我正在使用以下代码创建小提琴图:
import seaborn as sns
ax = sns.violinplot(data=df[['SoundProduction','SoundForecast','diff']])
ax.set_ylabel("Sound power level [dB(A)]")
它给了我以下结果:
有什么方法可以在第二个y轴上绘制diff
以便使三个系列都清晰可见?
还可以在两个系列之间绘制一条垂直线吗?在这种情况下,我希望在SoundForecast
和diff
之间绘制一条垂直线,将它们绘制在两个不同的轴上。
答案 0 :(得分:1)
您可以使用多个子图来实现这一点,这些子图可以使用plt.subplots轻松设置(请参阅更多subplot examples)。
这使您可以按适当的比例显示分布,而不会“浪费”显示空间。 seaborn的大多数(全部?)绘图功能都接受ax=
参数,因此您可以设置要绘制绘图的轴。轴之间也有明显的间距。
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
# generate some random distribution data
n = 800 # samples
prod = 95 + 5 * np.random.beta(0.6, 0.5, size=n); # a bimodal distribution
forecast = prod + 3*np.random.randn(n) # forecast is noisy estimate around the "true" production
diff = prod-forecast # should be with mu 0 sigma 3
df = pd.DataFrame(np.array([prod, forecast, diff]).T, columns=['SoundProduction','SoundForecast','diff']);
# set up two subplots, with one wider than the other
fig, ax = plt.subplots(1,2, num=1, gridspec_kw={'width_ratios':[2,1]})
# plot violin distribution estimates separately so the y-scaling makes sense in each group
sns.violinplot(data=df[['SoundProduction','SoundForecast']], ax=ax[0])
sns.violinplot(data=df[['diff']], ax=ax[1])