This repository contains an analysis of Cyclistic's bike share data, focusing on understanding the usage patterns of annual members and casual riders. The goal is to inform marketing strategies aimed at converting casual riders into annual members.
- Utilized R for data manipulation and cleaning.
- Tasks included loading data, merging datasets, removing irrelevant columns, and creating date and time columns.
- Conducted statistical analysis to understand rider usage patterns.
- Calculated key statistical measures (mean, median, max, min) for different membership types.
- Created visualizations to depict usage patterns.
- Visualizations include rides per day, month, most used bike types, and average ride time per week.
- Identified trends such as higher casual usage in warmer months and longer ride durations.
- Observed differences in preferences for bike types and riding days between casual and annual members.
- Provided insights for targeted marketing strategies.
- Suggestions for tailored membership plans and pricing strategies to convert casual riders.