Research Question
How do lifestyle factors, such as proximity to key locations (e.g., home, workplace, social hubs), and seasonal/time variations influence both the usage patterns and the subsequent cost-effectiveness of Citi Bike as a transportation choice?
This question is important because it delves into the intersection of personal lifestyle choices, urban mobility, and financial decision-making. Understanding how factors like proximity to important destinations impact both the frequency and timing of bike rides, as well as the associated expenses, can provide valuable insights for urban planners, policymakers, and individuals seeking to optimize their transportation choices. The question draws inspiration from the personal data retrieved from my Citi Bike account, which helped me understand the intimate connection between my biking habits, biking costs, and personal geography.
Methodology and Results
I created the dataset by manually logging every ride from Jan 2022 until Mar 2024 from my Citi Bike account. The information logged includes the date, price, start time, end time, start location, end location, bike code, form of payment, and type of bike for every ride. Embarking on 183 bike rides spanning from Jan 2022 to March 2024, I clocked 33.1 hours of pedal-powered adventures across the bustling streets of NYC. But it’s not just about the numbers; it’s about the experience and the story each ride tells.
The journey begins with a bar graph outlining my expenses over the years. This graph helps break down how much I have spent on my Citi Bike usage since Jan 2022, highlighting how the annual membership and preference for electric bikes primarily drive the cost. Besides this, one thing remains clear: Citi Bike has proven to be a cost-effective transportation choice, aligning perfectly with my goal of saving money.
As I delve deeper into the patterns of my bike usage, I use two bar graphs depicting minutes biked by the hour of the day and by month to effectively reveal intriguing insights into my biking habits. Night and evening rides dominate my schedule, painting a picture of a city illuminated by streetlights and bustling with nocturnal energy. With the shifting seasons, my reliance on biking peaks during the warmer months, a testament to my embrace of summer adventures.
Yet, it’s the maps showcasing the top 10 stations where my rides begin and end that truly bring my story to life. Each station represents a waypoint in my journey, a marker of the places and people that define my daily existence. From the familiarity of home to the camaraderie of my local barbershop, the sweat-soaked hours at the gym to the camaraderie of my workplace, and the warmth of my closest friends’ homes, my biking routes trace the contours of my life, weaving together a tapestry of personal connections and urban exploration.
In the end, my biking journey truly highlights the personal and meaningful aspects of my Citi Bike adventure. It’s a journey fueled not just by pedal power but by a sense of connection to the vibrant rhythm of city life.
Next Steps
To enhance this project further, several avenues could be explored. In the immediate future, I could focus on refining the data analysis techniques to uncover deeper insights into my biking patterns and expenses. This could involve conducting more detailed analyses, such as segmentation of biking routes based on distance or duration, to identify trends and patterns that may not be immediately apparent. Additionally, integrating demographic or contextual data, such as weather conditions, could provide further context to my biking behavior and help refine the analysis.
Furthermore, incorporating predictive modeling techniques could allow me to forecast future biking patterns and expenses based on historical data, enabling me to better plan and optimize my transportation choices. Additionally, exploring the potential integration of real-time data feeds from Citi Bike or other sources could provide more up-to-date insights and enable proactive decision-making.
