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Download README.md from OpenDataFoundation/opendata: direct link, hf CLI and curl.
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https://huggingface.co/datasets/OpenDataFoundation/opendata/resolve/main/README.md
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curl -L -o README.md https://huggingface.co/datasets/OpenDataFoundation/opendata/resolve/main/README.md
1.19 kB
| configs: | |
| - config_name: companies | |
| data_files: | |
| - split: train | |
| path: data/companies/parquet/*.parquet | |
| - config_name: locations | |
| data_files: | |
| - split: train | |
| path: data/locations/parquet/*.parquet | |
| - config_name: people | |
| data_files: | |
| - split: train | |
| path: data/people/parquet/*.parquet | |
| # OpenData Consortium | |
| Three open datasets exported from the OpenData Consortium data platform. | |
| | Config | Description | Primary format | | |
| |---|---|---| | |
| | `companies` | ~103M global companies with firmographic attributes | Parquet | | |
| | `locations` | ~273M business locations with address and geo data | Parquet | | |
| | `people` | ~101M business contacts linked to companies | Parquet | | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| companies = load_dataset("OpenDataFoundation/opendata", "companies") | |
| locations = load_dataset("OpenDataFoundation/opendata", "locations") | |
| people = load_dataset("OpenDataFoundation/opendata", "people") | |
| ``` | |
| ## Formats | |
| Each entity is available in three formats under `data/{entity}/{format}/`: | |
| - **parquet** — primary, gzip-compressed | |
| - **csv** — gzip-compressed, with header row | |
| - **json** — newline-delimited JSON, gzip-compressed | |