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b282437 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | import pandas as pd
import os
catalog_path = "C:/Users/Swamy/OneDrive - Zafrens/Desktop/Z-Screen Deepdive/Shared_Source_Data_June2026/external_reference/catalog/external_reference_dataset_catalog.csv"
metadata_path = "C:/Users/Swamy/OneDrive - Zafrens/Desktop/Z-Screen Deepdive/Shared_Source_Data_June2026/external_reference/scperturb_downloads/scperturb_summary_metadata.csv"
catalog_df = pd.read_csv(catalog_path)
metadata_df = pd.read_csv(metadata_path)
new_rows = []
for _, row in metadata_df.iterrows():
new_rows.append({
"dataset_id": "scperturb_" + row["dataset_id"],
"source_alias": "scperturb_h5ad_downloads",
"dataset_type": "scPerturb Single-Cell H5AD",
"primary_metadata_path": "data/external_reference/scperturb_downloads/scperturb_summary_metadata.csv",
"primary_signature_path": "data/external_reference/scperturb_downloads/" + row["file"],
"metadata_rows": row["num_perturbations"],
"signature_rows": row["num_cells"],
"signature_columns": row["num_genes"],
"processing_summary": "Raw H5AD downloaded from scPerturb Zenodo. Native AnnData format, enabling direct comparison."
})
new_rows_df = pd.DataFrame(new_rows)
updated_catalog = pd.concat([catalog_df, new_rows_df], ignore_index=True)
updated_catalog.to_csv(catalog_path, index=False)
print("Successfully appended 10 datasets to external_reference_dataset_catalog.csv")
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