This repository contains a comprehensive Jupyter Notebook detailing the process of aggregating and cleaning over a decade's worth of data from Citibikes NYC rides. The dataset encompasses a vast array of ride information, offering valuable insights into patterns, trends, and user behaviors over time.
The Jupyter Notebook included in this repository walks through each step of the data aggregation and cleaning process, highlighting methodologies and techniques employed to ensure data integrity and quality. From handling missing values to standardizing formats, every aspect of data preprocessing is thoroughly documented.
Furthermore, this cleaned dataset serves as the foundation for generating a compelling data story using Tableau. Leveraging Tableau's robust visualization capabilities, interactive dashboards are crafted to unveil fascinating insights derived from the Citibikes NYC ride data. These dashboards offer a user-friendly interface to explore key metrics, trends, and correlations, enabling stakeholders to gain deeper understanding and make informed decisions.
Whether you're a data enthusiast seeking to delve into Citibikes NYC ride patterns or a stakeholder aiming to leverage actionable insights, this repository provides a comprehensive resource to unlock the potential of the Citibikes dataset. Dive in, explore, and discover the stories hidden within the data!
This project is part of the data challenge for Module 18 of the UofT SCS edX Data Bootcamp.
Tableau Story: NYC Citibike Trip Data Story
Markdown file detailing analysis: Analysis_description.md
Citi Bike System Data (n.d.). Citi Bike NYC. https://citibikenyc.com/system-data. Accessed Jan 8, 2024.
Challenge instructions and starter files, as well as some code sections that were adapted from the UofT SCS EdX Data Bootcamp class activities:
© 2022 edX Boot Camps LLC. Confidential and Proprietary. All Rights Reserved.