Statistical Analysis Dashboard

A powerful, interactive statistical analysis and visualization platform built with Django and modern web technologies.

Multiple Data Sources

Upload CSV files, use random data, or analyze local datasets

Interactive Visualizations

Dynamic plots including histograms, box plots, Q-Q plots, and correlation matrices

Advanced Statistics

Comprehensive statistical analysis including hypothesis testing and distribution analysis

Key Features

Data Management
  • CSV file upload support
  • Excel file compatibility (.xlsx, .xls)
  • Random data generation
  • Local dataset integration
  • Automatic data type detection
Statistical Analysis
  • Descriptive statistics
  • Distribution parameters
  • Hypothesis testing (t-tests)
  • Normality testing (Shapiro-Wilk)
  • Correlation analysis
Visualizations
  • Interactive histograms
  • Box plots for distribution analysis
  • Q-Q plots for normality assessment
  • Correlation heatmaps
  • Customizable colors and bin sizes
User Experience
  • Responsive design
  • Real-time updates
  • Tabbed interface
  • Loading indicators
  • Error handling

Machine Learning Functionality

Support Vector Machine (SVM) Classifier
  • Enable machine learning with a single click in the dashboard sidebar
  • Choose your target column and SVM kernel type
  • Train an SVM model directly on your uploaded dataset
  • View performance metrics: accuracy, precision, recall, F1-score
  • Visualize confusion matrix and metrics chart
  • See model details: features, classes, training/test split, and more
  • Quick start guide and status messages for easy workflow

The dashboard's Machine Learning tab makes it easy to experiment with classification using SVM, providing instant feedback and visualizations for your data science projects.

Technology Stack

Backend
  • Django 4.2+ - Web framework
  • Pandas - Data manipulation
  • NumPy - Numerical computing
  • SciPy - Statistical functions
  • Scikit-learn - Machine learning
  • Statsmodels - Statistical modeling
Frontend
  • Bootstrap 5 - UI framework
  • Plotly.js - Interactive charts
  • jQuery - JavaScript library
  • Font Awesome - Icons
  • Responsive Design - Mobile-friendly
  • AJAX - Asynchronous updates

Getting Started

1. Choose Data Source

Select from random data, file upload, or local dataset

2. Configure Analysis

Set parameters like column selection, colors, and bin sizes

3. Explore Results

View interactive plots, statistics, and data previews

Start Analysis