Source code for discrimintools.datasets.load_heart

# -*- coding: utf-8 -*-
from pandas import read_excel
from pathlib import Path

#set directory
DATASETS_DIR = Path(__file__).parent / "data"

[docs] def load_heart(element = "subset"): """ Heart dataset Parameters ---------- element : str, default = 'train' The dataset to load. Possible values are: - 'subset' for subset of all dataset (with few columns). - 'train' for training dataset. - 'test' for testing dataset. Returns ------- heart : DataFrame of shape (n_samples, n_columns) The heart dataset. References ---------- [1] Ricco Rakotomalala (2020), « `Pratique de l'Analyse Discriminante Linéaire <https://hal.science/hal-04868585v1/file/Pratique_Analyse_Discriminante_Lineaire.pdf>`_ », Version 1.0, Université Lumière Lyon 2. Examples -------- >>> from discrimintools.datasets import load_heart >>> from discrimintools import GFALDA >>> D = load_heart("subset") # load subset data >>> y, X = D["disease"], D.drop(columns=["disease"]) # split into X and y >>> clf = GFALDA(n_components=5) >>> clf.fit(X,y) GFALDA(n_components=5) """ if element == "train": heart = read_excel(DATASETS_DIR/"heart.xlsx",sheet_name="Feuil1",header=0).query("status == 'train'").drop(columns=["status"]) elif element == "test": heart = read_excel(DATASETS_DIR/"heart.xlsx",sheet_name="Feuil1",header=0).query("status == 'test'").drop(columns=["status"]) elif element == "subset": heart = read_excel(DATASETS_DIR/"heart.xlsx",sheet_name="Feuil2",header=0) else: raise ValueError("'element' should be one of 'train', 'test', 'subset'") #set documentation heart.__doc__ = """ Heart dataset """ return heart