对 Seaborn 和 Barplot 使用预先计算的误差线

Question

我有一个 dataframe 我已经预先计算了一组特定值的平均值和标准偏差。 数据框的片段以及如何创建它如下所示：

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

channel = ["Red", "Green", "Blue", "Red", "Green", "Blue", "Red", "Green", "Blue"]
average= [83.438681, 36.512924, 17.826646, 83.763724, 36.689707, 17.892932, 84.747069, 37.072383, 18.070416]
sd = [7.451285, 3.673155, 1.933273, 7.915111, 3.802536, 2.060639, 7.415741, 3.659094, 2.020355]
conc = ["0.00", "0.00", "0.00", "0.25", "0.25", "0.25", "0.50", "0.50", "0.50"]

df = pd.DataFrame({"channel": channel,
                  "average": average,
                  "sd" : sd,
                  "conc": conc})

order = ["0.00", "0.25", "0.50"]
sns.barplot(x="conc", y="average", hue="channel", data=df, ci=None, order=order);

运行上面的代码会生成如下所示的图像：

我有一列sd具有预先计算的标准偏差，我想在绘制的每个条形图的上方和下方添加误差线。 但是我无法弄清楚该怎么做。

任何帮助将不胜感激。

Answer 1

昨天遇到这个错误。 在 seaborn 中，我相信您不能根据预先确定的错误添加错误栏。 最简单的解决方案是在 seaborn 上绘制 matplotlib 条形图。

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

channel = ["Red", "Green", "Blue", "Red", "Green", "Blue", "Red", "Green", "Blue"]
average= [83.438681, 36.512924, 17.826646, 83.763724, 36.689707, 17.892932, 84.747069, 37.072383, 18.070416]
sd = [7.451285, 3.673155, 1.933273, 7.915111, 3.802536, 2.060639, 7.415741, 3.659094, 2.020355]
conc = ["0.00", "0.00", "0.00", "0.25", "0.25", "0.25", "0.50", "0.50", "0.50"]

df = pd.DataFrame({"channel": channel,
                  "average": average,
                  "sd" : sd,
                  "conc": conc})

order = ["0.00", "0.25", "0.50"]
sns.barplot(x="conc", y="average", hue="channel", data=df, ci=None, 
            order=order)


conc2=[0,0,0,1,1,1,2,2,2]
width = .25
add = [-1*width, 0 , width, -1*width, 0 , width, -1*width, 0 , width,]
x = np.array(conc2)+np.array(add)

plt.errorbar(x = x, y = df['average'],
            yerr=df['sd'], fmt='none', c= 'black', capsize = 2)
plt.show()

有点愚蠢但有效！