B-Cycle Kiosk Addition through KMeans

Inspiration

We wanted to improve the efficiency of B-Cycle

What it does

We recommended 6 kiosks to alleviate high traffic bike paths.

How we built it

We ran a K-means clustering algorithm on the bike return location data

Challenges we ran into

Getting the points to show on our map once they were found

Accomplishments that we're proud of

Getting recommendations for new kiosks that made practical sense

What we learned

B-Cycle kiosks are not created equally when it comes to bike traffic

What's next for B-Cycle Kiosk Reduction through KMeans

Finding non-Austin locations to alleviate high-traffic bike locations

Built With

• folium
• python
• scikit-learn