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Other important factors are temperature, wind, and sunset.", "format": "arff", "uploader": "Dustin Carrion", "uploader_id": 30123, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-24 07:25:12", "update_comment": null, "last_update": "2022-03-24 07:25:12", "licence": "CC0: Public Domain", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102531\/dataset", "default_target_attribute": null, "row_id_attribute": null, "ignore_attribute": "\"id\"", "runs": 0, "suggest": { "input": [ "Uber-and-Lyft-Dataset-Boston-MA", "Uber vs Lyft This is a very beginner-friendly dataset. It does contain a lot of NA values. It is a good dataset if you want to use a Linear Regression Model to see the pattern between different predectors such as hour and price. A really amazing part of this dataset is that I have included the corresponding weather data for that hour with a short summary of the weather. Other important factors are temperature, wind, and sunset. 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