add notebook to compare MCS datasets from daps and core processing #112
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crispy-wonton
commented
Jun 9, 2025
| raw_daps_df = pd.read_parquet(daps_epc_path) | ||
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| # %% | ||
| # Preprocess datasets to make them comparable |
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The processing below is exactly the same as for the MCS-EPC full dataset
crispy-wonton
commented
Jun 9, 2025
Comment on lines
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| # %% | ||
| # Compare with y-data profiling | ||
| core_report = ProfileReport(core_df, title=f"Core {dataset.upper()}", minimal=True) | ||
| daps_report = ProfileReport(daps_df, title=f"Daps {dataset.upper()}", minimal=True) | ||
| comparison_report = core_report.compare(daps_report) | ||
| comparison_report.to_file(f"{dataset}_comparison.html") |
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These rows are identical to lines 30-33.
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Fixes #111
Summary
Compare the MCS and MCS-EPC joined output files from the daps and core processing pipelines in a notebook to identify any differences.
New files:
analysis/compare_processing/compare_mcs_installations_processing.py- notebook to compare processing outputsPlease note: the code is very repetitive due to using a notebook layout so I have left comments on the file on github to show where code is repeated from a previous section to save you from reviewing the exact same code twice!
Instructions for reviewer:
To create the notebook, you can use the following lines of code
You can then run the notebook as normal from your chosen IDE.
Please pay special attention to:
Is there anything missing that you think would be good to investigate?
Checklist:
notebooks/pre-commitand addressed any issues not automatically fixeddevREADMEsoutput/reports/