temporian.from_polars #

from_polars(
    df: polars.DataFrame,
    indexes: Optional[List[str]] = None,
    timestamps: str = "timestamp",
    name: Optional[str] = None,
    same_sampling_as: Optional[EventSet] = None,
    allow_copy: bool = True,
) -> EventSet

Converts a Polars DataFrame into an EventSet.

See tp.event_set() for the list of supported timestamp and feature types.

The allow_copy parameter is passed directly to Polars' to_numpy method. If set to False, the conversion process may fail if Polars is unable to perform a zero-copy conversion.Users are encouraged to refer to Polars documentation on to_numpy for detailed information on when a non-zero-copy conversion might be required.

Note

The function attempts to minimize data copying but will copy if required for compatibility.

Usage example

>>> import polars as pl
>>> df = pl.DataFrame(
...       {
...            "product_id": [666964, 666964, 574016, 574016],
...            "timestamp": [1.0, 2.0, 3.0, 4.0],
...            "costs": [740.0, 508.0, 573.0, None],
...        }
...    )
>>> evset = tp.from_polars(df, indexes=["product_id"])

>>> df1 = pl.DataFrame(
...        {
...            "timestamp": [1, 2, 3, 4],
...            "id": [1, 2, 3, None],
...            "category": [10, 20, 30, 40]
...        }
...    )

# allow_copy=False will result in zero_copy error for the below event set.
>>> evset1 = tp.from_polars(df1, indexes=["category"], allow_copy=True)

Parameters:

Name	Type	Description	Default
`df`	`DataFrame`	A non indexed Polars dataframe.	required
`indexes`	`Optional[List[str]]`	Names of the columns to use as indexes. If empty (default), the data is not indexed. Only integer and string columns can be used as indexes.	`None`
`timestamps`	`str`	Name of the column containing the timestamps. See `tp.event_set()` for the list of supported timestamp types.	`'timestamp'`
`name`	`Optional[str]`	Optional name of the EventSet. Used for debugging, and graph serialization.	`None`
`same_sampling_as`	`Optional[EventSet]`	If set, the new EventSet is checked and tagged as having the same sampling as `same_sampling_as`. Some operators, such as `EventSet.filter()`, require their inputs to have the same sampling.	`None`
`allow_copy`	`bool`	Allow memory to be copied to perform the conversion. If set to False, causes conversions that are not zero-copy to fail.	`True`

Returns: An EventSet.