temporian.EventSet.map

map(
    func: MapFunction,
    output_dtypes: Optional[TargetDtypes] = None,
    receive_extras: bool = False,
) -> EventSetOrNode

Applies a function on each value of an EventSet's features.

The function receives the scalar value, and if receive_extras is True, also a MapExtras object containing information about the value's position in the EventSet. The MapExtras object should not be modified by the function, since it is shared across all calls.

If the output of the functon has a different dtype than the input, the output_dtypes argument must be specified.

This operator is slow. When possible, existing operators should be used.

A Temporian graph with a map operator is not serializable.

Usage example with lambda function

>>> a = tp.event_set(
...     timestamps=[0, 1, 2],
...     features={"value": [10, 20, 30]},
... )

>>> b = a.map(lambda v: v + 1)
>>> b
indexes: ...
    (3 events):
        timestamps: [0. 1. 2.]
        'value': [11 21 31]
...

Usage example with output_dtypes:

>>> a = tp.event_set(
...     timestamps=[0, 1, 2],
...     features={"a": [10, 20, 30], "b": ["100", "200", "300"]},
... )

>>> def f(value):
...     if value.dtype == np.int64:
...         return float(value) + 1
...     else:
...         return int(value) + 2

>>> b = a.map(f, output_dtypes={"a": float, "b": int})
>>> b
indexes: ...
    (3 events):
        timestamps: [0. 1. 2.]
        'a': [11. 21. 31.]
        'b': [102 202 302]
...

Usage example with MapExtras:

>>> a = tp.event_set(
...     timestamps=[0, 1, 2],
...     features={"value": [10, 20, 30]},
... )

>>> def f(value, extras):
...     return f"{extras.feature_name}-{extras.timestamp}-{value}"

>>> b = a.map(f, output_dtypes=str, receive_extras=True)
>>> b
indexes: ...
    (3 events):
        timestamps: [0. 1. 2.]
        'value': [b'value-0.0-10' b'value-1.0-20' b'value-2.0-30']
...

Parameters:

Name	Type	Description	Default
func	MapFunction	The function to apply on each value.	required
output_dtypes	Optional[TargetDtypes]	Expected dtypes of the output feature(s) after applying the function to them. If not provided, the output dtypes will be expected to be the same as the input ones. If a single dtype, all features will be expected to have that dtype. If a mapping, the keys can be either feature names or the input dtypes (and not both types mixed), and the values are the target dtypes for them. All dtypes must be Temporian types (see dtype.py).	None
receive_extras	bool	Whether the function should receive a MapExtras object as second argument.	False

Returns:

Type	Description
EventSetOrNode	EventSet with the function applied on each value.