An automated, intelligent Exploratory Data Analysis tool built with Streamlit.
Extract meaningful insights from any CSV dataset — instantly.
AUTOMATIC EDA is a blazing-fast dashboard built entirely in Python. It's designed to replicate and modernize the core functionality of tools like ydata-profiling inside a sleek, intuitive Streamlit web interface.
The complete workflow covers:
- 🗂 Automatic Column Type Detection
- 📊 Deep Statistical Profiling
- 🧮 Interactive Correlation Analysis
- 🔍 Missing Value Detection
All without writing a single line of Python code!
| Feature | Description |
|---|---|
| 🏠 Overview Room | Bird's-eye view of your dataset. See rows, variables, duplicate row counts, and memory size at a glance. |
| 🚨 Smart Alerts | Automatically flags missing values, uniform columns, all-zero columns, and highly correlated variables (Threshold > 0.5). |
| 📊 Variable Profiling | Per-column detailed dive. Generates histograms for numerics, bar charts for categorical formats, and word clouds for text data. |
| 🪢 Interactions | Dynamic Scatter plot interface to visually inspect the relationship between any two numerical features. |
| 🎯 Correlations | Auto-encodes categorical data safely to render beautiful, fully-readable Heatmaps and Correlation tables. |
| 🧩 Missing Values | Comprehensive missing data viz via Count Bar Charts, Nullity Matrices, and Nullity Heatmaps using the missingno library. |
graph TD;
A[Raw CSV Upload] --> B[Smart Type Detection]
B -->|Numeric/Categorical/Text| C[Per-Column Analytics]
C --> D[Alert Evaluation Engine]
D --> E((Interactive UI rendering))
Before running the app locally, ensure you have Python 3.8+ deployed on your system.
# Clone this repository
git clone https://github.com/GaurRitika/Automatic-EDA_platform-
cd Auto-EDA
# Install the dependencies
pip install -r requirements.txt# Start your local Streamlit server
streamlit run app.py- Upload Dataset: Drag and drop any tabular
.csvfile into the sidebar. - Navigate: Use the sidebar radio buttons to switch between Views.
- Analyze: Let the interface compute everything from memory usage to data outliers in real-time.
