作业七

import numpy as np
from sklearn.datasets import load_iris

# #鸢尾花数据集
data=load_iris()
print(data)
print(type(data))
print(data.keys(),data.feature_names)
iris=data.data
print(iris)
petal_length=iris[:,2]
print(petal_length)
print("平均值",np.mean(petal_length))
print("最大值",np.max(petal_length))
print("最小值",np.min(petal_length))
print("标准差",np.std(petal_length))
print("中位数",np.median(petal_length))

#np.random.randn()产生一个正态分布的随机数组，并显示出来。
import numpy as np
rand_data=np.random.randn(1,5)
print(rand_data)
#np.random.normal()产生一个正态分布的随机数组，并显示出来。
rand_data1=np.random.normal(1,5)
print(rand_data1)

#numpy随机数
import numpy as np
print("数组",np.arange(5))
print(np.array([1,10]))
print(np.arange(0,60,5).reshape(3,4))
print(np.linspace(0,20)) #在指定的间隔内返回均匀间隔的数字

print(np.random.random(10)) #(0,1)以内10个随机浮动数
print(np.random.randint(1,100,[5,5])) #(1,100)以内5行5列随机整数
print(np.random.rand(2,3)) #产生2行3列均匀分布随机数组
print(np.random.randn(3,3)) #3行3列正态分布随机数据

#显示鸢尾花花瓣长度的正态分布图，曲线图，散点图。
import numpy as np
from sklearn.datasets import load_iris
import matplotlib.pyplot as plt

data=load_iris()
print(data)
print(type(data))
print(data.keys(),data.feature_names)
iris=data.data
print(iris)
petal_length=iris[:,2]
print(petal_length)

mu=np.mean(petal_length) #期望
sigma=np.std(petal_length) #标准差
num=10000

rand_data=np.random.normal(mu,sigma,num)
print(np.mean(petal_length),np.std(petal_length),np.median(petal_length))
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.plot(np.linspace(0,150,num=150),petal_length,"r")
# plt.scatter(np.linspace(0,150,num=150),petal_length,alpha=0.5,marker="x")
print(plt.show())