箱图中的自动(晶须敏感)ylim [英] Automatic (whisker-sensitive) ylim in boxplots

问题描述

在绘制带有熊猫的数据框的列时，例如

When plotting columns of a dataframe with pandas, e.g.

  df.boxplot()

yaxis的自动调整会导致绘图中大量未使用的空间.我想知道这是否是因为数据框的点超过了箱线图的晶须(但由于某些原因，未显示异常值).如果是这种情况，哪种自动调整ylim的好方法是什么，以便在绘图中没有太多的空白空间?

the automatic adjustment of the yaxis can lead to a large amount of unused space in the plot. I wonder if this is because the dataframe has points that exceed the boxplot whiskers (but for some reason the outliers aren't displayed). If that is the case, what would be a good way to automatically adjust ylim so that there isn't so much empty space in the plot?

推荐答案

我认为，seaborn风格和matplotlib绘制箱形图的方式的结合在这里隐藏了您的异常值.

I think a combination of the seaborn style and the way matplotlib draws boxplots is hiding your outliers here.

如果我生成一些偏斜的数据

If I generate some skewed data

import seaborn as sns
import pandas as pd
import numpy as np

x = pd.DataFrame(np.random.lognormal(size=(100, 6)),
             columns=list("abcdef"))

然后在数据框上使用boxplot方法，我看到类似的内容

And then use the boxplot method on the dataframe, I see something similar

x.boxplot()

但是，如果更改用于绘制异常值的符号，则会得到

But if you change the symbol used to plot outliers, you get

x.boxplot(sym="k.")

或者，您可以使用seaborn的boxplot函数，该函数执行相同的操作，但具有一些美观的外观:

Alternatively, you can use the seaborn boxplot function, which does the same thing but with some nice aesthetics:

sns.boxplot(x)

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