Welcome to my Data Analysis Portfolio! Hi I'm Ken. Here, you'll find a collection of my data analysis projects and relevant information about me. I'm passionate about extracting insights and telling stories from data, and I'm excited to share my work with you.
Description: In this project, I conducted an in-depth inventory analysis for Mint Classics Company, a classic model car retailer. The project aimed to optimize inventory management, identify sales trends, and enhance shipping efficiency. I collected, cleaned, and analyzed data from Mint Classics Company's relational database to provide actionable insights for strategic decision-making.
Languages and Packages Used: SQL, Python, Pandas, Matplotlib, Seaborn, Jupyter Notebook
Link to Project: Project Report
Description: In this project, I analyzed a dataset of vehicle attributes from the 1970s and 1980s to identify factors impacting fuel efficiency (mpg). I cleaned the data, performed exploratory analysis, and used feature engineering for in-depth analysis. By applying OLS and Ridge Regression models and employing cross-validation, I found that vehicle weight, model year, and origin significantly influence mpg. These insights can inform vehicle design and environmental policy, demonstrating data analysis's role in automotive research.
Languages and Packages Used: Python, Pandas, Matplotlib, Seaborn, Sklean, Statsmodel, Numpy, Jupyter Notebook
Linke to Project: Project Report
Feel free to explore more of my projects on my GitHub profile. Each project comes with detailed documentation and code to give you a deeper understanding of my work.
I'm always open to new opportunities, collaborations, and discussions. If you'd like to connect with me or have any questions, feel free to reach out via:
- LinkedIn: LinkedIn Profile
- GitHub: GitHub profile
Let's explore the world of data together! 📊📈🔍
