custom errorbars for seaborn catplot plotting bars

[ironv]

pandas 1.5.3 matplotlib 3.7.1 seaborn 0.12.2

My code and part of the data is shown below. I am trying to plot the errorbars precomputed in the dataframe (val_lo,val_hi). It seems that sns.catplot with kind=bar has support using errorbar as mentioned here - how do I get that to work? Or any guidance into how to use matplotlib errorbar?

My datasets have millions of observations, with output from several models which are compared and running 1000bootstrap iterations parallelized using ThreadPool (with 20 threads) takes over an hour. Hence I prefer pre-computing and plotting.

import pandas as pd
import re
import seaborn as sns
from matplotlib.ticker import PercentFormatter

df = pd.DataFrame([
    ['C', 'G1', 'gbt',    'auc', 0.7999, 0.7944, 0.8032],
    ['C', 'G1', 'gbtv2',  'auc', 0.8199, 0.8144, 0.8232],
    ['C', 'G1', 'gbt',  'pr@2%', 0.0883, 0.0841, 0.0909],
    ['C', 'G1', 'gbt', 'pr@10%', 0.0430, 0.0416, 0.0435],
    ['C', 'G2', 'gbt',    'auc', 0.7554, 0.7506, 0.7573],
    ['C', 'G2', 'gbt',  'pr@2%', 0.0842, 0.0795, 0.0872],
    ['C', 'G2', 'gbt', 'pr@10%', 0.0572, 0.0556, 0.0585],
    ['C', 'G3', 'gbt',    'auc', 0.7442, 0.7404, 0.7460],
    ['C', 'G3', 'gbt',  'pr@2%', 0.0894, 0.0836, 0.0913],
    ['C', 'G3', 'gbt', 'pr@10%', 0.0736, 0.0714, 0.0742],
    ['E', 'G1', 'gbt',    'auc', 0.7988, 0.7939, 0.8017],
    ['E', 'G1', 'gbt',  'pr@2%', 0.0810, 0.0770, 0.0832],
    ['E', 'G1', 'gbt', 'pr@10%', 0.0354, 0.0342, 0.0361],
    ['E', 'G1', 'gbtv3','pr@10%',0.0454, 0.0442, 0.0461],
    ['E', 'G2', 'gbt',    'auc', 0.7296, 0.7253, 0.7311],
    ['E', 'G2', 'gbt',  'pr@2%', 0.1071, 0.1034, 0.1083],
    ['E', 'G2', 'gbt', 'pr@10%', 0.0528, 0.0508, 0.0532],
    ['E', 'G3', 'gbt',    'auc', 0.6958, 0.6914, 0.6978],
    ['E', 'G3', 'gbt',  'pr@2%', 0.1007, 0.0961, 0.1030],
    ['E', 'G3', 'gbt', 'pr@10%', 0.0536, 0.0518, 0.0541],
  ], columns=["src","grp","model","metric","val","val_lo","val_hi"])

sns.reset_defaults()
sns.set(style="whitegrid", font_scale=1.)
g = sns.catplot(data=df, x="grp", y="val", hue="model", 
  col="metric", row="src", kind="bar", sharey=False)
for ax in g.axes.flat:
  ax.yaxis.set_major_formatter(PercentFormatter(1))
  if re.search("metric = auc",ax.get_title(),re.IGNORECASE):
    _ = ax.set_ylim((.5,1.))
plt.show()

[mwaskom]

Sorry, catplot does not support precomputed error bars.

[ironv]

In case anybody else runs into this here is an alternative. I really wish catplot supported asymmetric error bars.