smarteda-shlok 1.0.1

A lightweight Python library for automated exploratory data analysis (EDA).

SmartEDA

SmartEDA is a lightweight Python library for Automated Exploratory Data Analysis (EDA). It helps data analysts, data scientists, students, and researchers quickly understand their datasets by generating essential statistical insights with a single function call.

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✨ Features

• 📊 Dataset Summary
• 🧹 Missing Value Analysis
• 🔁 Duplicate Analysis
• 📈 Numerical Feature Analysis
• 📝 Categorical Feature Analysis
• 🔗 Correlation Analysis
• 📦 Outlier Detection
• ⚡ Fast and Lightweight
• 🐍 One-Line Dataset Analysis

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📦 Installation

pip install smarteda-shlok

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🚀 Quick Start

import pandas as pd
from smarteda import analyzer

# Load dataset
df = pd.read_csv("Titanic.csv")

# Generate EDA Report
analyzer(df)

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📋 Example Output

======================================================================
                        SMARTEDA REPORT
======================================================================

📊 DATASET SUMMARY

Rows                           : 891
Columns                        : 12
Memory Usage (MB)              : 0.28
Duplicate Rows                 : 0
Missing Cells                  : 866
Missing Percentage             : 8.10

🧹 MISSING VALUE ANALYSIS

Total Missing Cells            : 866
Columns with Missing Values    : 3
Missing Percentage             : 8.10

🔁 DUPLICATE ANALYSIS

Duplicate Rows                 : 0

📈 NUMERICAL ANALYSIS

...

📝 CATEGORICAL ANALYSIS

...

🔗 CORRELATION ANALYSIS

...

📦 OUTLIER ANALYSIS

...

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📚 Modules

Module	Description
analyzer.py	Generates the complete EDA report
summary.py	Dataset summary
missing.py	Missing value analysis
duplicates.py	Duplicate row analysis
numerical.py	Numerical statistics
categorical.py	Categorical feature analysis
correlation.py	Correlation analysis
outliers.py	Outlier detection

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💻 Requirements

• Python 3.9 or higher
• pandas
• numpy

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📂 Project Structure

smarteda/
│
├── src/
│   └── smarteda/
│       ├── __init__.py
│       ├── analyzer.py
│       ├── summary.py
│       ├── missing.py
│       ├── duplicates.py
│       ├── numerical.py
│       ├── categorical.py
│       ├── correlation.py
│       └── outliers.py
│
├── pyproject.toml
├── README.md
├── LICENSE
└── MANIFEST.in

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🎯 Why SmartEDA?

• Beginner-friendly
• Lightweight and fast
• Easy to understand
• Modular architecture
• Works seamlessly with Pandas DataFrames
• Designed for quick exploratory data analysis

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📄 License

This project is licensed under the MIT License.

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👨‍💻 Author

Shlok Apte