top of page
Business Meeting

NEW York Citi Bike

Citi bike is a bike-sharing system in New York City. Operated by Motivate, a subsidiary of Lyft, Citi Bike provides a convenient and affordable way for people to rent bicycles for short trips around the city. My job is to increase their profits and show them how and where to make it better.

Data

  • Data set downloaded from kaggle.com

  • Open source and trustworthy

  • Covers all bike rentals for the month of September in 2013

Skills

  • Exploratory analysis

  • Supervised machine learning: Regression

  • Advanced analytics

  • Time series analysis

Project/Tools

Key Analysis

Busiest Bike Pick-up Stations

  • Zip Code 10019, Manhattan, is the busiest station for the company.

  • Followed by 10003, 10014, 10011, all different portions of Manhattan.

  • The rest of the company’s stations are spread out over other portions of Manhattan, Brooklyn, part of Queens and a small portion of The Bronx.

Picture 1.png

Key Analysis

User Age

Most users were born between 1974 – 1979. That will make them 39 – 43 years old.

Picture 1.png
Busiest Hours

The busiest times are 16:00 – 17:00, followed by 08:00 – 09:00 in the morning. These are most likely the times people go to work and back home.

Picture 1.png
Frequency of Monthly Trips

There was a steep increase of rides over the first few days and then it fluctuated the rest of the month.

Picture 1.png
Time Series

The level and trend look different, meaning that I worked with unsmoothed data. The trend gradually goes upwards, telling me that the amount of rides are increasing during the month. I can see seasonal fluctuations, meaning that some days were busier than other days during the month.

Picture 1.png

Recommendations

Picture 1.png

  • Consider stocking stocking more bikes at the busiest stations.

  • The areas that Citi Bike covers, are not that much. Consider expanding to new areas.

  • Early mornings and late afternoons are the busiest. Citi Bike should offer some incentives to get more people on the bikes during the day and at night.

  • Most users are aged between 39 – 43 years. Offer some incentives to the other age groups to get them on the bikes.

bottom of page