from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
import mglearn
import pandas as pd
import matplotlib.pyplot as plt

iris_dataset = load_iris()
X_train, X_test, y_train, y_test = train_test_split(
 iris_dataset['data'], iris_dataset['target'], random_state=0)

iris_dataframe = pd.DataFrame(X_train, columns=iris_dataset.feature_names)
grr = pd.plotting.scatter_matrix(iris_dataframe, c=y_train, figsize=(15, 15),
                                 marker='X', hist_kwds={'bins': 20}, s=60,
                                 alpha=.8, cmap=mglearn.cm3)
plt.show()

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
import mglearn
import pandas as pd
import matplotlib.pyplot as plt

iris_dataset = load_iris()
X_train, X_test, y_train, y_test = train_test_split(
 iris_dataset['data'], iris_dataset['target'], random_state=0)

iris_dataframe = pd.DataFrame(X_train, columns=iris_dataset.feature_names)
grr = pd.plotting.scatter_matrix(iris_dataframe, c=y_train, figsize=(15, 15),
                                 marker='X', hist_kwds={'bins': 20}, s=60,
                                 alpha=.8, cmap=mglearn.cm3)
plt.show()
