AutoEDA

AutoEDA is a lightweight Python library that automatically performs Exploratory Data Analysis (EDA) and generates an interactive HTML report with visualizations, insights, and dataset statistics.

It is designed to help data scientists quickly understand a dataset without writing repetitive EDA code.

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Features

• Automatic dataset overview
• Missing value analysis
• Correlation matrix
• Distribution plots
• Boxplots
• Scatterplots
• Outlier detection
• Automated insights
• Interactive HTML dashboard
• Works in Jupyter, Google Colab, Kaggle, and Python scripts
• CLI support

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Installation

Install from PyPI:

pip install autoeda-pro

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Quick Start

import pandas as pd
from autoeda import autoeda

df = pd.read_csv("data.csv")

a = autoeda(df)
a.analyze()
a.show()

This will generate a full interactive EDA report inside the notebook.

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Example Output

The generated report includes:

• Dataset overview
• Missing value statistics
• Correlation heatmap
• Variable distributions
• Boxplots and scatterplots
• Key insights about the dataset

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Export Report

You can also export the report as an HTML file:

a.save_html("report.html")

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Command Line Usage

AutoEDA also provides a CLI tool.

autoeda dataset.csv

This will generate:

autoeda_report.html

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Example Dataset

import pandas as pd
from autoeda import autoeda

df = pd.read_csv("dataset_name.csv")

autoeda(df).analyze().show()

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Requirements

• Python ≥ 3.8
• pandas
• numpy
• matplotlib
• jinja2
• tqdm

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PyPI Package

Install the latest version:

pip install autoeda-pro

GitHub Repository:

https://github.com/Harshal-Malviya/AutoEDA

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Author

Harshal Malviya

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