Analysis of Citi Bike Data: Understanding Usage Patterns and User Demographics

Introduction

This analysis delves into the usage patterns and user demographics of Citi Bike, a bike-sharing system in New Jersey, based on the available data from 2021. By examining key insights from the dataset, we aim to gain a deeper understanding of the popular starting stations, user types, gender distribution, and trip durations. This analysis provides valuable information for improving the bike-sharing system's efficiency, understanding user preferences, and enhancing transportation infrastructure in the region.

Sources of data

The dataset used in this analysis is derived from the Citi Bike program in New Jersey for the year 2021: -https://s3.amazonaws.com/tripdata/index.html

Findings

1. Popular Starting Stations: The top ten starting stations for Citi Bike journeys in New Jersey during January 2021 were Grove St. PATH, Sip Ave, Newport Pkwy, Hamilton Park, Marin Light Rail, Newport Path, Warrenst, Harborside, Liberty Light Rail, and JC Medical Center. These stations are strategically located near major transportation hubs, residential areas, and recreational spaces, making them convenient starting points for various types of trips.
2. User Demographics: There is a notable gender disparity in Citi Bike usage, with a higher proportion of male users compared to female users. The most common birth year for male users is 1987, while for female users, it is 1991. These findings provide insights into the age distribution and gender representation among Citi Bike riders.
3. User Types: The analysis reveals that a larger number of users opt for day/3-day passes rather than annual subscriptions. This suggests that a significant portion of Citi Bike users are occasional riders or tourists who prefer shorter-term access to the bike-sharing system.
4. Trip Durations: Female riders, regardless of user type, tend to have longer trip durations measured in seconds compared to male riders. This observation indicates potential differences in travel behavior, trip purposes, or preferred routes between genders.

Conclusion

The analysis of the USGS earthquake data highlights the ongoing seismic activity around the world. The findings emphasize the importance of monitoring and understanding earthquakes for effective disaster management and preparedness. By visualising and analysing earthquake data, we can gain valuable insights into the Earth's dynamics and contribute to scientific research. The development of interactive tools and visualisations, like the one created using Leaflet, HTML, CSS, JavaScript, and D3, facilitates public awareness and better comprehension of seismic events. Such tools can aid in educating the public, informing decision-making processes, and fostering a proactive approach towards mitigating the impacts of earthquakes.

Project Outline

Instructions

Your task in this assignment is to aggregate the data found in the Citi Bike Trip History Logs and find two unexpected phenomena.

1. Design 2–5 visualizations for each discovered phenomenon (4–10 total). You may work with a timespan of your choosing. Optionally, you can also merge multiple datasets from different periods.

   • The following are questions you may wish to answer. Do not limit yourself to these questions; they are suggestions for a starting point. Be creative!

2. Use your visualizations (not necessarily all of them) to design a dashboard for each phenomenon. The dashboards should be accompanied by an analysis explaining why the phenomenon may be occurring.

3. Create one of the following visualizations for city officials:

   • Basic: A static map that plots all bike stations with a visual indication of the most popular locations to start and end a journey, with zip code data overlaid on top.
   • Advanced: A dynamic map that shows how each station's popularity changes over time (by month and year). Again, with zip code data overlaid on the map.
   • The map you choose should also be accompanied by a write-up describing any trends that were noticed during your analysis.

4. Create your final presentation:

   • Create a Tableau story that brings together the visualizations, requested maps, and dashboards.
   • Ensure your presentation is professional, logical, and visually appealing.