可以通过以下方式创建Seaborn barplot:
import pandas as pd
import seaborn as sns
df = pd.DataFrame(
[
['variable_a', 0.656536, 0.054560],
['variable_b', 0.425124, 0.056104],
['variable_c', 0.391201, 0.049393],
['variable_d', 0.331990, 0.032777],
['variable_e', 0.309588, 0.027449],
],
columns = [
'index',
'mean',
'statistical_uncertainty'
]
)
df.index = df['index']
del df['index']
df
p = sns.barplot(df["mean"], df.index);
plt.show;
如何将不确定性条形图添加到条形图中?这似乎是一种有前途的方法,但是我不确定如何进行:https://matplotlib.org/api/_as_gen/matplotlib.axes.Axes.errorbar.html
答案 0 :(得分:2)
您可以使用图解上方的plt.errorbar
绘制误差线:
p = sns.barplot(df["mean"], df.index)
# to enhance visibility of error bars,
# you can draw them twice with different widths and colors:
p.errorbar(y=range(len(df)),
x=df['mean'],
xerr=df.statistical_uncertainty,
fmt='none',
linewidth=3, c='w')
p.errorbar(y=range(len(df)),
x=df['mean'],
xerr=df.statistical_uncertainty,
fmt='none',
c='r')
plt.show;