To answer your question no.
The term "imbalance" usually refers to classification problems. For your case, i.e. a regression problem you can only look at the distribution of your target variable.
If by "balance" you mean them having a uniform distribution, you could argue that they are, if fact imbalanced. However, I'd argue that this is not the problem ...
You need to clean up the data. Load it into the Power Query editor.
Split the column with the variables by the delimiter ;
now you have a lot of individual columns, some have values, some are empty
select all columns except the newly split ones and use Unpivot > Unpivot Other Columns on the transform ribbon.
Now you have one row for each combination of ...
With more than two variables, you have a dimension problem. Here, with 3 variables and one output you would need a 4 dimensionnal graph, which is not possible unless you use some trick.
1. Reduce the dimension of your problem
Generally speaking, if you need to observe a problem for which the dimension is too big, you may want to reduce its dimension. ...
If we limit the question on comparing two graphs, I can propose a way based on adjacency matrices comparison. There is a sample notebook: graph_diff.ipynb
Having two graphs,
A B C D A B D E F
A 0 2 2 2 A 0 1 2 3 0
B 2 0 1 1 B 1 0 0 1 1
C 2 1 2 0 D 2 ...