[英]How to add a marker from a different column to a seaborn pandas barplot
I have the following dataset, code and plot:我有以下数据集、代码和 plot:
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
data = [['tom', 10,15], ['matt', 13,10]]
df3 = pd.DataFrame(data, columns = ['Name', 'Attempts','L4AverageAttempts'])
f,ax = plt.subplots(nrows=1,figsize=(16,9))
sns.barplot(x='Attempts',y='Name',data=df3)
plt.show()
How can get a marker of some description (dot, *, shape, etc) to show that tom
has averaged 15 (so is below his average) and matt
has averaged 10 so is above average.如何获得某种描述的标记(点、*、形状等)以显示
tom
的平均得分为 15(因此低于他的平均水平), matt
的平均得分为 10,因此高于平均水平。 So a marker basxed off the L4AverageAttempts
value for each person.因此,一个标记会根据每个人的
L4AverageAttempts
值进行标记。
I have looked into axvline
but that seems to be only a set number rather than a specific value for each y axis category.我研究了
axvline
但这似乎只是一个设定的数字,而不是每个 y 轴类别的特定值。 Any help would be much appreciated!任何帮助将非常感激! thanks!
谢谢!
You can simply plot a scatter plot on top of your bar plot using L4AverageAttempts
as the x value:您可以简单地 plot 散布 plot 在您的酒吧 plot 顶部使用
L4AverageAttempts
作为 x 值:
You can use seaborn.scatterplot for this.您可以为此使用seaborn.scatterplot 。 Make sure to set the
zorder
parameter so that the markers appear on top of the bars.确保设置
zorder
参数,以便标记出现在条形顶部。
import seaborn as sns
import pandas as pd
data = [['tom', 10,15], ['matt', 13,10]]
df3 = pd.DataFrame(data, columns = ['Name', 'Attempts','L4AverageAttempts'])
f,ax = plt.subplots(nrows=1,figsize=(16,9))
sns.barplot(x='Attempts',y='Name',data=df3)
sns.scatterplot(x='L4AverageAttempts', y="Name", data=df3, zorder=10, color='k', edgecolor='k')
plt.show()
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