Published July 22, 2021
| Version 1
Dataset
Open
Rideshare Dataset with Missing Values
- 1. PhD Student at Monash University
- 2. Lecturer at Monash University
- 3. Professor at Monash University
- 4. Lecturer at University of Sydney
Description
This dataset contains various hourly time series representations of attributes related to Uber and Lyft rideshare services for various locations in New York between 26/11/2018 and 18/12/2018.
For a given starting location, provider and service, the following types are represented: 'price_min', 'price_mean', 'price_max', 'distance_min', 'distance_mean', 'distance_max', 'surge_min', 'surge_mean', 'surge_max', 'api_calls', 'temp', 'rain', 'humidity', 'clouds' and 'wind'.
Files
rideshare_dataset_with_missing_values.zip
Files
(1.0 MB)
| Name | Size | Download all |
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md5:b5faa7112787bb6d42e5de56462de7c7
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1.0 MB | Preview Download |
Additional details
Related works
- Cites
- Dataset: https://www.kaggle.com/ravi72munde/uber-lyft-cab-prices (URL)
- Dataset: https://github.com/ravi72munde/scala-spark-cab-rides-predictions (URL)
References
- RaviMunde, 2019. Uber & lyft cab prices. URL https://www.kaggle.com/ravi72munde/uber-lyft-cab-prices
- ravi72munde, 2018. scala-spark-cab-rides-predictions. URL https://github.com/ravi72munde/scala-spark-cab-rides-predictions