Parking-Statistics-in-North-America
OpenML dataset with id 43564
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Full work available at URL: https://api.openml.org/data/v1/download/22102389/Parking-Statistics-in-North-America.arff
Upload date: 23 March 2022
Copyright license: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Dataset Characteristics
Number of features: 31 (numeric: 19, symbolic: 0 and in total binary: 0 )
Number of instances: 4,750
Number of instances with missing values: 1,002
Number of missing values: 1,002
ABOUT This dataset identifies areas within a city where drivers are experiencing difficulty searching for parking. Cities can use this data to identify problem areas, adjust signage, and more. Only cities with a population of more than 100,000 are included. Data Some variables to highlight:
AvgTimeToPark: The average time taken to search for parking (in minutes) AvgTimeToParkRatio: The ratio between the average time taken to search for parking and of those not searching for parking in the current geohash TotalSearching: The number of drivers searching for parking PercentSearching: The percentage of drivers that were searching for parking AvgUniqueGeohashes: The average number of unique geohashes at the 7 character level (including neighbouring and parking geohashes) that were driven in among vehicles that searched for parking AvgTotalGeohashes: The average number of all geohashes at the 7 character level (including neighbouring and parking geohashes) that were driven in among vehicles that searched for parking CirclingDistribution: JSON object representing the neighbouring geohashes at the 7 character level whereby vehicles searching for parking tend to spend their time. Each geohash will have the average percentage of time spent in that geohash prior to parking. HourlyDistribution: JSON object representing the average prevalence of searching for parking by hour of day ( distribution based on number of vehicles experiencing parking problems) SearchingByHour: JSON object representing the average percentage of vehicles searching for parking within the hour PercentCar: Percentage of vehicles with parking issues that were cars PercentMPV: Percentage of vehicles with parking issues that were multi purpose vehicles PercentLDT: Percentage of vehicles with parking issues that were light duty trucks PercentMDT: Percentage of vehicles with parking issues that were medium duty trucks PercentHDT: Percentage of vehicles with parking issues that were heavy duty trucks PercentOther: Percentage of vehicles with parking issues that were unknown classification
Content This dataset is aggregated over the previous 6 months and is updated monthly. This data is publicly available from Geotab (geotab.com). Inspiration As some inspiration, here are some questions:
Which cities are the hardest to find parking?
By joining population data externally, can you determine a relationship between a region's population and the time that it takes to find parking?
Similarly, by finding external data, is there a correlation between GDP and parking times? What about average household income?
This page was built for dataset: Parking-Statistics-in-North-America
