我有以下一行：
genre_df.groupby(['release_year', 'genres']).vote_average.mean()
这给了我以下内容：
release_year genres
1960 Action 6.950000
Adventure 7.150000
Comedy 7.900000
Drama 7.600000
Fantasy 7.300000
History 6.900000
Horror 8.000000
Romance 7.600000
Science Fiction 7.300000
Thriller 7.650000
Western 7.000000
1961 Action 7.000000
Adventure 6.800000
Animation 6.600000
Comedy 7.000000
Crime 6.600000
Drama 7.000000
Family 6.600000
History 6.700000
Music 6.600000
Romance 7.400000
War 7.000000
...
我想看到的是按发行年份和流派分组的df，但先按最高投票平均数排序。
又名：
release_year genres
1960 Horror 8.000000
Comedy 7.900000
Action 6.950000
Thriller 7.650000
Drama 7.600000
Romance 7.600000
Fantasy 7.300000
Science Fiction 7.300000
Adventure 7.150000
Western 7.000000
History 6.900000
如何实现？
答案 0 :(得分：2)
0.23.0+的解决方案-首先用to_frame创建一个列DataFrame，然后创建sort_values：
df = df.to_frame().sort_values(['release_year','vote_average'], ascending=[True, False])
print (df)
vote_average
release_year genres
1960 Horror 8.00
Comedy 7.90
Thriller 7.65
Drama 7.60
Romance 7.60
Fantasy 7.30
Science Fiction 7.30
Adventure 7.15
Western 7.00
Action 6.95
History 6.90
1961 Romance 7.40
Action 7.00
Comedy 7.00
Drama 7.00
War 7.00
Adventure 6.80
History 6.70
Animation 6.60
Crime 6.60
Family 6.60
Music 6.60
对于较旧版本的熊猫，必须reset_index和set_index：
df = (df.reset_index()
.sort_values(['release_year','vote_average'], ascending=[True, False])
.set_index(['release_year','genres']))
答案 1 :(得分：0)
尝试一下：
genre_df = genre_df.reset_index()
genre_df.sort_values(['vote_average'],ascending=False)