Metadata-Version: 2.4
Name: pycardio
Version: 0.1.0
Summary: A curated collection of cardiovascular, clinical trial, and heart disease datasets for data analysis, statistical modeling, and machine learning research. Includes cardiac arrest risk evaluations, UCI Cleveland heart disease database subsets, Framingham 10-year coronary risk factors, 1D ECG time-series signals for regression, cardiac biomarkers (CK-MB, troponin), hospital performance metrics, and regional risk assessments from Kaggle sources.
Home-page: https://github.com/yuyoun25/pycardio
Author: Yuna Youn Ipanaque
Author-email: Yuna Youn Ipanaque <yuna.youn@alum.udep.edu.pe>
Maintainer-email: Yuna Youn Ipanaque <yuna.youn@alum.udep.edu.pe>
License: MIT License
        
        Copyright (c) 2026 Yuna Youn Ipanaque
        
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Project-URL: Bug Tracker, https://github.com/yuyoun25/pycardio/issues
Project-URL: Documentation, https://github.com/yuyoun25/pycardio
Project-URL: Source Code, https://github.com/yuyoun25/pycardio
Keywords: cardiology,cardiovascular,heart disease,cardiac arrest,coronary heart disease,troponin,ck-mb,ecg,time series,electrocardiogram,clinical data,risk assessment,predictive modeling,survival analysis,epidemiology,biostatistics,medical statistics,data science,machine learning,datasets,open data,open science,research,healthcare,kaggle
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Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.10
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Requires-Python: >=3.8
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License-File: LICENSE
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# pycardio

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/)

The `pycardio` package provides a curated collection of cardiovascular, clinical trial, and heart disease datasets for data analysis, statistical modeling, and machine learning research. Includes cardiac arrest risk evaluations, UCI Cleveland heart disease database subsets, Framingham 10-year coronary risk factors, 1D ECG time-series signals for regression, cardiac biomarkers (CK-MB, troponin), hospital performance metrics, and regional risk assessments from Kaggle sources.


## Installation
You can install the `pycardio` package from PyPI:
```bash
pip install pycardio
```

## Usage
```python

import pycardio as pcd

# List all available datasets

datasets = pcd.list_datasets()
print(datasets)

# Load a specific dataset

df = pcd.load_dataset('cardiac_arrest')
print(df.head())

# Describe dataset

df_01 = pcd.describe('cardiac_arrest')
print(df_01)

```

## Some Available Datasets

| Dataset | Description |
|---------|-------------|
| `cardiac_arrest` | Clinical and demographic data from the UCI repository for cardiac arrest risk evaluation and predictive modeling. |
| `heart_patients` | Contains 1,025 patient records with cardiac health attributes such as age, sex, chest pain type, and resting blood pressure. |
| `heart_healthcare` | Features 76 clinical attributes (14 commonly used) from the Cleveland database for heart disease presence classification. |


> Run `pycardio.list_datasets()` or `pcd.list_datasets()` (using `pcd` as alias) to see the full list of available datasets.

## Disclaimer

The datasets included in `pycardio` are provided strictly for educational,
research, and informational purposes. All datasets originate from open Kaggle sources
and retain their original licenses and attributions.

The author of `pycardio` makes no warranties, express or implied, regarding
the accuracy, completeness, or suitability of any dataset for a particular purpose.
Users are solely responsible for ensuring that their use of these datasets complies
with applicable laws, regulations, and ethical guidelines.

Any findings, conclusions, or decisions derived from the use of these datasets
are the sole responsibility of the user. The author shall not be held liable for
any direct, indirect, incidental, or consequential damages arising from the use
or misuse of the datasets included in this library.

For clinical, diagnostic, or any medical decision-making purposes, always consult
a qualified healthcare professional or cardiologist.


## License

The `pycardio` library is released under the **MIT License**, which allows for open use, modification, and distribution.
See the [LICENSE](LICENSE) file for details.
