I have recently completed an in-depth Exploratory Data Analysis (EDA) on Walmart's sales data, uncovering valuable insights that can drive key business decisions. By analyzing three months of data (January - March), I have identified several crucial patterns related to customer behavior, product performance, and branch operations.
- Product Performance: Electronic accessories and Food & Beverages emerged as the top performing product categories in terms of total sales.
- Branch Comparison: Unique performance trends were observed across branches A, B, and C.
- Customer Insights: Explored spending habits and product preferences between members vs. normal customers.
- Temporal Patterns: Visualized daily and monthly sales trends using moving averages.
- Payment Methods: Analyzed payment method preferences across different customer segments.
- Data Cleaning: Tackled outliers and ensured data quality for accurate insights.
- Statistical Analysis: Applied descriptive statistics to understand sales distributions.
- Data Visualization: Created meaningful visualizations using Matplotlib and Seaborn.
- Time Series Analysis: Incorporated moving averages to identify emerging sales trends.
- Categorical Analysis: Cross-analyzed product performance by branch and customer type.
- Python (Pandas, NumPy)
- Matplotlib & Seaborn for insightful visualizations
- Jupyter Notebook for an efficient analysis workflow
I’m currently building an interactive Streamlit dashboard to make these insights accessible to business stakeholders. The dashboard will enable users to:
- Filter data by time period, product category, and branch
- Compare performance metrics across various dimensions
- Generate dynamic visualizations based on selected parameters
- Export insights for reporting and presentations
I’m extremely passionate about transforming data into actionable insights for businesses. If you’re interested in retail analytics, dashboard development, or data visualization, I’d love to connect! Feel free to reach out for feedback or collaboration opportunities.
#DataAnalysis #RetailAnalytics #Python #DataVisualization #BusinessIntelligence #Streamlit #DataScience