kaizenstat 0.1.0

Zero-friction AutoML + Data Cleaning Toolkit

🚀 KaizenStat

KaizenStat is a zero-friction data validation, automatic cleaning, and AutoML benchmarking toolkit designed to fit right into your daily data science workflow. It helps you diagnose and repair dataset issues instantly and trains baseline models to give you immediate insights.

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✨ Features

• 🔍 kz.audit(): Instantly sweep datasets for duplicates, NaNs, infs, constant columns, and target label integrity.
• 🩹 kz.heal(): Automatically clean datasets by repairing missing targets, removing duplicates, dropping dead/constant columns, and imputing missing data using mean, median, or mode.
• 🚀 kz.benchmark(): Auto-detects objectives (classification/regression), builds pre-processing pipelines, trains elite models (Linear/Ridge, RandomForest, Neural Networks), and ranks them on a beautiful leaderboard.
• 💻 CLI Interface: Command line utility (kz) to audit, heal, or benchmark CSV datasets directly from the terminal.

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📦 Installation

Install KaizenStat from PyPI:

pip install kaizenstat

Or install it locally in editable mode for development:

pip install -e .

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🚀 Quickstart Usage

Python API

import pandas as pd
from kaizenstat import KaizenStat

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

# 1. Audit dataset
KaizenStat.audit(df, target_column="target")

# 2. Automatically repair dataset issues
clean_df = KaizenStat.heal(df, target_column="target", method="fill_median")

# 3. Benchmark ML models
leaderboard = KaizenStat.benchmark(clean_df, target_column="target")

💻 Command Line Interface (CLI)

KaizenStat provides a powerful CLI tool named kz right out of the box:

Audit a dataset:

kz audit data.csv --target price

Heal a dataset:

kz heal data.csv --target price --method fill_median -o clean_data.csv

Benchmark a dataset:

kz benchmark clean_data.csv --target price

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🛠 Development and Packaging

Build the package using build:

pip install build twine
python -m build

Upload to PyPI:

twine upload dist/*

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📄 License

Distributed under the MIT License. See LICENSE for more information.