bikesharing
Purpose of the Analysis
The purpose of the Analysis is to present specific data visualization of different Bike Trip elements in order to prepare a proposal for a bike-sharing program in Des Moines. In order to complete this analysis, Python's Pandas library was used to create a datetime datatype which was then utilized in Tableau to generate a set of visualizations supporting the Des moines project for a bike-sharing program.
Results
In order to understand different components of the project, several visualizations are created to emphasize the relationship between different data elements. These include:
- The length of time that bikes are checked out for all riders and genders
- The number of bike trips for each hour of each day of the week
- The number of bike trips for each type of user and gender
- The peak hours for the month of August 2019
- The average trip duration
Checkout Times for Users
The data on the graph below indicates the checkout times for users for August 2019, during which bikes were more likely to be rented for a period ranging from 2 to 15 minutes.
Checkout Times for Users by Gender
The checkout times by gender was illustrated by graphing the trip duration by hour and by the gender of the riders. As shown below, male riders constituted a majority of bike riders and their checkout time period was estimated to be between 2 and 12 minutes. On the other hand, female riders checkout time was between 2 and 16 minutes while the unknown category of riders biked on average for 12 minutes.
Trips per Weekday Per Hour
The following graph shows that the busiest hours for bike trips are 8 am, 5 pm and 6 pm. Relatively, the busiest days are Saturday afternoons and Thursdays between 5 pm to 7 pm.
The Weekday Per Hour Trips by Gender shows that the most active hours for male and female riders remain between the range of 5 pm to 7 pm. Male riders are also more likely to rent bikes than female riders.
User Trips by Gender by Weekday
The graph below illustrates the usertype by gender and by weekday. The two types of users are Subscribers, which refers to annual Subscribers of the bike-sharing service, and Customers who are the short-term riders. As shown below, Subscribers represent the majority of riders for both the male and female categories, while there are more male than female riders.
Peak hours for August 2019
The Bar Chart below shows that the peak hours for riders during the month of August 2019 are 8 am, 5 pm and 6 pm.
Average trip duration
The following chart is an area chart which best represents the data for the Average Trip Duration. It shows that the later the birth year, the longer the ride duration will be.
Summary
As seen in the analysis, male riders and Subscribers constitute the majority of riders. In addition to the information provided above, a few additional visualizations could be considered in order to further develop the project's data visualization component:
- Graphing an itinerary of the most frequently used routes and elaborate the differences, if any, between male, female and unknown riders.
- Graphing the age demographic of male, female and unknown riders, wile taking into consideration if they belong to the customers and subscribers categories.
- Mapping the frequency, popularity and length of longer and shorter routes taken by the riders.
The link to the dashboard can be found below: