bowdenk7/uberlens

Visualize Uber fare rates in your area!

UberLens - visualize Uber fare rates in your area

From an origin to a destination: Fares surrounding a certain location:

Running locally

Pre-reqs

• Python 2.7
• pip (comes with Python 2.7.9 and later)
• virtualenv - Helps with managing python dependencies

> pip install virtualenv

• Google developer account and an Google Maps API key
  • Visit https://developers.google.com/console and log in with a Google Account
  • Select one of your existing projects, or create a new project.
  • Enable the API(s) you want to use. The python client lib for Google maps that we use supports
    • Geocoding API (currently used)
    • Elevation API (currently used)
    • Directions API
    • Distance Matrix API
    • Geolocation API
    • Places API
    • Roads API
    • Time Zone API
  • Create an API key and copy it into a local file called APIKEYS.txt. This file is in .gitignore but make sure you never share this file.

Setup

• Create a new virtualenv. The below command will create a folder env that contains everything virtualenv needs to manage your dependencies.

> virtualenv env

• Activate the virtualenv. Note the different commands for windows and linux. Also if you didn't name your folder env as shown above you'll need to replace env below with your chosen folder name.

# on Windows
> env/Scripts/activate

# on unix
> source env/bin/activate

• Restore python package dependencies:

> pip install -r requirements.txt

Run

• The app is currently hard coded with values, but you can run it with:

> python main.py

Notes

Get data --> visualize data

Microsoft office locations:

• Redmond
• Bellevue
• Seattle

From each office, we want to visualize how Uber's fares change within a certain radius. Perhaps we'll see price spikes at points of interest (POIs)... Perhaps we'll see a nice gradient... It'd also be interesting to see how the fares change over time, if they change at all.

That said, here's the flow of information: Coordinate points of addresses -> Get fare estimate from origin to address -> visualize fares on a map. Here's our data sources:

• Addresses - From list of coordinates, remove those that don't correspond to a valid address.
• From origin to every lat lng pair, call Uber API to get a fare estimate.

Plot [lat, lng, fare] on a map.

Pretty straightforward!