📊 InstaViz - Intelligent Data Visualization

See truth, not just charts.

InstaViz is a next-generation Python visualization library built on top of Matplotlib that automatically chooses the best chart type for your data and provides natural language insights.

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✨ Features

• 🎯 Smart Auto-Selection
• 📈 Built-in Insights
• 🎨 Beautiful Themes
• 🔍 One-Line EDA
• 📊 Statistical Annotations
• 🚀 Zero Configuration

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📦 Installation

pip install instavizlib

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🚀 Quick Start

import instavizlib as viz
import pandas as pd
import numpy as np

df = pd.DataFrame({
    'category': ['A', 'B', 'C', 'D'] * 25,
    'value': np.random.randn(100),
    'score': np.random.exponential(50, 100)
})

viz.show(df)
viz.plot(df, x='category', y='value')
viz.distribution(df, 'score')
viz.compare(df, x='category', y='value')
viz.correlate(df)

📖 API Reference

Function	Description
viz.show(df)	Automatic EDA
viz.plot(df, x, y)	Smart plot
viz.distribution(df, column)	Distribution
viz.compare(df, x, y)	Comparison
viz.trend(df, date, value)	Time series
viz.correlate(df)	Correlation
viz.relationship(df, x, y)	Relationships
viz.target(df, target)	Target analysis

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🎨 Themes

# Available themes: 'dark', 'minimal', 'vibrant', 'corporate'
viz.set_theme('dark')

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⚙️ Configuration

viz.set_config(
    figsize=(12, 8),
    show_insights=True,
    auto_annotate=True,
    max_categories=20
)

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📋 Requirements

• Python >= 3.8
• NumPy >= 1.20
• Pandas >= 1.3
• Matplotlib >= 3.5
• SciPy >= 1.7

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👨‍💻 Author

Md. Ujayer Hasnat
Email: dev.ujayerhasnat@gmail.com
LinkedIn: https://linkedin.com/in/ujayerhasnat
GitHub: https://github.com/CodexUjayer

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📄 License

MIT License

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