Source code for discrimintools.datasets.load_alcools

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

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

[docs] def load_alcools(element="train"): """ Alcools dataset Parameters ---------- element : str, default = 'train' The dataset to load. Possible values are: - 'train' for training dataset. - 'test' for testing dataset. Returns ------- alcools : DataFrame of shape (n_samples, n_columns) The alcools 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_alcools >>> from discrimintools import DISCRIM >>> D = load_alcools("train") # load training data >>> y, X = D["TYPE"], D.drop(columns=["TYPE"]) # split into X and y >>> clf = DISCRIM() >>> clf.fit(X,y) DISCRIM(priors='prop') """ if element == "train": alcools = read_excel(DATASETS_DIR/"alcools.xlsx",header=0,sheet_name="Feuil1") elif element == "test": alcools = read_excel(DATASETS_DIR/"alcools.xlsx",header=0,sheet_name="Feuil2") else: raise ValueError("'element' should be one of 'train', 'test'.") #set cocumentation alcools.__doc__ = """ Alcools dataset """ return alcools