a Python toolbox loads 172 public time series datasets for machine/deep learning with a single line of code. Datasets from multiple domains including healthcare, financial, power, traffic, weather, and etc.
The raw data is in http://pems.dot.ca.gov/. The data in this repo is a collection of 48 months (2015-2016) hourly data from the California Department of Transportation. The data describes the road occupancy rates (between 0 and 1) measured by different sensors on San Francisco Bay area freeways.
2. Check open-source status
[X] The dataset implementation is publicly available
3. Provide useful information for the implementation
1. Dataset description
https://github.com/laiguokun/multivariate-time-series-data/tree/master?tab=readme-ov-file#traffic-usage
The raw data is in http://pems.dot.ca.gov/. The data in this repo is a collection of 48 months (2015-2016) hourly data from the California Department of Transportation. The data describes the road occupancy rates (between 0 and 1) measured by different sensors on San Francisco Bay area freeways.2. Check open-source status
3. Provide useful information for the implementation
https://pems.dot.ca.gov