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README.md

Hotspots by Metermaid

Find parking hotspots in columbus.

Use Case

https://www.smartcolumbusos.com/data-stories/parking-tickets-piling-up-use-data-to-determine-why

Tech Stack

  1. Python
  2. Bokeh - Interactive visualization library https://bokeh.pydata.org/en/latest/
  3. Litespeed (web-server) - https://www.litespeedtech.com/products/litespeed-web-server
  4. Pandas - Data analysis library https://pandas.pydata.org/
  5. PyCharm SE - IDE
  6. Google maps platform - key registration

Installation

Running the application

  1. Clone repo to your local https://github.com/allparks/metermaid.git
  2. Install lite-server 1. sudo npm install -g lite-server
  3. In terminal navigate to '/metermaid/parkingApp' dir
  4. type lite-server to start the server and load the app.

Data Used

https://www.smartcolumbusos.com/data

  1. Mapping meter count = Parking Meters + Parking transaction data (2015-2017)
    1. Parking Meters -
      1. Longitude x/ Latitude y/
    2. Parking transaction data (2015-2017) -
      1. Longitude and latitude
      2. count (meter ids)
      3. meter_id pole
  2. Geotab data (Searching For Parking) - How many people are trying to park with different time frames
    1. sum (Avg. time to park searching)
    2. Avg (Total searching )
    3. Parking geohash
    4. Distinct value Longitude
    5. Distinct value Latitude
    6. location and hourly, avg park time
  3. Violations (Columbus City Parking Violations and Ticket Status 2013-2018) + Parking meters
    1. inner join (meter id)
    2. Longitude / Latitude
    3. count (ticket_id)
  4. Points of interests
    1. POI Type (edited)

Team

Presentation

Finding Parking Hotspots

Screen Shots

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