{ "data_id": "43563", "name": "Digital-currency---Time-series", "exact_name": "Digital-currency---Time-series", "version": 1, "version_label": "v1.0", "description": "Context\nHowdy folks! \nI have prepared a starter dataset for time series practice. This is my 1st upload. Any questions\/feedback are welcome. \nContent\n\nThe data was prepared using Alpha Vantage API\nThe data represents historical daily time series for a digital currency (BTC) traded on the Saudi market (SAR\/Sudi Riyal)\nPrices and volumes are quoted in both SAR USD.\nData date range: 2018-05-11 to 30.01.2021\n\nTask: Use the past to predict the future!\n\nCheck Tasks tab\n\nAcknowledgements\nSpecial thanks to all my instructors and friends at GA.", "format": "arff", "uploader": "Onur Yildirim", "uploader_id": 30126, "visibility": "public", "creator": null, "contributor": null, "date": "2022-03-23 13:51:32", "update_comment": null, "last_update": "2022-03-23 13:51:32", "licence": "CC0: Public Domain", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/22102388\/dataset", "default_target_attribute": null, "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Digital-currency---Time-series", "Context Howdy folks! I have prepared a starter dataset for time series practice. This is my 1st upload. Any questions\/feedback are welcome. Content The data was prepared using Alpha Vantage API The data represents historical daily time series for a digital currency (BTC) traded on the Saudi market (SAR\/Sudi Riyal) Prices and volumes are quoted in both SAR USD. Data date range: 2018-05-11 to 30.01.2021 Task: Use the past to predict the future! Check Tasks tab Acknowledgements Special thanks to al " ], "weight": 5 }, "qualities": { "NumberOfInstances": 1000, "NumberOfFeatures": 10, "NumberOfClasses": null, "NumberOfMissingValues": 0, "NumberOfInstancesWithMissingValues": 0, "NumberOfNumericFeatures": 9, "NumberOfSymbolicFeatures": 0, "Dimensionality": 0.01, "PercentageOfNumericFeatures": 90, "MajorityClassPercentage": null, "PercentageOfSymbolicFeatures": 0, "MajorityClassSize": null, "MinorityClassPercentage": null, "MinorityClassSize": null, "NumberOfBinaryFeatures": 0, "PercentageOfBinaryFeatures": 0, "PercentageOfInstancesWithMissingValues": 0, "AutoCorrelation": null, "PercentageOfMissingValues": 0 }, "tags": [ { "uploader": "38960", "tag": "Computer Systems" }, { "uploader": "38960", "tag": "Machine Learning" } ], "features": [ { "name": "Unnamed:_0", "index": "0", "type": "string", "distinct": "1000", "missing": "0" }, { "name": "open_SAR", "index": "1", "type": "numeric", "distinct": "1000", "missing": "0", "min": "12045", "max": "152217", "mean": "34825", "stdev": "21728" }, { "name": "open_USD", "index": "2", "type": "numeric", "distinct": "1000", "missing": "0", "min": "3212", "max": "40587", "mean": "9286", "stdev": "5794" }, { "name": "high_SAR", "index": "3", "type": "numeric", "distinct": "966", "missing": "0", "min": "12288", "max": "157329", "mean": "35790", "stdev": "22786" }, { "name": "high_USD", "index": "4", "type": "numeric", "distinct": "966", "missing": "0", "min": "3277", "max": "41950", "mean": "9543", "stdev": "6076" }, { "name": "low_SAR", "index": "5", "type": "numeric", "distinct": "970", "missing": "0", "min": "11837", "max": "145215", "mean": "33796", "stdev": "20565" }, { "name": "low_USD", "index": "6", "type": "numeric", "distinct": "970", "missing": "0", "min": "3156", "max": "38720", "mean": "9011", "stdev": "5484" }, { "name": "close_SAR", "index": "7", "type": "numeric", "distinct": "999", "missing": "0", "min": "12045", "max": "152202", "mean": "34917", "stdev": "21928" }, { "name": "close_USD", "index": "8", "type": "numeric", "distinct": "999", "missing": "0", "min": "3212", "max": "40583", "mean": "9310", "stdev": "5847" }, { "name": "volume", "index": "9", "type": "numeric", "distinct": "990", "missing": "0", "min": "5743", "max": "402201", "mean": "53100", "stdev": "35330" } ], "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 }