Box画法笔记
import pandas as pd normal_sample = np.random.normal(loc=0.0, scale=1.0, size=10000) random_sample = np.random.random(size=10000) gamma_sample = np.random.gamma(2, size=10000) df = pd.DataFrame({'normal': normal_sample, 'random': random_sample, 'gamma': gamma_sample})
df.describe()
2.作图
plt.figure() # create a boxplot of the normal data, assign the output to a variable to supress output _ = plt.boxplot(df['normal'], whis='range')
3. 显示三列
# clear the current figure plt.clf() # plot boxplots for all three of df's columns _ = plt.boxplot([ df['normal'], df['random'], df['gamma'] ], whis='range')
4.
import mpl_toolkits.axes_grid1.inset_locator as mpl_il plt.figure() plt.boxplot([ df['normal'], df['random'], df['gamma'] ], whis='range') # overlay axis on top of another ax2 = mpl_il.inset_axes(plt.gca(), width='60%', height='40%', loc=2) ax2.hist(df['gamma'], bins=100) ax2.margins(x=0.5)
5. y坐标标记转换位置
# switch the y axis ticks for ax2 to the right side ax2.yaxis.tick_right()
6. whis的妙用
# if `whis` argument isn't passed, boxplot defaults to showing 1.5*interquartile (IQR) whiskers with outliers plt.figure() _ = plt.boxplot([ df['normal'], df['random'], df['gamma'] ] )
