📈 Insightify Dashboard

A powerful and interactive sales analytics dashboard built with Streamlit, offering comprehensive insights into superstore sales data.

🌟 Features

• Real-time KPI Metrics: Track sales, profit, and order volumes with year-over-year changes
• Interactive Filtering: Filter data by year for targeted analysis
• Rich Visualizations:
  • Category Performance Scatter Plot
  • Order Distribution Sunburst Chart
  • Monthly Sales Trends Line Chart
  • Top Products Analysis
  • Shipping Performance Gauge
  • Category Sales Trends

🛠️ Tech Stack

• Streamlit: Core framework for building the web application
• Pandas: Data manipulation and analysis
• Plotly: Interactive plotting (scatter plots, sunburst charts, gauges)
• Altair: Declarative statistical visualizations
• NumPy: Numerical computations
• Millify: Number formatting

📋 Prerequisites

• Python 3.12+
• Required Python packages:

  streamlit
  pandas
  numpy
  plotly
  altair
  millify
  

• Excel dataset: superstore_enriched.xlsx

🚀 Installation & Running

1. Clone the repository
2. Install dependencies:

   pip install -r requirements.txt

3. Run the dashboard:

   streamlit run app.py

📊 Dashboard Sections

1. KPI Metrics

• Sales total with YoY change
• Profit total with YoY change
• Order count with YoY change

2. Category Performance Analysis

• Scatter plot showing Sales vs Profit by Category
• Sunburst chart displaying order distribution by Region and Segment

3. Sales Trends

• Interactive line chart showing monthly sales trends by year

4. Product Performance

• Top 10 selling products
• Top 10 most profitable products

5. Shipping and Category Trends

• Gauge chart showing average shipping days
• Stacked bar chart displaying sales trends by product category

🎨 Customization

The dashboard uses a custom color palette:

CUSTOM_COLORS = {
    'Furniture': '#005C53',
    'Office Supplies': '#9FC131',
    'Technology': '#042940'
}

🔧 Performance Optimizations

• Data loading is cached using @st.cache_data
• Efficient data filtering and aggregation
• Responsive layout using Streamlit's column system

📝 Code Structure

• Constants: Configuration and color definitions
• Data Loading: Cached data loading and preprocessing
• UI Styling: Custom styling for metrics and layout
• Dashboard Components: Modular functions for each visualization
• Main Function: Orchestrates the dashboard assembly

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.