Problem

There are memory issues with autocausality since the fitted estimator automatically stores the data after fitting. DoWhy or Scikit-Learn estimators don't do that and there is no immediate need for it.

Proposed changes

• Add option to remove data after fitting in fit method
• also removed initialisation of autocausality with data since it is never used. Suffices and would be consistent with DoWhy / Scikit-Learn to only insert data through fit method.

In the future, will consider moving train-test-split to CausalityDataset to always keep test_df available.

Types of changes

What types of changes does your code introduce to Auto-Causality?
Put an x in the boxes that apply

• Bugfix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Documentation Update (if none of the other choices apply)

Checklist

• I have read the CONTRIBUTING doc
• Description above provides context of the change
• I have added tests that prove my fix is effective or that my feature works
• Unit tests for changes (not needed for documentation changes)
• Bumping version in setup.py is an individual PR and not mixed with feature or bugfix PRs
• Commits follow "How to write a good git commit message"
• Relevant documentation is updated including usage instructions