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   源码介绍

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import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
import pandas as pd

TRAIN_URL ="http://download.tensorflow.org/data/iris_training.csv"
train_path = tf.keras.utils.get_file (" iris_trainning.csV ", TRAIN_URL )

COLUMN_NAMES =['SepalLength','SepalWidth','PetalLength','PetalWidth','Species']
df_iris = pd.read_csv(train_path, names = COLUMN_NAMES, header =0)
iris = np.array( df_iris )

fig = plt.figure ('Iris Data', figsize =(15,15))
fig.suptitle ("Anderson's Iris Data Set\n( Bule -> Setosa | Red -> Versicolor | Green -> Virginica )", fontsize=20)

for i in range (4):
    for j in range (4):
        plt.subplot (4,4,4*i ( j 1))
        if ( i == j ):
            plt.hist(iris[:, i], align='mid', color='blue', edgecolor='black')
        else :
            plt.scatter( iris [:, j ], iris [:, i ], c = iris [:,4], cmap ='brg')
        if (i==0):
            plt.title ( COLUMN_NAMES[j])
           
        if ( j ==0):
            plt.ylabel ( COLUMN_NAMES[i])
plt.show ()