An interactive Streamlit dashboard that lets users upload any CSV file and instantly explore it — preview the data, generate charts, and view summary statistics, all without writing code.
🔗 Live App: https://csv-analytics-dashboard.streamlit.app
- CSV Upload — drag and drop any CSV file to load it instantly
- Data Preview — view the full dataset in a scrollable, sortable table
- Dynamic Visualization — choose between Bar, Line, and Pie charts, with any column as X-axis and any numeric column as Y-axis
- Smart Pie Chart Handling — automatically groups low-value categories into "Others" and falls back to a horizontal bar chart when a column has too many unique values, keeping charts readable instead of cluttered
- Column Validation — warns the user if X-axis and Y-axis are the same column, or if no numeric columns exist in the uploaded file
- Summary Statistics — instant descriptive stats (count, mean, std, min, max, quartiles) for the selected numeric column
- Python
- Streamlit — web app framework
- Pandas — data loading and aggregation
- Matplotlib — pie chart rendering
- Upload a CSV file via the file uploader
- The app auto-detects numeric columns for valid Y-axis options
- Pick a chart type and axes from the sidebar controls
- The dashboard renders the chart and matching statistics in real time
git clone https://github.com/Akhilesh-Mogaveer/CSV-Analytics-Dashboard.git
cd CSV-Analytics-Dashboard
pip install -r requirements.txt
streamlit run Data_Analytics.py
Akhilesh Mogaveer
- GitHub: Akhilesh-Mogaveer
- LinkedIn: akhilesh-1109ma