# How to train a model on a data where there are multiple data inside a data point?

I'm trying to do prediction on capacity column, however each data point consist of more data.

Each data point represent a cycle data. Each cycle has a capacity. Each cycle runs for some time duration, and in that duration some data is collected over which capacity is dependant

I tried exploding the dataset and copying the capacity values to each row, but that shouldn't be the case because each row will get different capacity predicted. Is there a way to train such kind of dataset?

• Question: are the lists in the columns of equal length? Why don‘t you simply make $x$ columns out of a (now) single column? – Peter Aug 1 '19 at 18:32
• No. They are not equal columns – Bhaskar Dhariyal Aug 1 '19 at 18:35
• is there a logical structure you can use? You need to have the same thing in one column anyway – Peter Aug 1 '19 at 18:36