str | None = None,
*,
strict: bool = True,
exact: bool = True,
cache: bool = True,
ambiguous: Ambiguous | Expr = 'raise',
) → Expr[source]#

Convert a String column into a Date/Datetime/Time column.

Parameters:
dtype

The data type to convert into. Can be either Date, Datetime, or Time.

format

Format to use for conversion. Refer to the chrono crate documentation for the full specification. Example: "%Y-%m-%d %H:%M:%S". If set to None (default), the format is inferred from the data.

strict

Raise an error if any conversion fails.

exact

Require an exact format match. If False, allow the format to match anywhere in the target string. Conversion to the Time type is always exact.

Note

Using exact=False introduces a performance penalty - cleaning your data beforehand will almost certainly be more performant.

cache

Use a cache of unique, converted dates to apply the datetime conversion.

ambiguous

Determine how to deal with ambiguous datetimes:

  • 'raise' (default): raise

  • 'earliest': use the earliest datetime

  • 'latest': use the latest datetime

  • 'null': set to null

Notes

When converting to a Datetime type, the time unit is inferred from the format string if given, eg: "%F %T%.3f" => Datetime("ms"). If no fractional second component is found, the default is "us".

Examples

Dealing with a consistent format:

>>> s = pl.Series(["2020-01-01 01:00Z", "2020-01-01 02:00Z"])
>>> s.str.strptime(pl.Datetime, "%Y-%m-%d %H:%M%#z")
shape: (2,)
Series: '' [datetime[μs, UTC]]
[
        2020-01-01 01:00:00 UTC
        2020-01-01 02:00:00 UTC
]

Dealing with different formats.

>>> s = pl.Series(
...     "date",
...     [
...         "2021-04-22",
...         "2022-01-04 00:00:00",
...         "01/31/22",
...         "Sun Jul  8 00:34:60 2001",
...     ],
... )
>>> s.to_frame().select(
...     pl.coalesce(
...         pl.col("date").str.strptime(pl.Date, "%F", strict=False),
...         pl.col("date").str.strptime(pl.Date, "%F %T", strict=False),
...         pl.col("date").str.strptime(pl.Date, "%D", strict=False),
...         pl.col("date").str.strptime(pl.Date, "%c", strict=False),
...     )
... ).to_series()
shape: (4,)
Series: 'date' [date]
[
        2021-04-22
        2022-01-04
        2022-01-31
        2001-07-08
]