The Data Analyst Dashboard is a comprehensive, interactive analytic platform designed to streamline e-commerce data exploration. Built with Python and Streamlit, it allows analysts to move beyond static reports by providing real-time data filtering, dynamic chart generation (bar, line, pie), and automated summary statistics. The system features a robust preprocessing pipeline for handling missing data and outliers, ensuring that decision-makers have access to high-quality insights on sales performance and product category trends.
Tech Stack
Python
Streamlit
Plotly
Pandas
NumPy
Dash
Tools Used
VS Code
Jupyter Notebook
Git LFS
PowerShell
Key Features
Interactive Data Exploration
▸Dynamic Chart Generation: Real-time rendering of bar, line, and pie charts based on multi-variable user selections.
▸Drill-down Analytics: Ability to focus on specific time periods or product categories with instant visual feedback.
▸Metric Customization: Dynamic dashboard layout that adjusts according to the selected Key Performance Indicators (KPIs).
Data Filtering & Manipulation
▸Smart Preprocessing: Automated handling of missing values, duplicate entries, and data type transformations.
▸Advanced Filtering: Multi-layered filters for product categories, price ranges, and sales dates.
▸Outlier Detection: Integrated statistical methods to identify and isolate anomalies in e-commerce transaction data.
Customizable Dashboards
▸Modular UI Layout: Flexible dashboard design using Streamlit containers for a clean and professional analytics interface.
▸Real-time State Management: Instant synchronization between dropdown selections and data visualization components.
▸Export Capabilities: One-click functionality to export processed data and summary statistics for offline reporting.