In [48]:

    

%matplotlib inline

import numpy as np
import matplotlib.pyplot as plt
from sklearn import datasets
from sklearn import svm

iris = datasets.load_iris()


    

In [10]:

    

features = iris.data
target = iris.target
target_names = iris.target_names
labels = target_names[target]


    

In [41]:

    

iris_list = []
for i in range(len(features)):
    iris_list.append([labels[i], features[i]])


    

In [58]:

    

setosa_x = []
setosa_y = []
virginica_x = []
virginica_y = []
versicolor_x = []
versicolor_y = []

for i in range(len(iris_list)):
    if iris_list[i][0] == 'setosa':
        setosa_x.append(iris_list[i][1][1])
        setosa_y.append(iris_list[i][1][2])
    elif iris_list[i][0] == 'virginica':
        virginica_x.append(iris_list[i][1][1])
        virginica_y.append(iris_list[i][1][2])
    else:
        versicolor_x.append(iris_list[i][1][1])
        versicolor_y.append(iris_list[i][1][2])

plt.plot(setosa_x, setosa_y, 'ro')
plt.plot(virginica_x, virginica_y, 'bo')
plt.plot(versicolor_x,versicolor_y, 'go')


    

    
Out[58]:





[<matplotlib.lines.Line2D at 0x11d26d860>]






    

In [22]:

    

print


    

    
Out[22]:





'setosa'

In [52]:

    

target_names


    

    
Out[52]:





array(['setosa', 'versicolor', 'virginica'], 
      dtype='<U10')

In [ ]:

    

etosa_x.append(iris_list[i][1][1])
        setosa_y.append(iris_list[i][1][2])