The Ford GoBike System Data is a dataset that includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area. The dataset provides valuable insights into the usage patterns, trip durations, and user characteristics of the bike-sharing system.
Throughout my exploration of the Ford GoBike System dataset, I made several key findings:
User Types: As I analyzed the dataset, I discovered that the majority of users were subscribers, indicating a strong base of regular users who use the bike-sharing system more frequently. Customers, on the other hand, represented a smaller portion of the user base, suggesting that they may be more casual or occasional users of the system.
Ride Durations: I found interesting patterns in ride durations. Subscribers generally had shorter ride durations compared to customers, which aligns with the assumption that subscribers might use the system more frequently for shorter trips. Conversely, customers had longer and more variable ride durations, indicating different usage patterns, potentially for leisure or recreational purposes.
Gender Distribution: Analyzing the dataset, I observed a gender imbalance in the bike-sharing system. There were significantly more male users compared to female and other genders. This gender disparity highlights potential areas for improvement to encourage greater diversity and inclusivity within the bike-sharing community.
Popular End Stations: By exploring the data, I identified the top 10 popular end stations in the bike-sharing system. These stations, such as "San Francisco Caltrain Station 2 (Townsend St at 4th St)" and "Market St at 10th St," exhibited high usage and demand, serving as popular destinations for bike rides.
From my exploration, I have selected the following visualizations as the main threads to present:
-
Number of Rides by User Types: This bar plot will showcase the difference in the number of rides across different user types, highlighting the strong presence of subscribers in the bike-sharing system.
-
Top 10 End Stations: I will present a bar plot displaying the top 10 end stations to illustrate the popularity of these destinations among users.
-
Gender Distribution: The count plot depicting the distribution of member genders will provide insights into the gender imbalance within the bike-sharing system.
-
Distribution of Member Birth Years: The histogram showing the distribution of member birth years will offer an understanding of the age demographics of users.
-
Start Stations and User Types: The stacked bar plot visualizing the relationship between the top 10 start stations and user types will demonstrate the dominance of subscribers in popular start stations.
-
Ride Duration by Day of the Week and User Type: The box plot displaying the ride duration variation across different days of the week and user types will highlight the influence of these factors on ride durations.
-
Ride Duration by User Type and Member Gender: The heatmap visualization will showcase the variation in ride duration across different user types and member genders.
-
Ride Duration by User Type and Bike-Sharing Behavior: The box plot matrix will present the relationship between ride duration, user type, member gender, and bike-sharing behavior, revealing interesting interactions between these variables.