{ "data_id": "43735", "name": "NYC-Hourly-Temperature", "exact_name": "NYC-Hourly-Temperature", "version": 1, "version_label": "v1.0", "description": "Context\nHourly weather data for New York City. Extracted from online web sources. The following data set is cleaned for the purpose for NYC Taxi ETA calculation.\nContent\nWe have features such as Date, Time, temperature (F), Dew Point (F), Humidity, Wind Speed (MPH), Condition.\nAcknowledgements\nThe cleaned version is user owned. Used in past research for weather data analysis in Boston. Performed the similar calculation to extract the dataset.\nInspiration\nThe hourly dataset is cleaned with no missing values. Along with temperature the dataset also consists of features like Humidity and Condition such as snow, rain etc.", "format": "arff", "uploader": "Dustin Carrion", "uploader_id": 30123, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-24 07:44:02", "update_comment": null, "last_update": "2022-03-24 07:44:02", "licence": "CC0: Public Domain", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102560\/dataset", "default_target_attribute": null, "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "NYC-Hourly-Temperature", "Context Hourly weather data for New York City. Extracted from online web sources. The following data set is cleaned for the purpose for NYC Taxi ETA calculation. Content We have features such as Date, Time, temperature (F), Dew Point (F), Humidity, Wind Speed (MPH), Condition. Acknowledgements The cleaned version is user owned. Used in past research for weather data analysis in Boston. Performed the similar calculation to extract the dataset. Inspiration The hourly dataset is cleaned with no mis " ], "weight": 5 }, "qualities": { "NumberOfInstances": 5141, "NumberOfFeatures": 7, "NumberOfClasses": null, "NumberOfMissingValues": 4, "NumberOfInstancesWithMissingValues": 4, "NumberOfNumericFeatures": 3, "NumberOfSymbolicFeatures": 0, "Dimensionality": 0.0013616028010114763, "PercentageOfNumericFeatures": 42.857142857142854, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0.07780587434351294, "AutoCorrelation": null, "PercentageOfMissingValues": 0.011115124906216134 }, "tags": [ { "uploader": "38960", "tag": "Chemistry" } ], "features": [ { "name": "date", "index": "0", "type": "string", "distinct": "183", "missing": "0" }, { "name": "TimeEST", "index": "1", "type": "string", "distinct": "682", "missing": "0" }, { "name": "TemperatureF", "index": "2", "type": "numeric", "distinct": "130", "missing": "0", "min": "-9999", "max": "90", "mean": "43", "stdev": "281" }, { "name": "Dew_PointF", "index": "3", "type": "numeric", "distinct": "133", "missing": "0", "min": "-9999", "max": "70", "mean": "27", "stdev": "280" }, { "name": "Humidity", "index": "4", "type": "numeric", "distinct": "88", "missing": "4", "min": "9", "max": "100", "mean": "58", "stdev": "21" }, { "name": "Wind_SpeedMPH", "index": "5", "type": "string", "distinct": "25", "missing": "0" }, { "name": "Conditions", "index": "6", "type": "string", "distinct": "15", "missing": "0" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 0, "total_downloads": 0, "reach": 0, "reuse": 0, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 0 }