Here are some of my projects that showcase my interest in data analysis. Or you can check out my Tableau Portfolio below ⬇️
Retail Revenue Analysis: External Factors Impact Study
Led a comprehensive analysis of how external factors affect retail chain performance using the Walmart Sales dataset. Discovered significant sales increases during holiday periods (+$81,631 on average) and mapped complex relationships between sales and economic indicators. Developed statistical models to analyze impacts of unemployment rates (4.80-13.12% range), CPI, and fuel prices on consumer behavior.
Skills/Tools: Python, Pandas, Matplotlib, Seaborn, Statistical Analysis, Data Visualization
Unveiling the Enigma of Viking Artifacts
Developed an interactive geospatial visualization system for Viking artifacts across Europe using web scraping and mapping technologies. Created the Gelmir project to analyze Early Medieval Scandinavian art distribution patterns. Combined historical data with modern analytical techniques to reveal new insights about artifact distribution and cultural patterns.
Skills/Tools: Web Scraping, Geospatial Analysis, Data Visualization, Historical Data Analysis
Marketing Campaign A/B Test Analysis
Conducted rigorous A/B testing analysis comparing paid advertisements versus PSAs. Demonstrated a substantial 43.09% lift in conversion rates for the treatment group. Applied chi-square testing and confidence interval analysis to prove statistical significance (p < 0.0001) of the campaign’s effectiveness.
Skills/Tools: A/B Testing, Statistical Analysis, Chi-Square Testing, Marketing Analytics
Historical Letters Analysis: Henry VIII and Anne Boleyn
Applied Natural Language Processing techniques to analyze historical correspondence between Henry VIII and Anne Boleyn. Utilized Python and NLTK for sentiment analysis, revealing emotional patterns and thematic elements. Created visualizations to track sentiment changes across letters, identifying key emotional shifts and religious references.
Skills/Tools: Python, NLTK, Sentiment Analysis, Text Mining, Data Visualization
Premier League Home Advantage Analysis
Conducted statistical analysis of home advantage in the Premier League during the 23/24 season. Applied paired t-tests to confirm statistical significance of home field advantage. Developed analytical framework for evaluating performance differentials between home and away matches.
Skills/Tools: Sports Analytics, Statistical Testing, Data Analysis, Python
E-commerce Mobile App vs. Website Analysis
Led comprehensive analysis comparing mobile app and website performance for an NYC e-commerce retailer. Discovered significant correlation between app usage and spending (+$38.59 per unit time) compared to website (+$0.19). Developed predictive models showing membership length as the strongest revenue driver (+$61.27 per year). Recommendations led to strategic shift in mobile app investment.
Skills/Tools: Python, Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, Statistical Analysis, Predictive Modeling
Support Vector Machines: Iris Classification
Implemented SVM classification model on the classic Iris dataset to distinguish between flower species. Optimized model parameters for maximum accuracy and created visualization tools to demonstrate decision boundaries. Project showcases practical application of machine learning fundamentals and model optimization techniques.
Skills/Tools: Python, Scikit-learn, SVM, Data Visualization, Machine Learning, Model Optimization
K-Means University Clustering
Applied unsupervised learning to categorize universities into public/private institutions using K-means clustering. Uniquely validated clustering results against known labels to assess algorithm performance. Developed comprehensive evaluation metrics to assess clustering effectiveness.
Skills/Tools: Python, K-means Clustering, Unsupervised Learning, Data Analysis, Model Evaluation
Ad Click Prediction Analysis
Developed predictive model for ad click behavior using logistic regression. Created user behavior profiles to optimize ad targeting strategies. Analysis revealed key demographic patterns and engagement factors, leading to actionable recommendations for improved ad targeting and personalization strategies.
Skills/Tools: Python, Logistic Regression, Predictive Modeling, Marketing Analytics, Data Visualization
Damian Wong 