After brainstorming and researching for a goal to guide our CodeJam endeavours, we saw that geospatial analysis can be used to help industries and people at a disadvantage, and we wanted to target another such group of people: taxi drivers. We wanted to help taxi drivers in Chicago optimize their day and their income by allowing them to target areas of high demand more efficiently.

What it does

Shows taxi drivers the areas of highest traffic and demand so that they can know where to be stationed in order to increase the efficiency of their work and their income

How we built it

We built it using the OSMnx library to create a map of the network of roads in Chicago and the Kmean clustering algorithm to show clusters of activity

Challenges we ran into

Readability and aesthetics of the map, setting map markers corresponding to cluster locations on the map, and setting up the OSMnx library

Accomplishments that we're proud of

Familiarizing ourselves with the OSMnx library and using different python libraries and their functionalities effectively

What we learned

The different functionalities python libraries can offer and the applications of geospatial analysis

What's next for TaxiTaxi

Being able to turn this into a web app using JavaScript to make it more interactive and aesthetically pleasing

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