在seaborn barplots中调整不同厚度的条形图以用于子图

Question

在一个seaborn水平条形图中，它有两组条形图，其中一组放在另一组上，每个条形图的轴是如何独立控制的？目前，我想根据其中某些实体的出现频率调整条形的厚度。

目前两个条形图都绘制有轴存储在ax1和ax2中。但是我能够仅为ax1（浅蓝色）调整条的厚度，但不能用于ax2（深蓝色。所有条都有均匀的厚度）。我无法弄清楚如何完成ax2的分配以便调整第二组条的条形厚度。

如何获得两个条形图的变长条？

%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")


f, ax = plt.subplots(figsize=(15, 45))
crashes = plotie.groupby('target_wcount').mean()

sns.set_color_codes("pastel")
ax1 = sns.barplot(x="uno", y="indie", orient='h',  data=crashes,
            label="uno", color="b")
sns.set_color_codes("muted")
ax2 = sns.barplot(x="miss", y="indie", orient='h',  data=crashes,
            label="miss", color="b")


for bar, newwidth in zip(ax1.patches, summa):
    bar.set_height(3*newwidth)

for bar, newwidth in zip(ax2.patches, summa):
    bar.set_height(3*newwidth)

sns.despine(left=True, bottom=True)
f.savefig('filea')

Sample For data

    output_wcount   missing_count   match_count     uni     indie   uno     miss
target_wcount                           
49  49.0    39.440000   9.560000    1.0     49  1.0     0.804898
48  48.0    36.730000   11.270000   1.0     48  1.0     0.765208
46  46.0    34.400000   11.600000   1.0     46  1.0     0.747826
45  45.0    33.940000   11.060000   1.0     45  1.0     0.754222
44  44.0    34.630000   9.370000    1.0     44  1.0     0.787045
43  43.0    31.420000   11.580000   1.0     43  1.0     0.730698
42  42.0    31.455000   10.545000   1.0     42  1.0     0.748929
41  41.0    29.630000   11.370000   1.0     41  1.0     0.722683
40  40.0    28.430000   11.570000   1.0     40  1.0     0.710750
39  39.0    27.935556   11.064444   1.0     39  1.0     0.716296

Answer 1

通过使用twinx函数，这可以很容易地解决

%matplotlib inline
import seaborn as sns
import matplotlib.pyplot as plt
sns.set(style="whitegrid")

f, ax = plt.subplots(figsize=(15, 45))
crashes = plotie.groupby('target_wcount').mean() 
sns.set_color_codes("pastel")
ax1 = sns.barplot(x="uno", y="indie", orient='h',  data=crashes,
            label="uno", color="b")
sns.set_color_codes("muted")


ax2 = ax.twinx()


sns.barplot(x="miss", y="indie", orient='h',  data=crashes,
            label="miss", color="b",ax=ax2)


for bar, newwidth in zip(ax1.patches, summa):
    bar.set_height(3*newwidth)

for bar, newwidth in zip(ax2.patches, summa):
    bar.set_height(3*newwidth)

sns.despine(left=True, bottom=True)
f.savefig('filea')