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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 ...
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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 ...
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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. ...
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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
To summarize:
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 ...
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