Seaborn如何把两张数据源不同的图合并？

French_movie_genre_count = French_movies['Genre_count']
non_French_movies_genre_count = non_French_movies['Genre_count']
fig, ax = plt.subplots(1,2)
plt.figure(figsize=(20, 16))
sns.countplot(x = French_movie_genre_count, color = 'blue', ax = ax[0])
sns.countplot(x = non_French_movies_genre_count, color = 'green', ax=ax[1])
fig.show()

如何把这来个图放到一个表里啊？
把下面这两个分开的图 合并到一个图里面 最好能归一化 变成百分比

先转换一下数据，换算成百分比，使用matplotlib的函数直接绘制，将主轴设置成百分比刻度,代码这样写，：

import pandas as pd 
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import matplotlib.ticker as mtick
French_movies=pd.read_csv('French_movies.csv')
non_French_movies = pd.read_csv('non_French_movies.csv')
French_movie_genre_count = French_movies['Genre_count'].apply(
    lambda x: x/French_movies['Genre_count'].sum())
non_French_movies_genre_count = non_French_movies['Genre_count'].apply(
    lambda x: x/non_French_movies['Genre_count'].sum())
df = pd.DataFrame({'french_movie_count': French_movie_genre_count, 'non_french_movie_count': non_French_movies_genre_count})
print(df)
ax=df.plot(kind='bar',
          figsize=(12, 6),
          title='French_movies and non_French_movies',
        rot=0)
ax.yaxis.set_major_formatter(mtick.PercentFormatter(xmax=1))
plt.show()

运行效果图：

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