Divvy is a bike-sharing system in Chicago, owned by the Chicago Department of Transportation (CDOT). It was launched on June 28, 2013, and later expanded north to Evanston on June 27, 2016. Since 2019, Divvy has been operated by Lyft. Divvy is North America’s largest bike-share system by service area. Divvy is considered one of the primary bike-share system in Chicago, with over 400,000 new riders and 5.5 million rides taken in 2021. Divvy has two primary group users, which are annual membership riders and casual riders. One of Divvy’s goals is to increase the number of annual membership riders. This project will focus on in-depth analysis of Divvy’s rider behavior and how external factors impact its ridership.
Divvy as of September 2024 has 1,014 stations in total.
The goal of this project is to use Tableau to visualize the usage patterns of Divvy bikes in Chicago in 2019. By analyzing the trip data provided, we can gain insights into when, where, and how bikes are being used.
The data provided contains information on each trip taken on a Divvy bike in 2019, including the trip start and end time, the starting and ending station, and the rider demographics. The data has been pre-processed to exclude trips without a start or end date.
• Trip duration: Analyze the distribution of trip durations to determine the average and median trip lengths.
• Station usage: Determine the most popular starting and ending stations by analyzing the number of trips originating or terminating at each station.
• Time of day: Determine the busiest times of day by analyzing the number of trips starting or ending at different times.
• User type: Compare the usage patterns of Customers and Subscribers to determine the difference in their usage patterns.
• Gender and age: Analyze the gender and age of Subscribers to determine any demographic trends in bike usage.
Tableau will be used to create a series of interactive dashboards to visualize the data. Dashboards will include:
• Map of Chicago with starting and ending stations highlighted
• Histogram of trip duration
• Bar charts showing the number of trips starting or ending at each station
• Line charts showing the number of trips starting or ending at different times of day
• Bar charts comparing the usage patterns of Customers and Subscribers
• Bar charts showing the gender and age distribution of Subscribers.
- Trip data from the Divvy: https://divvy-tripdata.s3.amazonaws.com/index.html
- Station data from Chicago Data Portal: https://data.cityofchicago.org/Transportation/Divvy-Bicycle-Stations/bbyy-e7gq/data
- Weather data from National Weather Service: https://www.weather.gov/wrh/climate?wfo=lot
- Population data from Chicago Data Portal: https://data.cityofchicago.org/Health-Human-Services/Chicago-Population-Counts/85cm-7uqa
By using Tableau to analyze the Divvy bike trip data, we can gain valuable insights into how bikes are being used in Chicago. This information can be useful in planning future bike infrastructure and promoting sustainable transportation options. The interactive dashboards created will allow users to easily explore the data and uncover patterns and trends in bike usage.