Question

我需要获得'ma'和'young'观看的top1和top2评分。在这里我只需要专门定义我的值，而不是使用group by的列。

数据：

gender  age rating
ma  young   PG
fe  young   PG
ma  adult   PG
fe  adult   PG
ma  young   PG
fe  young   PG
ma  adult   R
fe  adult   R
ma  young   R
fe  young   R

代码：

top1 = df.groupby(['ma','young']])['rating'].apply(lambda x: x.value_counts().index[0])
top2 = df.groupby(['ma','young']])['rating'].apply(lambda x: x.value_counts().index[1])

请让我知道我该怎么做。

Answer 1

首先过滤然后获得tops，但一般情况下可能不存在第二个top：

df1 = df.query("gender== 'ma' & age == 'young'")
#alternative is boolean indexing
#df1 = df[(df['gender'] == 'ma') & (df['age'] == 'young')]
tops = df1.groupby(['gender','age'])['rating'].value_counts()
print (tops)
gender  age    rating
ma      young  PG        2
               R         1

print (df.iloc[[0]])
  gender    age rating
0     ma  young     PG


print (df.iloc[[1]])
  gender    age rating
1     fe  young     PG

如何将列值用于groupby

1 个答案: