Pandas -使用groupby创建一个最常见单词的元组

Question

我有一个包含列的数据框架:languages and words

df:
Parts of speech  word
0 Noun             cat
1 Noun             water
2 Noun             cat
3 verb             draw
4 verb             draw
5 adj              slow

我想按词性(我所期望的)对最热门的单词进行分组:

Parts of speech     top 
Noun             {'cat':2,'water':1}
verb             {'draw':2}
adj              {'slow':1}

我使用方法groupby和apply，但是我没有得到我需要的

df2=df.groupby('Parts of speech')['word'].apply(lambda x : x.value_counts())

如何为每个词性创建一个元组?

Answer 1

一种方法是使用.agg+collections.Counter进行聚合:

from collections import Counter
df2=df.groupby('Parts of speech')['word'].agg(Counter)
print(df2)

Parts of speech
Noun    {'cat': 2, 'water': 1}
adj                {'slow': 1}
verb               {'draw': 2}
Name: word, dtype: object

使用value_counts的替代方法(注意末尾的to_dict调用):

df2 = df.groupby('Parts of speech')['word'].agg(lambda x: x.value_counts().to_dict())