[mertcankaratass]

Closes #7

Summary

Adds a runnable quick start example to the README and an end-to-end interactive tutorial notebook in examples/quickstart.ipynb.

• README quick start: replaced the planned API note with a runnable inline DataFrame example showing fit_transform on train, transform on test, and get_feature_names_out(). The printed output matches code execution exactly.
• examples/quickstart.ipynb:
  • Generates a self-contained synthetic customer classification dataset (runs completely offline without downloads).
  • Demonstrates each block individually (MissingValueImputer, CategoricalEncoder, FeatureScaler), then composes them in Pipeline.
  • Shows feature names tracking after one-hot encoding with get_feature_names_out().
  • Integrates with scikit-learn via make_pipeline and cross_val_score(cv=5).
  • Explains and demonstrates data leakage prevention by comparing training center with test set statistics.
  • Executed and committed with outputs.
• pyproject.toml: added jupyter and nbconvert to dev extra.

Note: This branch includes PR #12 (CategoricalEncoder) so that the notebook and README run cleanly end-to-end. Once PR #12 is merged into main, this PR will only contain the documentation and notebook changes.

How was it tested

• pytest: 134 passed in 1.92s
• jupyter nbconvert --to notebook --execute --inplace examples/quickstart.ipynb: runs cleanly with exit code 0
• ruff check .: All checks passed!
• ruff format --check .: 15 files already formatted

Checklist

• ruff format . and ruff check . pass
• pytest passes
• New or changed blocks follow the block rules in CONTRIBUTING.md
• Block tests include a leakage test (statistics come from the training data only) and a run inside sklearn cross_val_score