Title: Chicago DIVVY Bikeshare Data Analysis – A Google Data Analytics Capstone Project
Introduction: This is my Google Data Analytics Professional Certificate Capstone Project. In this endeavor, I delved deep into the extensive dataset of Chicago’s DIVVY bikeshare service, covering the entire 2022 calendar year. Using R for data analysis and R Markdown for reporting, I meticulously dissected the data, offering insights into this invaluable urban mobility system.
Project Details:
1. Data Cleaning and Transformation: One of the foundational aspects of my project was the thorough data cleaning and manipulation process, meticulously documented in my report. This crucial step ensured the reliability and accuracy of the subsequent analysis. The resulting clean dataset served as the foundation for the in-depth analysis that followed.
2. Exploratory Data Analysis (EDA): Employing various statistical and visualization techniques, I conducted a comprehensive EDA. This allowed me to uncover patterns, trends, and valuable insights from the DIVVY bikeshare data. My analysis shed light on user behavior, ride patterns, popular routes, and more, enabling us to understand the bikeshare service’s dynamics and its role in Chicago’s urban ecosystem.
3. Data Visualization with Tableau: The outcomes of the ETL (Extract, Transform, Load) process were seamlessly integrated into Tableau. Here, I harnessed the power of this versatile data visualization tool to create compelling and informative visualizations. These visualizations are not only visually appealing but also serve as effective communication tools, making complex data accessible and understandable to a broad audience.
4. Key Insights and Impact: My analysis uncovered valuable insights that can be used to enhance Chicago’s DIVVY bikeshare service. The project provides an opportunity for stakeholders, city planners, and the community to make informed decisions and improvements that can help shape the future of urban mobility in Chicago.