How does your dynamic inventory look like?

[muelleram]

We aim to make dynamic_characterization useful for everybody, regardless of their preferred LCA software.

As enthusiastic Brightway users, we have defined a data format like this:

date	amount	flow	activity
101	33	1	2
312	21	4	2

where date is a timestamp, e.g. a datetime-object, amount is the amount of the biosphere flow, flow is the flow id, e.g. a integer, and activity is the activity id, also an integer. Then, each row of this dataframe gets characterized by dynamic_characterization.characterize()

This format works well with Brightway, but we are curious about the needs of the wider community.

What does your dynamic inventory look like and what kind of challenges do you face during dynamic characterization that could be addressed in this package?

Please feel free to use this issue to share your dataformat, needs or any suggestions to make dynamic_characterization more useful to you.