Part I: Final Project
The project delves into Citibike usage data to unearth patterns and behaviors among its users. It seeks to illustrate not just the logistics of bike-sharing but also its integration into the urban tapestry. The narrative is designed to resonate with city planners, potential users, and urban studies enthusiasts, offering a unique perspective on how a bike-sharing program molds and is shaped by the city’s rhythm.
Chapter 1: A City on Wheels
Visualization: Pie chart for rideable types and a counter for total rides.
Data Required: Count of different rideable types and total number of rides.
Chapter 2: Where Journeys Begin and End
Visualization: Top 10 list of stations, and a map highlighting these stations.
Data Required: Frequency counts for start and end stations.
Chapter 3: Riders of the City
Visualization: Bar graph showing the proportion of members vs. casual riders.
Data Required: Count of rides by member type (member vs. casual).
Chapter 4: The Length of the Ride
Visualization: Histogram or box plot showing the distribution of ride durations for both groups.
Data Required: Duration of each ride, classified by rider type.
Chapter 5: The Paths Taken
Visualization: A map with lines representing the most popular routes.
Data Required: Count of rides for each route (from start station to end station).
Chapter 6: Riding Through Time
Visualization: Heatmap or line graph showing ride frequency by time of day and day of the week.
Data Required: Ride counts are categorized by time of day and day of the week.
Chapter 7: The Geographic Tapestry
Visualization: Map with colored zones indicating different ride characteristics.
Data Required: Geographic coordinates of rides and their characteristics like duration or user type.
Conclusion: Be Part of the Movement
CTA: Encourage viewers to engage with Citi Bike – either as new riders or by being more conscious of their riding patterns to improve the service (e.g., using bikes from less frequented stations).
Visualization: An inspirational image showing a diverse group of people using Citi Bikes, symbolizing community and movement.
Data Source: The dataset used for this analysis is sourced from Citibike’s official website, specifically from their system data section which can be accessed at Citibike System Data. Citibike, as part of its commitment to transparency and community engagement, routinely publishes comprehensive data on bike trips taken using their service in New York City. This data is publicly available and can be used for various analyses and insights generation.
Dataset Content: The specific dataset analyzed here is the “JC-202310 Citibike Trip Data.” It contains detailed information about individual bike trips, including the ride ID, type of bike, start and end times, start and end locations (with latitude and longitude), and user type (member or casual). The data typically covers a range of dates, providing a rich source for understanding usage patterns over time.
Usage of Data:
1. Analyzing Commuting Patterns: The data is particularly useful for analyzing urban commuting patterns, understanding peak usage hours, and identifying the most frequented stations. This can inform city planning and transportation management.
2. User Behavior Insights: By examining trip durations and frequencies, insights can be drawn about user behavior, preferences, and tendencies, such as the preference for short-duration trips.
3. Service Improvement: For Citibike, this data is invaluable for operational improvements, such as optimizing bike distribution among stations, maintenance schedules, and service expansion.
Through careful analysis, this dataset not only serves the needs of urban planners and environmental advocates but also provides Citibike with actionable insights to enhance their service for a better user experience.
Method and Medium
The final project will be a digital storytelling piece using a platform like Shorthand. The narrative will revolve around understanding urban mobility through Citibike usage, aiming to appeal to a broad audience, including city planners, bike enthusiasts, and potential Citibike users. The story will:
2. Narrative Structure: Weave a compelling story about urban mobility, supported by data visualizations.
In summary, the project aims to tell a data-driven story about urban biking habits, highlighting patterns and preferences among Citibike users in a visually engaging and interactive way.