Datasets:
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1.55 kB
| license: mit | |
| task_categories: | |
| - time-series-forecasting | |
| tags: | |
| - tsfile | |
| - timeseries | |
| - time-series | |
| - format:tsfile | |
| pretty_name: github_top_developers | |
| size_categories: | |
| - 10K<n<100K | |
| # github_top_developers (TsFile) | |
| Apache TsFile version of [`diamond-in/github-top-developers`](https://huggingface.co/datasets/diamond-in/github-top-developers). | |
| - **Records:** 39,390 | |
| ## Schema (TsFile structure) | |
| - **name** (TAG) — device dimension(s). | |
| - **name** (FIELD). | |
| - **rank** (FIELD). | |
| ## Usage | |
| Install the Apache TsFile Python SDK (`pip install tsfile`) and read a converted file: | |
| ```python | |
| from pathlib import Path | |
| from tsfile import TsFileReader | |
| path = Path("github_top_developers.tsfile") | |
| with TsFileReader(str(path)) as reader: | |
| schemas = reader.get_all_table_schemas() | |
| print("tables:", list(schemas)) | |
| table_name = next(iter(schemas)) | |
| table = schemas[table_name] | |
| columns = [column.get_column_name() for column in table.get_columns()] | |
| print("columns:", columns) | |
| field_names = [ | |
| column.get_column_name() | |
| for column in table.get_columns() | |
| if column.get_column_name() not in {"Time", "time"} | |
| ] | |
| if field_names: | |
| with reader.query_table(table_name, field_names[:3], batch_size=1024) as result: | |
| batch = result.read_arrow_batch() | |
| if batch is not None: | |
| print(batch.to_pandas().head()) | |
| ``` | |
| ## Source & license | |
| - Original dataset: https://huggingface.co/datasets/diamond-in/github-top-developers | |
| - Author / publisher: diamond-in | |
| - License: mit | |