1 import pandas as pd 2 normal_sample = np.random.normal(loc=0.0, scale=1.0, size=10000) 3 random_sample = np.random.random(size=10000) 4 gamma_sample = np.random.gamma(2, size=10000) 5 6 #创建新的数据格式 7 df = pd.DataFrame({'normal': normal_sample, 8 'random': random_sample, 9 'gamma': gamma_sample}) 10 11 df.describe()
1 plt.figure() 2 # 画normal的箱型图 3 _ = plt.boxplot(df['normal'], whis='range') 4 5 6 # 清空图像 7 plt.clf() 8 # 同时画normal,random,gamma的箱型图 9 _ = plt.boxplot([ df['normal'], df['random'], df['gamma'] ], whis='range')
1 plt.figure() 2 _ = plt.hist(df['gamma'], bins=100)
1 import mpl_toolkits.axes_grid1.inset_locator as mpl_il 2 3 plt.figure()
现在图上画出normal,random,gamma的箱型图 4 plt.boxplot([ df['normal'], df['random'], df['gamma'] ], whis='range') 5 # 在图的右上角得到一块区域画拟合图 6 ax2 = mpl_il.inset_axes(plt.gca(), width='60%', height='40%', loc=2) 7 ax2.hist(df['gamma'], bins=100) 8 ax2.margins(x=0.5)
1 # 把左边的y轴坐标的标注移到右边 2 ax2.yaxis.tick_right()
1 # if `whis` argument isn't passed, boxplot defaults to showing 1.5*interquartile (IQR) whiskers with outliers 2 plt.figure() 3 _ = plt.boxplot([ df['normal'], df['random'], df['gamma'] ] )
