也许这会帮助你开始，我不知道如何用格式将类别居中（它基本上是在文本周围 Package 乳胶，似乎你失去了理由时，你这样做）。
它也可能有助于发挥周围的主要和次要刻度，例如设置变量名称为主要刻度和水平为次要刻度，然后你可以删除刻度本身的主要，但保留它们的次要刻度。

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

s = """level,margins_fluid,margins_vp
volume,0,0
1L,0.718,0.690
2L,0.501,0.808
5L,0.181,0.920
MAP,0,0
64,0.434,0.647
58,0.477,0.854
52,0.489,0.904
Exam,0,0
dry,0.668,0.713
euvolemic,0.475,0.798
wet,0.262,0.893
history,0,0
COPD,0.506,0.804
Kidney,0.441,0.778
HF,0.450,0.832
Case,0,0
1 (PIV),0.435,0.802
2 (CVC),0.497,0.809"""

data = np.array([a.split(',') for a in s.split("\n")])

fluid_vp_1_2 = pd.DataFrame(data[1:], columns=data[0])
fluid_vp_1_2['margins_fluid'] = fluid_vp_1_2['margins_fluid'].apply(float)
fluid_vp_1_2['margins_vp'] = fluid_vp_1_2['margins_vp'].apply(float)
fluid_vp_1_2

variableNames = {'volume', 'MAP', 'Exam', 'history', 'Case'}

font_color = '#525252'
hfont = {'fontname':'DejaVu Sans'}
facecolor = '#eaeaf2'
index = fluid_vp_1_2.index#['level']
column0 = fluid_vp_1_2['margins_fluid']
column1 = fluid_vp_1_2['margins_vp']
title0 = 'Fluids'
title1 = 'Vasopressors'

fig, axes = plt.subplots(figsize=(10,5), facecolor=facecolor, ncols=2, sharey=True)
axes[0].barh(index, column0, align='center', color='dimgray', zorder=10)
axes[0].set_title(title0, fontsize=18, pad=15, color='black', **hfont)
axes[1].barh(index, column1, align='center', color='lightgray', zorder=10)
axes[1].set_title(title1, fontsize=18, pad=15, color='black', **hfont)
# If you have positive numbers and want to invert the x-axis of the left plot
axes[0].invert_xaxis() 
# To show data from highest to lowest
plt.gca().invert_yaxis()

axes[0].yaxis.tick_right()
axes[0].set_yticks(range(len(fluid_vp_1_2)))
maxWordLength = fluid_vp_1_2['level'].apply(lambda x: len(x)).max()
formattedyticklabels = [r'$\bf{'+f"{t.rjust(maxWordLength)}"+r'}$' if t in variableNames else t.rjust(maxWordLength) for t in fluid_vp_1_2['level']]
axes[0].set_yticklabels(formattedyticklabels)
    
fig.tight_layout()

plt.show()