为 seaborn FacetGrid distplots 添加均值和可变性 [英] Add mean and variability to seaborn FacetGrid distplots

问题描述

向 seaborn FacetGrid 中的每个直方图添加代表均值(或其他集中趋势度量)的点和可变性度量(例如，标准偏差或置信区间)的最佳方法是什么?

结果应该类似于

(不知道为什么 0.01 稍微向右移动...)

What is the best way to add a point representing the mean (or another measure of central tendency) and a measure of variability (e.g., standard deviation or confidence interval) to each histogram in a seaborn FacetGrid?

The result should look similar to the figure shown here, but with a mean/SD in each of the FacetGrid subplots. This is a related question for the non-FacetGrid case.

解决方案

Based on @mwaskom's comment, here is one possible solution (using boxplot, analogous for pointplot):

tips = sns.load_dataset("tips")

sns.set(font_scale=1.3)

def dist_boxplot(x, **kwargs):
    ax = sns.distplot(x, hist_kws=dict(alpha=0.2))
    ax2 = ax.twinx()
    sns.boxplot(x=x, ax=ax2)
    ax2.set(ylim=(-5, 5))

g = sns.FacetGrid(tips, col="sex")
g.map(dist_boxplot, "total_bill");

(Not sure why the 0.01 is shifted slightly rightwards...)

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