import numpy
from sklearn.datasets import load_iris #从sklearn包自带的数据集中读出鸢尾花数据集data
iris_data = load_iris()
# 查看data类型,包含哪些数据
print("数据类型: ", type(iris_data))
print("包含数据: ", iris_data.keys())  # 看包含哪些数据

  

iris_feature = data.feature_names,data.data
#鸢尾花特征:
print(iris_feature)
#iris_feature数据类型
print(type(iris_feature))
iris_target = data.target
#鸢尾花数据类别:
print(iris_target)
#iris_target数据类型:
print(type(iris_target))

sepal_len = np.array(list(len[0] for len in data.data))
#取出所有花的花萼长度(cm)的数据
print(sepal_len)

  

# 6.取出所有花的花瓣长度(cm)+花瓣宽度(cm)的数据
petal_len = numpy.array(list(len[2] for len in iris_data['data']))  # 取花瓣长
petal_len.resize(5, 30)
petal_wid = numpy.array(list(wid[3] for wid in iris_data['data']))  # 取花瓣宽
petal_wid.resize((5, 30))
petal_len_wid = numpy.array(dict(length=petal_len, width=petal_wid))  # 形成新数组
print("花瓣长宽: ", petal_len_wid)

  

# 取出某朵花的四个特征及其类别
print("某朵花数据: ", iris_data['data'][0], iris_data['target'][0])

  

iris_one = []
iris_two = []
iris_three = []

for i in range(0,150):
    if  data.target[i] == 0:
        Data = data.data[i].tolist()
        Data.append('setose')
        iris_one.append(Data)
    elif data.target[i] ==1:
        Data = data.data[i].tolist()
        Data.append('color')
        iris_two.append(Data)
    else: 
        Data = data.data[i].tolist()
        Data.append('flower')
        iris_three.append(Data)

  

# 生成新的数组,每个元素包含四个特征+类别
iris_result = numpy.array([iris_setosa, iris_versicolor, iris_virginica])

print("分类结果", iris_result)