Cyclistic Bike-Share Case Study

Google Data Analytics Professional Certificate – Capstone Project

Overview

This project explores bike-share usage patterns to understand how casual riders and annual members use Cyclistic bikes differently.
The objective is to support a marketing strategy focused on converting casual riders into annual members.

Skills Demonstrated

• R programming (dplyr, ggplot2, lubridate, janitor)
• Data cleaning and preparation
• Exploratory data analysis
• Data visualization
• Business reporting and communication

Data

Data was provided by Motivate International Inc.

Datasets:

• Divvy Trips 2019 Q1
• Divvy Trips 2020 Q1

Data Cleaning

Data cleaning and preparation were performed in R using tidyverse packages.
Key steps included:

• Standardizing inconsistent column names
• Converting text timestamps to datetime format
• Creating ride_length and day_of_week variables
• Removing invalid trips (negative or longer than 24 hours)
• Merging datasets (combined size ~792,000 records)

Key Findings

1. Casual riders take longer rides

   • Casual: 36.5 minutes
   • Member: 11.4 minutes

2. Casual riders use the service more on weekends

   • Particularly on Saturdays and Sundays

3. Members ride mainly on weekdays

   • Consistent with commuter usage

4. Casual ride duration increases significantly on weekends

   • Indicates leisure or tourism-driven behavior

Visualizations

• Average ride duration by day of the week
• Member vs. casual ride length
• Number of rides by day of the week

(Plots available in the images/ folder.)

Recommendations

• Offer weekend-focused membership promotions
• Use experience-based marketing aimed at leisure riders
• Expand partnerships with employers to increase weekday member usage

Challenges and Solutions

• Column name inconsistencies between years → resolved with rename()
• Timestamp fields imported as text → corrected with ymd_hms()
• ride_id format mismatch → converted to character
• tidyverse dependency issues on Linux → resolved by installing packages individually
• Removed invalid trips (>24 hours or negative duration)

Reports

Final versions of the project reports are available below:

• Final Report (PDF)
  https://github.com/dpf-tech/cyclistic-case-study/raw/main/Cyclistic_Report_Capstone_Project.pdf

• Executive Summary (PDF)
  https://github.com/dpf-tech/cyclistic-case-study/raw/main/GH_Cyclistic_Summary_Report.pdf