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Superstore Sales Performance Dashboard | Python + Streamlit
I recently worked on a complete data analysis and visualization project using the Superstore dataset.
The goal was to transform raw data into a clear and interactive dashboard that makes business performance easier to understand and explore.
Data Cleaning & Preparation
Cleaned and prepared the dataset using Python in Jupyter Notebook
Handled data inconsistencies and prepared the data for analysis
Created the necessary transformations and metrics
Data Analysis
Sales and revenue analysis
Order and customer analysis
Customer segmentation
Product and category performance
Temporal and seasonal analysis
Identification of top-performing and loss-making products
Interactive Dashboard
I developed the dashboard using Python + Streamlit, with interactive filters for:
Date
Category
Sub-category
Segment
Region
The dashboard includes KPIs such as revenue, number of orders, average basket value, and number of customers, along with interactive charts and detailed breakdowns.
Tools & Technologies:
Python • Pandas • NumPy • Jupyter Notebook • Streamlit • Plotly
This project was a great exercise in turning raw business data into actionable insights through an interactive data product.
#DataAnalysis #Python #Streamlit #Pandas #DataScience #Dashboard #DataVisualization #JupyterNotebook #Analytics
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