pycardio 0.1.0

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.

pycardio

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:

pip install pycardio

Usage

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 file for details.