如何绘制这种图形（误差线）？

Question

I have a dataframe:

import pandas as pd
import numpy as np

df = pd.read_csv(r'https://exploratory.io/data/kanaugust/2016-California-Election-Data-oTv4Hgd1UT/2016%20California%20Election%20Data.csv')

df['cluster'] = [3, 3, 1, 2, 1, 1, 3, 1, 1, 2, 1, 3, 2, 1, 1, 1, 2, 1, 3, 1, 3, 1, 3, 2, 1, 2, 3, 3, 2, 2, 1, 1, 2, 2, 2, 2, 2, 3, 2, 2, 3, 3, 3, 3, 1, 1, 1, 2, 3, 2, 1, 1, 1, 1, 1, 2, 3, 1]

df = df.drop(columns=['COUNTY_NAME', 'PARTY_NAME']).groupby('cluster').agg(['mean', 'std'])
df

I would like to make graph of it, like this one:

For each cluster every line is drawn as line that connects three dots. In the middle is column mean, lower dot is mean - std, and upper mean + std. For example for Ban on Single-use Plastic Bags and cluster 3, lower dot is 0.647902 - 0.065703, dot in the middle is 0.647902, and upper dot is 0.647902 + 0.065703.

On each x position all three clusters should be drawn, each in different color.

matplotlib errorbar could be good for that purpose, but I don't know how to use it to produce the graph as I shown above. Maybe seaborn is good as well?

How to draw this kind of graph?

Answer 1

One way to do so with errorbar :

df = df.drop(columns=['COUNTY_NAME', 'PARTY_NAME']).groupby('cluster').agg(['mean', 'std'])

# change categories to index
new_df = df.T.unstack()

fig, ax = plt.subplots(1,1, figsize=(16,10))
for i in range(1,4):
    ax.errorbar(range(len(new_df)), new_df[new_df.columns[2*i-2]],
                yerr=new_df[new_df.columns[2*i-1]], fmt='x', 
                label=f'Cluster {i}')

ax.set_xticks(range(len(new_df)))
ax.set_xticklabels(new_df.index)
ax.legend()
plt.show()

Output is not perfect, but I leave the detail to you: