Does ATM handle multiple rows of the same entity?

[RogerTangos]

Hey @micahjsmith , etc, I apologize if this is a bit vague. I figured it'd be better to ask about this in a public forum so that it was well documented.

Is ATM able to handle multiple rows of the same entity? Or do samples need to be flattened into a single row?

As an example use-case, a timeseries dataset might have single entities with multiple observations.

If ATM can handle this, it seems like the entity_id would be contained in an unnamed index column, as shown in the pitchfork_genres.csv example dataset. However, none of the example datasets have multiple rows of the same entity.

[micahjsmith]

Every row of the dataset is a unique entity to make predictions for. But this "entity" can in essence be a compound primary key of other logical entities.

For example, it is totally possible to have a dataset like

person_id	date	class
0	2018-01-01	red
0	2018-01-02	blue

so multiple predictions can be made for person 0.

[RogerTangos]

Thank you @micahjsmith !

Am I right in thinking that if I wanted to predict a single event using a time-series, then I'd want to add all of my observations into a single row, as such?

person_id	date1	data@date1	date2	data@date2	...	class
0	2018-01-01	0.0	2018-01-01	0.1	...	red

And a followup: Is there a way to exclude columns like person_id from the model? Otherwise, I should probably remove the index columns from the example datasets.

[micahjsmith]

Am I right in thinking that if I wanted to predict a single event using a time-series, then I'd want to add all of my observations into a single row, as such?

Yes

Is there a way to exclude columns like person_id from the model? Otherwise, I should probably remove the index columns from the example datasets.

No, currently. Data file is ultimately loaded via https://github.com/HDI-Project/ATM/blob/master/atm/model.py#L87. No custom options can be passed to read_csv, though it would be a nice feature to allow arbitrary read_csv kwargs in run.yaml config file.