Metadata-Version: 2.4
Name: datapilot-kit
Version: 0.4.1
Summary: An open-source Python library for deterministic exploratory data analysis and dataset understanding.
Author: Avishkar D. Gopale
License-Expression: MIT
Project-URL: Homepage, https://github.com/Aviii-3085/datapilot
Project-URL: Repository, https://github.com/Aviii-3085/datapilot
Project-URL: Issues, https://github.com/Aviii-3085/datapilot/issues
Project-URL: Documentation, https://github.com/Aviii-3085/datapilot/tree/main/docs
Keywords: eda,exploratory-data-analysis,data-analysis,data-science,dataset-profiling,machine-learning,analytics,python
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=2.2
Requires-Dist: numpy>=2.0
Requires-Dist: scipy>=1.14
Requires-Dist: matplotlib>=3.9
Requires-Dist: plotly>=6.0
Requires-Dist: jinja2>=3.1
Requires-Dist: rich>=14.0
Requires-Dist: typer>=0.16
Requires-Dist: openpyxl>=3.1
Provides-Extra: dev
Requires-Dist: black; extra == "dev"
Requires-Dist: ruff; extra == "dev"
Requires-Dist: mypy; extra == "dev"
Requires-Dist: pytest; extra == "dev"
Dynamic: license-file

# Datapilot

**The first step after loading your dataset.**

Datapilot is an open-source Python library for deterministic exploratory data analysis and dataset understanding.

Every data project begins with understanding the data. Datapilot helps you understand your dataset before building machine learning models, dashboards, or AI-powered applications.

---

## Installation

Install Datapilot from PyPI:

```bash
pip install datapilot-kit
```

---

## Quick Start

```python
import pandas as pd

from datapilot import analyze

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

report = analyze(df)

print(report.summary())
print(report.dataset_health())
print(report.insights())
```

Datapilot analyzes your dataset and returns a structured `Report` object containing dataset summaries, health assessments, statistical analysis, insights, and recommendations.

---

## Supported Inputs

Datapilot currently supports:

- Pandas DataFrames
- CSV files
- Excel files
- Headerless `.data` files

---

## Features

- Dataset Summary
- Dataset Health Score
- Missing Value Analysis
- Duplicate Detection
- Data Type Analysis
- Statistical Summaries
- Outlier Detection
- Correlation Analysis
- Actionable Insights
- Professional HTML Reports

---

## Documentation

Project documentation is available in the `docs/` directory.

- Vision
- User Journey
- API Philosophy
- API Review
- Roadmap

---

## Status

**Datapilot v0.4.0 — Stable Release**

Datapilot v0.4.0 extends the core data-quality workflow with:

- Dataset Health 2.0
- ML Readiness assessment
- ML assessment coverage
- Statistical Profile
- Data Integrity signals
- Notebook Readiness
- Assessment Boundaries
- Expanded HTML reporting
- Real-world dataset validation

The package is available on PyPI as **`datapilot-kit`**.

## License

Datapilot is open source and released under the **MIT License**.
