#导包import numpy as np# 从sklearn包自带的数据集中读出鸢尾花数据集datafrom sklearn.datasets import load_irisdata = load_iris()# 查看data类型,包含哪些数据print("数据类型:",type(data))print("数据类目:",data.keys())# 取出鸢尾花特征和鸢尾花类别数据,查看其形状及数据类型iris_feature = data.feature_names,data.dataprint("鸢尾花特征:",iris_feature)print("iris_feature数据类型",type(iris_feature))iris_target = data.targetprint("鸢尾花数据类别:",iris_target)print("iris_target数据类型:",type(iris_target))# 取出所有花的花萼长度(cm)的数据sepal_len = np.array(list(len[0] for len in data.data))print("花萼长度:",sepal_len)# 取出所有花的花瓣长度(cm)+花瓣宽度(cm)的数据pental_len = np.array(list(len[2] for len in data.data))pental_len.resize(3,50) #重新分配花瓣长度内存pental_wid = np.array(list(len[3] for len in data.data))pental_wid.resize(3,50) #重新分配花瓣宽度内存iris_lens = (pental_len,pental_wid)print("花瓣长宽:",iris_lens)# 取出某朵花的四个特征及其类别print("特征:",data.data[1])print("类别:",data.target[1])# 将所有花的特征和类别分成三组,每组50个#建立3个相应列表存放数据iris_set = []iris_ver = []iris_vir = []for i in range(0,150): if data.target[i] == 0: Data = data.data[i].tolist() Data.append('setosa') iris_set.append(Data) elif data.target[i] ==1: Data = data.data[i].tolist() Data.append('versicolor') iris_ver.append(Data) else: Data = data.data[i].tolist() Data.append('virginica') iris_vir.append(Data)# 生成新的数组,每个元素包含四个特征+类别datas = (iris_set,iris_ver,iris_vir)print("新的数组:",datas)