temporian.event_set #

event_set(
    timestamps: DataArray,
    features: Optional[Dict[str, DataArray]] = None,
    indexes: Optional[List[str]] = None,
    name: Optional[str] = None,
    is_unix_timestamp: Optional[bool] = None,
    same_sampling_as: Optional[EventSet] = None,
) -> EventSet

Creates an EventSet from arrays (lists, NumPy arrays, Pandas Series.)

Usage examples:

```python
>>> # Creates an EventSet with 4 timestamps and 3 features.
>>> evset = tp.event_set(
...     timestamps=[1, 2, 3, 4],
...     features={
...         "feature_1": [0.5, 0.6, np.nan, 0.9],
...         "feature_2": ["red", "blue", "red", "blue"],
...         "feature_3": [10, -1, 5, 5],
...     },
... )

>>> # Creates an EventSet with an index.
>>> evset = tp.event_set(
...     timestamps=[1, 2, 3, 4],
...     features={
...         "feature_1": [0.5, 0.6, np.nan, 0.9],
...         "feature_2": ["red", "blue", "red", "blue"],
...     },
...     indexes=["feature_2"],
... )

>>> # Create an EventSet with datetimes.
>>> from datetime import datetime
>>> evset = tp.event_set(
...     timestamps=[datetime(2015, 1, 1), datetime(2015, 1, 2)],
...     features={
...         "feature_1": [0.5, 0.6],
...         "feature_2": ["red", "blue"],
...     },
...     indexes=["feature_2"],
... )

```

Supported values for timestamps:

List of int, float, str, bytes and datetime.
Numpy arrays of int{32, 64}, float{32, 64}, str_, string_ / bytes_, Numpy datetime64, and object containing "str".
Pandas series of int{32, 64}, float{32, 64}, Pandas Timestamp.

String timestamps are interpreted as ISO 8601 datetime.

Supported values for features:

List of int, float, str, bytes, bool, and datetime.
Numpy arrays of int{32, 64}, float{32, 64}, str_, string_ / bytes_, Numpy datetime64, or object containing "str".
Pandas series of int{32, 64}, float{32, 64}, Pandas Timestamp.

Date / datetime features are converted to int64 unix times. NaN for float-like features are interpreted as missing values.

Parameters:

Name	Type	Description	Default
`timestamps`	`DataArray`	Array of timestamps values.	required
`features`	`Optional[Dict[str, DataArray]]`	Dictionary of feature names to feature values. Feature and timestamp arrays must be of the same length.	`None`
`indexes`	`Optional[List[str]]`	Names of the features to use as indexes. If empty (default), the data is not indexed. Only integer and string features can be used as indexes.	`None`
`name`	`Optional[str]`	Optional name of the EventSet. Used for debugging, and graph serialization.	`None`
`is_unix_timestamp`	`Optional[bool]`	Whether the timestamps correspond to unix time. Unix times are required for calendar operators. If `None` (default), timestamps are interpreted as unix times if the `timestamps` argument is an array of date or date-like object.	`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`

Returns:

Type	Description
`EventSet`	An EventSet.