How to do it...

1. Let's get the data sorted first:

from sklearn import datasets
import numpy as np
iris = datasets.load_iris()
 
X = iris.data
y = iris.target

1. Place X and y, all of the numerical data, side-by-side. Create an encoder with scikit-learn to handle the category of the y column:

from sklearn import preprocessing
cat_encoder = preprocessing.OneHotEncoder()
cat_encoder.fit_transform(y.reshape(-1,1)).toarray()[:5]

array([[ 1.,  0.,  0.],
       [ 1.,  0.,  0.],
       [ 1.,  0.,  0.],
       [ 1.,  0.,  0.],
       [ 1.,  0.,  0.]])