01 – Data Overview

📘 RIDE User Manual – Panel 1: Data Overview

🔍 Purpose of this Panel

The Data Overview panel is designed to give users an instant, interactive understanding of their dataset. It provides descriptive statistics, data types, shape, missing value counts, and correlation analysis—all wrapped with optional AI-driven explanations.

Recommended Reading

Blog: A Gentle Introduction to Python's Pandas Library — The First 5 Functions You Need to Know

🧭 User Workflow

Add API Key (on Home Page)
The user needs to first input their OpenAI API key for GPT-powered insights to work.
Upload Dataset
The dataset must be uploaded. The tool expects a tabular format (e.g., CSV, Excel).
View Header & Dataset Cards
A GIF and a visual introduction describe what this panel does.
Explore Tabs:
- 📊 Basic Statistics
  - Preview of top rows of the dataset.
  - Descriptive statistics using .describe().
  - Info about shape, features, data types, and missing values.
  - Option to trigger AI analysis of summary statistics.
- 🔄 Correlations
  - Correlation matrix for numeric features.
  - Plotly heatmap visualization.
  - Optional GPT-based insights for both matrix and heatmap.

💻 Features Breakdown

Feature	Description
Dataset Preview	Shows the first few rows of the uploaded dataset.
Statistical Summary	Displays count, mean, std, min, max, and quartiles for each numeric column.
Shape and Columns	Shows number of rows/columns and feature names.
Data Types	Indicates each column’s datatype (int, float, object, etc.).
Missing Values Count	Identifies which columns have missing data and how much.
Correlation Matrix	Matrix showing linear relationships between numeric features.
Correlation Heatmap	Heatmap using Plotly to visualize strong/weak relationships.
AI-Powered Insights	GPT-generated explanations for summary stats and heatmap analysis.

🤖 AI Features

LLM (GPT-4o-mini) analyzes:
- Statistical distribution
- Data trends
- Feature relationships
Image-based GPT analysis of the correlation heatmap using the AnalyzeImage() function.