| | import polars as pl |
| | from huggingface_hub import hf_hub_url, list_repo_files |
| | from tqdm import tqdm |
| |
|
| | file_names = pl.Series(list_repo_files("allenai/c4", repo_type="dataset")) |
| | |
| | news_files = file_names.filter( |
| | file_names.str.starts_with("realnewslike/") & file_names.str.ends_with(".json.gz"), |
| | ).str.strip_prefix("realnewslike/") |
| |
|
| | c4n_features = {"timestamp": pl.Datetime, "url": pl.String} |
| | aggregator = pl.DataFrame() |
| | for filename in tqdm(news_files): |
| | json_url = hf_hub_url( |
| | repo_id="allenai/c4", |
| | filename=filename, |
| | subfolder="realnewslike", |
| | repo_type="dataset", |
| | ) |
| | print(f"Processing {json_url}") |
| | df = pl.read_ndjson(json_url, schema=c4n_features).sort("timestamp") |
| | yearly = df.group_by(pl.col("timestamp").dt.year()).agg( |
| | pl.count("url").alias("count") |
| | ) |
| | y_pivot = pl.DataFrame({str(year): count for year, count in yearly.rows()}) |
| | aggregator = pl.concat([aggregator, y_pivot], how="diagonal").sum() |
| | print(aggregator) |
| |
|
