重新格式化双向条形图以匹配示例

我生成了这个条形图

使用此代码：

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']*100
column1 = fluid_vp_1_2['margins_vp']*100
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='silver', 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].set(xlim = [100,0])
axes[1].set(xlim = [0,100])

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'$\bf{'+f"{t}"+r'}$' 
                        if t in variableNames else t for t in fluid_vp_1_2['level']]
axes[0].set_yticklabels(formattedyticklabels, ha='center', position=(1.12, 0))

axes[0].tick_params(right = False)

axes[1].tick_params(left = False)
    
fig.tight_layout()
plt.savefig("fluid_vp_1_2.jpg")

plt.show()

但是，我想修改此图表，使其更类似于下面的示例，其中 y 轴标签位于左侧，双向条在中心接触，白色背景，形状更垂直（缩小 x 轴），添加 x 轴标签（“调整后的受访者比例”），但我仍然想保持变量的顺序以及由粗体标题标签引起的条形间隙，例如Volume, MAP, etc.

有小费吗？

您可以进行一些简化/因式分解，以使绘图的样式更容易。但你基本上已经差不多了。只需设置刻度标签并删除图之间的空格即可fig.subplots_adjust(wspace=0)（你必须删除fig.tight_layout()):

from io import StringIO
import matplotlib.pyplot as plt
import pandas as pd

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"""

# building df directly with pandas
fluid_vp_1_2 = pd.read_csv(StringIO(s))
fluid_vp_1_2['margins_fluid'] = fluid_vp_1_2['margins_fluid']*100
fluid_vp_1_2['margins_vp'] = fluid_vp_1_2['margins_vp']*100

# style parameters for all plots
title_format = dict(
    fontsize=18,
    pad=15,
    color='black',
    fontname='DejaVu Sans'
)

plot_params = dict(
    align='center',
    zorder=10,
    legend=None,
    width=0.9
)

grid_params = dict(
    zorder=0,
    axis='x'
)

tick_params = dict(
    left=False,
    which='both'
)

variableNames = {'Volume', 'MAP', 'Exam', 'History', 'Case'}

fig, axes = plt.subplots(figsize=(8,10), ncols=2, sharey=True, facecolor='#eaeaf2')
# removing spaces between plots
fig.subplots_adjust(wspace=0)

# plotting Fluids
fluid_vp_1_2.plot.barh(y='margins_fluid', ax=axes[0], color='dimgray', **plot_params)
axes[0].grid(**grid_params)
axes[0].set_title('Fluids', **title_format)
axes[0].tick_params(**tick_params)

# plotting Vasopressors
fluid_vp_1_2.plot.barh(y='margins_vp', ax=axes[1], color='silver', **plot_params)
axes[1].grid(**grid_params)
axes[1].set_title('Vasopressors', **title_format)
axes[1].tick_params(**tick_params)

# adjust axes
axes[0].invert_xaxis()
plt.gca().invert_yaxis()
axes[0].set(xlim = [100,0])
axes[1].set(xlim = [0,100])

# adding y labels
formattedyticklabels = [rf'$\bf{{{t}}}$' 
                        if t in variableNames else t for t in fluid_vp_1_2['level']]
axes[0].set_yticklabels(formattedyticklabels)

plt.show()

编辑：你可以通过改变来获得“更长”的情节figsize。 输出为figsize=(8,10):