Datasets:
| #!/usr/bin/env python3 | |
| """Summarize exported reply features. Luke Steuber, 2026. MIT.""" | |
| from pathlib import Path | |
| import argparse | |
| import pandas as pd | |
| def main(): | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument( | |
| "--data-dir", | |
| type=Path, | |
| default=Path(__file__).resolve().parents[1] / "data", | |
| ) | |
| args = parser.parse_args() | |
| replies = pd.read_parquet(args.data_dir / "reply_features.parquet") | |
| by_post = replies.groupby("post_id").agg( | |
| captured_replies=("post_id", "size"), | |
| median_delay_hours=("delay_hours", "median"), | |
| replies_with_text=("has_captured_text", "sum"), | |
| ) | |
| topic_columns = [c for c in replies.columns if c.startswith("topic_")] | |
| rates = replies[topic_columns].mean().mul(1000).sort_values(ascending=False) | |
| print(by_post.to_string()) | |
| print("\nLiteral topic matches per 1,000 captured replies (overlapping patterns)") | |
| print(rates.to_string()) | |
| if __name__ == "__main__": | |
| main() | |