#1.安装scipy，numpy，sklearn包#2.从sklearn包自带的数据集中读出鸢尾花数据集data#3.查看data类型，包含哪些数据import numpyfrom sklearn.datasets import load_irisdata = load_iris()type(data)print(data.keys())

 

4、取出花的特性和类别数据，查看数据类型

data_tgs=data ['target']##鸢尾花特征data_tgsname=data['target_names']##鸢尾花的类别数据data_ts=data_tgsname,data_tgs#鸢尾花特征和鸢尾花的类别数据print(data_ts)#形状print(type(data_ts))#数据类型#4.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#特征iris_feature = data['data']print(iris_feature)#类别数据iris_target = data.target,data.target_namesprint('类型：',iris_target)

#取出所有花的花萼长度sepal_len = numpy.array(list(len[0] for len in data['data']))print('所有长度：',sepal_len)

# 6.取出所有花的花瓣长度(cm)+花瓣宽度(cm)的数据#宽iris_width=numpy.array(list(len[3] for len in data['data']))print(iris_width)# 长iris_length=numpy.array(list(len[2] for len in data['data']))print(iris_length)

#8定义三个列表来存放不同类型花朵的类别data_setosa=[]data_versicolor=[]data_virginica=[]len(data['data'])for i in  range(0,150):    if data['target'][i]==0:        datas=data['data'][i].tolist()        datas.append('setosa')        print(data_setosa.append(datas))    elif data['target'][i]==1:        datas=data['data'][i].tolist()        datas.append('versicolor')        data_versicolor.append(datas)    else:        data1=data['data'][i].tolist()        data1.append('virginica')        data_virginica.append(datas)Go_data=(numpy.array([data_setosa,data_versicolor,data_virginica]))print(Go_data)

 

#计算鸢尾花花瓣长度最大值import numpy as npfrom sklearn.datasets import load_irisdata = load_iris()petal_length=numpy.array(list(len[2]for len in data['data']))print(np.max(petal_length))print(np.mean(petal_length))print(np.std(petal_length))print(np.median(petal_length))np.random.normal(1,5,60)np.random.randn(3,3)#正态分布图import numpy as npimport matplotlib.pyplot as pltmu = 1sigma = 3num = 10000rand_data = np.random.normal(mu, sigma, num)print(rand_data.shape,type(rand_data))count, bins, ignored=plt.hist(rand_data, 30, normed=True)plt.plot(bins, 1/(sigma * np.sqrt(2 * np.pi)) *np.exp( - (bins - mu)**2 / (2 * sigma**2)), linewidth=2, color='r')plt.show()#曲线图plt.plot(np.linspace(0,150,num=150),petal_length,'r')plt.show()#散点图import numpy as npimport matplotlib.pyplot as pltplt.scatter(np.linspace(0,150,num=150),petal_length,alpha=0.5,marker='x')plt.show()