机器学习测试笔记（7）——可视化

# coding:utf-8
import numpy asnp
import pandas aspd
importmatplotlib.pyplot as plt#pip3 install matplotlib
importseaborn as sns#pip3 install seaborn

defbroken_line():
    s = pd.Series(np.random.randn(20).cumsum())
    s.plot(style='o-',xlim=[0,22],grid=True)
    plt.show()
    df =pd.DataFrame(np.random.randn(10,3).cumsum(0),
                      columns = ['A','B','C'],
                      index =np.arange(0,100,10))
    df.plot()
    plt.show()

def Histogram():
    flag,axes = plt.subplots(2,1)
    s =pd.Series(np.random.randn(10),index=list('ABCDEFGHIJ'))
    s.plot.bar(ax=axes[0])#纵向柱状图
    s.plot.barh(ax=axes[1])#横向柱状图
    plt.show()
    flag,axes = plt.subplots(2,1)
    df = pd.DataFrame(np.random.randn(6,3),
                      index = list('abcdef'),
                      columns =list('ABC'))                    
    df.plot.bar(ax=axes[0])
    df.plot.barh(ax=axes[1],stacked=True)#stacked=True表示生成堆积柱状图
    plt.show()

def density_map():
    flag,axes = plt.subplots(2,1)
    s = pd.Series(np.random.randn(100))
    s.plot.hist(ax=axes[0])#直方图
    s.plot.density(ax=axes[1])#密度图
#C:\Users\xiang>pip3 install scipy
    plt.show()
    s = pd.Series(np.random.normal(0,1,100))
    sns.distplot(s,color='g')
    plt.show()

defscatter_diagram():
    df = pd.DataFrame(np.random.randn(100,3),
                      columns = list('ABC'))
    sns.regplot('A','B',data=df)#散点图
    plt.show()
    sns.pairplot(df,diag_kind='kde')#散布图
    plt.show()

if __name__=="__main__":
    broken_line()
    Histogram()
    density_map()
    scatter_diagram()