temporian.to_numpy

to_numpy(
    evset: EventSet,
    timestamp_to_datetime: bool = True,
    timestamps: bool = True,
) -> Dict[str, ndarray]

Converts an EventSet to a flattened dictionary with numpy arrays.

Usage example

>>> from datetime import datetime

>>> evset = tp.event_set(
...     timestamps=['2023-11-08T17:14:38', '2023-11-29T21:44:46'],
...     features={
...         "store": ['STORE_1', 'STORE_2'],
...         "revenue": [1571, 6101]
...     },
...     indexes=["store"],
... )

# Timestamps are exported as datetime64[s] if they were created as datetimes,
# otherwhise they are floats
>>> res = tp.to_numpy(evset)
>>> res
{'store': array([b'STORE_2', b'STORE_1'], dtype='|S7'), 'revenue': array([6101, 1571]),
'timestamp': array(['2023-11-29T21:44:46', '2023-11-08T17:14:38'], dtype='datetime64[s]')}

Parameters:

Name	Type	Description	Default
evset	EventSet	input event set.	required
timestamp_to_datetime	bool	If true, cast Temporian timestamps to datetime64 when is_unix_timestamp is set to True.	True
timestamps	bool	If true, the timestamps are included as a column.	True

Returns:

Type	Description
Dict[str, ndarray]	object with numpy arrays created from EventSet.