Datasets:
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078b8d1 | 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 30 31 32 33 34 35 36 | """Minimal, runnable example: load and analyse the dataset straight from HF.
Requires: pandas, pyarrow
pip install pandas pyarrow
Run:
python examples/quickstart.py
"""
import pandas as pd
BASE = "hf://datasets/skyleee/diversa-biomedical-v1"
def main():
works = pd.read_parquet(
f"{BASE}/data/works.parquet",
columns=["work_id", "publication_year", "field_name", "cited_by_count",
"is_oa", "international_collaboration"],
)
print(f"works: {len(works):,}")
print(f"years: {works.publication_year.min()}-{works.publication_year.max()}")
print(f"open access share: {works.is_oa.mean():.1%}")
print(f"international collaboration rate: {works.international_collaboration.mean():.1%}")
print("\nworks per field:")
print(works.field_name.value_counts().head(10).to_string())
print("\nmost-cited topics (dimension table):")
topics = pd.read_parquet(f"{BASE}/data/topics.parquet",
columns=["topic_name", "works_count", "total_citations"])
print(topics.sort_values("total_citations", ascending=False).head(10).to_string(index=False))
if __name__ == "__main__":
main()
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