This repository contains the advanced capstone project for the Google Data Analytics program, focusing on Cyclistic, a bike-sharing company based in Chicago. The project's primary objective is to analyze and identify key trends in bike usage to develop strategies for converting casual riders into annual members.
- Clean and prepare Cyclistic's bike-sharing data for analysis.
- Perform exploratory data analysis (EDA) to understand user patterns.
- Develop visualizations to communicate findings.
- Provide actionable insights and business recommendations.
The dataset used in this analysis is provided by Cyclistic and includes detailed records of bike trips taken by customers. The data I drew came from the August 2020 - July 2021 range, offering comprehensive insights into user behavior.
R, Tableau, Excel
- Importing and merging datasets.
- Handling missing values.
- Ensuring data consistency.
- Exploratory Data Analysis (EDA):
- Analyzing ride duration, distance, and user demographics.
- Identifying peak usage times and popular routes.
- Creating interactive dashboards using Tableau.
- Generating plots and graphs to illustrate key findings.
- Insights & Recommendations:
- Analyzing differences between casual riders and annual members.
- Suggesting marketing strategies to increase annual memberships.
I do not have a background in marketing at all, so please correct me if needed. These are my suggestions for the marketing team to convert casual riders to annual members:
- Emphasize membership benefits with a focus on discounts during busy times of the year, Summer, and more on weekends.
- Personalize customer discounts by asking the customer what their riding habits and preferences are.
- Have existing members give testimonials and their personal story on how using Cyclistic's system has changed their lives. This creates a community out of customers, offers discounts to existing customers, and encourages new customers to join the program.
Arguably the most important piece of this project, where I've spent a combined total of 40+ hours.
- Pivot Tables in Microsoft Excel
- Practice using R for data analysis and cleaning specifically using the 'tidyverse' package for data analysis
- Graphs in Tableau, edited visual elements along with creating different charts and filters.
- Design elements of an effective dashboard
- FinalAnalysis.R: Main R script for data cleaning and analysis.
- FinalAnalysisTableau.R: R script for preparing data for Tableau visualizations.
- Excel Sheets: Download the required data (082020 - 072021) from this link: https://divvy-tripdata.s3.amazonaws.com/index.html
- Copy
git clone https://github.com/aaroncapron/google-DA-capstone-project.git
- Install the necessary dependencies and tools:
install.packages("dplyr")
install.packages("ggplot2")
This project is licensed under the MIT License. See the LICENSE file for more details.
- Coursera/Google Advanced Data Analytics program for the capstone project guidelines and grading.
- Cyclistic for providing the data.
If you have any questions or need more information, please get in touch with me at aaroncapron.work@gmail.com.