#!/usr/bin/env python3
"""
Beautiful EDA Standards Showcase
================================

This test demonstrates the enhanced Rich console styling across multiple
EDA functions that now have beautiful, consistent display standards.

Functions Enhanced with Beautiful Styling:
✅ check_null_columns - COMPLETED (main data health overview)
✅ summarize_eda_insights - CRITICAL comprehensive insights 
✅ analyze_categorical_columns - HIGH priority core EDA
✅ display_column_types - HIGH priority display function  
✅ convert_to_numeric - MEDIUM widely used conversion
✅ impute_numerical_median - MEDIUM data cleaning
"""

import pandas as pd
import numpy as np

def create_showcase_dataset():
    """Create a comprehensive dataset to showcase all EDA functions."""
    np.random.seed(42)
    
    # Create a realistic dataset with various data issues
    data = {
        # Clean numeric columns
        'age': np.random.normal(35, 10, 1000).astype(int),
        'income': np.random.lognormal(10, 1, 1000),
        
        # Column with nulls for null analysis
        'education_years': [None if i % 10 == 0 else np.random.randint(8, 20) 
                           for i in range(1000)],
        
        # Categorical columns for categorical analysis
        'city': np.random.choice(['NYC', 'LA', 'Chicago', 'Houston', 'Phoenix'], 1000),
        'job_category': np.random.choice(['Tech', 'Finance', 'Healthcare', 'Education'], 1000),
        
        # Numeric data stored as strings (for convert_to_numeric)
        'score_as_string': [str(np.random.randint(0, 100)) if i % 20 != 0 else 'N/A' 
                           for i in range(1000)],
        
        # Target variable for insights
        'approved': np.random.choice([0, 1], 1000, p=[0.3, 0.7]),  # Imbalanced
        
        # Column needing imputation
        'salary': [None if i % 15 == 0 else np.random.normal(50000, 15000) 
                  for i in range(1000)]
    }
    
    return pd.DataFrame(data)

def showcase_beautiful_eda():
    """Showcase all the beautiful EDA functions with enhanced styling."""
    
    print("🎨 BEAUTIFUL EDA STANDARDS SHOWCASE")
    print("=" * 60)
    print("Demonstrating enhanced Rich console styling across EDA functions")
    print()
    
    # Create showcase dataset
    df = create_showcase_dataset()
    
    print("📊 Dataset created with intentional data quality issues for demonstration")
    print(f"Shape: {df.shape}")
    print()
    
    from edaflow.analysis.core import (
        check_null_columns, 
        analyze_categorical_columns,
        display_column_types,
        convert_to_numeric,
        impute_numerical_median,
        summarize_eda_insights
    )
    
    # Test 1: Beautiful null analysis
    print("🔍 1. BEAUTIFUL NULL ANALYSIS")
    print("-" * 40)
    result1 = check_null_columns(df, threshold=8)
    
    print("\n" + "🔍 2. BEAUTIFUL CATEGORICAL ANALYSIS")  
    print("-" * 40)
    analyze_categorical_columns(df, threshold=30)
    
    print("\n" + "🔍 3. BEAUTIFUL COLUMN TYPES DISPLAY")
    print("-" * 40) 
    col_info = display_column_types(df)
    
    print("\n" + "🔍 4. BEAUTIFUL NUMERIC CONVERSION")
    print("-" * 40)
    df_converted = convert_to_numeric(df, threshold=25, inplace=False)
    
    print("\n" + "🔍 5. BEAUTIFUL IMPUTATION DISPLAY")
    print("-" * 40)
    df_imputed = impute_numerical_median(df_converted, inplace=False)
    
    print("\n" + "🔍 6. BEAUTIFUL COMPREHENSIVE INSIGHTS")
    print("-" * 40)
    insights = summarize_eda_insights(
        df_imputed, 
        target_column='approved',
        eda_functions_used=[
            'check_null_columns', 
            'analyze_categorical_columns',
            'display_column_types',
            'convert_to_numeric',
            'impute_numerical_median'
        ]
    )
    
    print("\n🎉 BEAUTIFUL EDA SHOWCASE COMPLETE!")
    print("=" * 60)
    print("✨ All functions now feature:")
    print("  • Consistent rounded borders (box.ROUNDED)")
    print("  • Optimized width constraints (width=80)")
    print("  • Google Colab compatibility")  
    print("  • Beautiful color schemes")
    print("  • Perfect alignment and padding")
    print("  • Professional visual hierarchy")
    
    return True

if __name__ == "__main__":
    showcase_beautiful_eda()
    print("\n🎨 Beautiful EDA standards successfully implemented!")
