\!hrSSKrSSKr\RR \5urr\RR\SS5r Sr g)Ndatazwine.csvc[R"[SS9nUSS2SS24USS2S4p!UR[5nX4$)aWine dataset. Source : https://archive.ics.uci.edu/ml/datasets/Wine Number of samples : 178 Class labels : {0, 1, 2}, distribution: [59, 71, 48] Dataset Attributes: - 1) Alcohol - 2) Malic acid - 3) Ash - 4) Alcalinity of ash - 5) Magnesium - 6) Total phenols - 7) Flavanoids - 8) Nonflavanoid phenols - 9) Proanthocyanins - 10) Color intensity - 11) Hue - 12) OD280/OD315 of diluted wines - 13) Proline Returns -------- X, y : [n_samples, n_features], [n_class_labels] X is the feature matrix with 178 wine samples as rows and 13 feature columns. y is a 1-dimensional array of the 3 class labels 0, 1, 2 Examples ----------- For usage examples, please see https://rasbt.github.io/mlxtend/user_guide/data/wine_data ,) delimiterN)nploadtxt DATA_PATHastypeint)tmpXys dC:\Users\julio\OneDrive\Documentos\Trabajo\Ideas Frescas\venv\Lib\site-packages\mlxtend/data/wine.py wine_datarsDH **Y# .C q#2#v;ArE q  A 4K) osnumpyrpathsplit__file__this_dir this_filenamejoinr rrrrs? ''--1- GGLL6: 6 'r