Cyclistic-Bike-Share-Analysis-R

A data-driven marketing strategy analysis using R to identify behavioral differences between casual riders and annual members.

From Data to Insight 🚲

📊 Project Overview

This project analyzes 12 months of historical trip data from 'Cyclistic', a fictional bike-share company. The goal is to design marketing strategies aimed at converting casual riders into annual members by analyzing behavioral trends.

🛠️ Technical Stack

• Language: R
• Libraries: tidyverse (Data Wrangling), ggplot2 (Visualization), lubridate (Date-Time analysis), skimr.
• Environment: RStudio / R Markdown.

💡 Key Analysis Steps

1. Data Cleaning: Handled missing values, removed duplicate entries, and filtered out "test" rides and negative trip durations.
2. Feature Engineering: Created new variables for ride_length and day_of_the_week.
3. Exploratory Data Analysis (EDA): Calculated mean/max ride lengths and identified peak usage hours for different user types.
4. Visualization: Used ggplot2 to map the divergent behaviors of 'Casual' vs. 'Member' riders.

📈 Key Insights

• Usage Patterns: Annual members have consistent trip durations, primarily for commuting. Casual riders spike significantly on weekends for leisure.
• Peak Season: Casual rider activity peaks in the summer months, providing a prime window for targeted digital marketing.

📷 Visualizations

Details

Click here to view all 5 Visual Analysis Charts 📊

📁 Project Contents

• PDF Report: A formal summary of the analysis.
• Interactive HTML: Detailed code walkthrough and interactive visuals.