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

Project description

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.


โœจ Features

  • ๐Ÿ“Š Dataset Summary
  • ๐Ÿงน Missing Value Analysis
  • ๐Ÿ” Duplicate Analysis
  • ๐Ÿ“ˆ Numerical Feature Analysis
  • ๐Ÿ“ Categorical Feature Analysis
  • ๐Ÿ”— Correlation Analysis
  • ๐Ÿ“ฆ Outlier Detection
  • โšก Fast and Lightweight
  • ๐Ÿ One-Line Dataset Analysis

๐Ÿ“ฆ Installation

pip install smarteda

๐Ÿš€ Quick Start

import pandas as pd
from smarteda import analyzer

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

# Generate EDA Report
analyzer(df)

๐Ÿ“‹ Example Output

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

๐Ÿ“Š DATASET SUMMARY

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

๐Ÿงน MISSING VALUE ANALYSIS

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

๐Ÿ” DUPLICATE ANALYSIS

Duplicate Rows                 : 0

๐Ÿ“ˆ NUMERICAL ANALYSIS

...

๐Ÿ“ CATEGORICAL ANALYSIS

...

๐Ÿ”— CORRELATION ANALYSIS

...

๐Ÿ“ฆ OUTLIER ANALYSIS

...

๐Ÿ“š 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

๐Ÿ’ป Requirements

  • Python 3.9 or higher
  • pandas
  • numpy

๐Ÿ“‚ Project Structure

smarteda/
โ”‚
โ”œโ”€โ”€ src/
โ”‚   โ””โ”€โ”€ smarteda/
โ”‚       โ”œโ”€โ”€ __init__.py
โ”‚       โ”œโ”€โ”€ analyzer.py
โ”‚       โ”œโ”€โ”€ summary.py
โ”‚       โ”œโ”€โ”€ missing.py
โ”‚       โ”œโ”€โ”€ duplicates.py
โ”‚       โ”œโ”€โ”€ numerical.py
โ”‚       โ”œโ”€โ”€ categorical.py
โ”‚       โ”œโ”€โ”€ correlation.py
โ”‚       โ””โ”€โ”€ outliers.py
โ”‚
โ”œโ”€โ”€ pyproject.toml
โ”œโ”€โ”€ README.md
โ”œโ”€โ”€ LICENSE
โ””โ”€โ”€ MANIFEST.in

๐ŸŽฏ Why SmartEDA?

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

๐Ÿ“„ License

This project is licensed under the MIT License.


๐Ÿ‘จโ€๐Ÿ’ป Author

Shlok Apte

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