# Formatting multi-level variable width data for model

I would like to calculate a value based on the number of lines on outage at a given time.

An outage consists of the two endpoints and the voltage of the line:

outage = ["node1", "node2", "120"]


The historical values I have are based on per hour time stamps, so the format I believe I will need to feed the model is like so:

[timestamp, [outage1, outage2, etc...], value]


Do most machine learning libraries accept data in a variable width format like this? Alternatively, the only other thing I can think of is to have a super-wide data set and do a one hot encoding where each column is a node and its value is the voltage (scaled perhaps).

Example:

  Columns:
[timestamp, node1, node2, node3, etc..., value]
Values:
["1/1/2019 14:00", 120, 120, 0, etc..., 5]


There are thousands of nodes on this grid. What is the best approach for formatting this data in a way that most models will accept?