I am studying different variables. I want to plot the results with the stadnard error.

I use the filter function because depending on what I want to analyse, I am interested in just plotting mineral, or just plotting one material...etc. I mention this because it is important for the error bars. With seaborn it is not possible to plot the error bars (I used the raw data and I introduced in the seaborn function cd='', but it does not work. Therefore, I have calculated the mean and st error in excel and I plot that directly. The table is the result of the average and the st error that I use in the script. If I add ci in the seaborn, does not do anything. Therefore I want to add it externally in a second line. But I have tried with ax.errorbar(), I cant either plot the st error.

import os
import io
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FormatStrFormatter
Results = pd.read_excel('results.xlsx',sheet_name='Sheet1',usecols="A:J")
df=pd.DataFrame(Results)

RR_filtered=Results[(Results['Mineral ']=='IC60') | (Results['Mineral ']=='MinFree')]
R_filtered=RR_filtered[(Results['Material']=='A')]

palette = ["#fdae61","#abd9e9"]
sns.set_palette(palette)
ax1=sns.relplot( data=R_filtered,x="Impeller speed (rpm)", y="Result",col="Media size ",hue="Mineral content (g/g fibre)",
palette=palette,size="Media size ",sizes=(50, 200))

R2_filtered=RR_filtered[(Results['Material']=='B')]
ax2=sns.relplot( data=R2_filtered,x="Impeller speed (rpm)", y="Result",col="Media size ",hue="Mineral content (g/g fibre)",
palette=palette,size="Media size ",sizes=(50, 200))
plt.show()

• If the error bar should be over each value, pass 'Reslt' to plt.errorbar, and don't add the 'mean_' column

g = sns.relplot(data=filtered, x="Impeller speed (rpm)", y="Result", col="Media size", row='Material', hue="Mineral content (g/g fibre)", size="Media size", sizes=(50, 200))
g.map(plt.errorbar, "Impeller speed (rpm)", "Result", "ster", marker="none", color='r', ls='none')