pandas :在列表的每个元素上使用groupby [英] Pandas : Use groupby on each element of list

问题描述

也许我错过了显而易见的事情.

Maybe I'm missing the obvious.

我有一个看起来像这样的pandas数据框:

I have a pandas dataframe that looks like this :

   id        product              categories
    0        Silmarillion         ['Book', 'Fantasy']
    1        Headphones           ['Electronic', 'Material']
    2        Dune                 ['Book', 'Sci-Fi']

我想使用groupby函数计算类别列中每个元素的出现次数，因此结果将是

I'd like to use the groupby function to count the number of appearances of each element in the categories column, so here the result would be

Book       2
Fantasy    1
Electronic 1
Material   1
Sci-Fi     1

但是，当我尝试使用groupby函数时，pandas会计算整个列表的出现，而不是分离其元素.我尝试过使用元组或拆分的多种不同方式来处理此问题，但到目前为止，我一直没有成功.

However when I try using a groupby function, pandas counts the occurrences of the entire list instead of separating its elements. I have tried multiple different ways of handling this, using tuples or splits, but this far I've been unsuccessful.

推荐答案

您可以通过堆叠记录然后调用value_counts()来对记录进行规范化:

You can normalize the records by stacking them then call value_counts():

pd.DataFrame(df['categories'].tolist()).stack().value_counts()
Out: 
Book          2
Fantasy       1
Material      1
Sci-Fi        1
Electronic    1
dtype: int64

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