python Iris dataset report shows

SNS Seaborn AS Import 
Import PANDAS AS PD 
Import matplotlib.pyplot AS PLT 
sns.set_style ( 'White', { 'serif-font.sans': [ 'simhei', 'Arial']}) 
from sklearn.datasets load_iris Import 

Data = load_iris () # loading iris data set 
tt = pd.DataFrame (data = data.data, columns = data.feature_names) # converts the data into data sets Panda 
TT [ 'Species'] = # data.target the iris type was added to the dataset 
data = TT 
# in order to facilitate viewing of the column names into Chinese 
data.rename (columns = { 'sepal length (cm)': " sepals", 
                     "sepal width (cm & lt)": "sepals wide ", 
                     " petal length (cm & lt) ":" petal length ", 
                     " width petal (cm & lt) ":" petal width ", 
                     " Species ":"Type"}, InPlace = True) 

kind_dict = { 
    0: "Mountain Iris", 
    1: "Iris versicolor"
    2: "Virginia Iris" 
} 
Data [ "type"] = data [ "type"] .map (kind_dict) 
content data.head () # dataset follows 

sns.pairplot (data)