将pandas Dataframe列映射到字典值 [英] map pandas Dataframe columns to dictionary values

问题描述

我有一个one:man字典.我想将pandas Dataframe列的值映射到字典的键(非值).这是我的字典:

I have a one:many dictionary. I would like to map the values of a pandas Dataframe column to the keys (NOT values) of the dictionary. here is my dictionary:

dict1={'fruits':('apple','grapes','oranges'),'food':('fish','meat','fibre')}

这是pandas系列对象:

And here is the pandas Series object:

df=pd.Series(['fish','apple','meat'])

我想要的期望输出:

0      food
1    fruits
2      food
dtype: object

推荐答案

如果其他"同时存在于水果"和食物"中怎么办?这就是为什么如果没有某种逻辑来解决重复项就无法进行反向查找的原因.

What if 'other' was in both 'fruits' and 'food'? That is why you cannot do a reverse lookup without having some sort of logic to resolve duplicates.

如果您的值都是唯一的，则可以使用字典理解来反转字典:

If your values are all unique, then you can reverse your dictionary using a dictionary comprehension:

reversed_dict = {val: key for key in dict1 for val in dict1[key]}

>>> reversed_dict
{'apple': 'fruits',
 'fibre': 'food',
 'fish': 'food',
 'grapes': 'fruits',
 'meat': 'food',
 'oranges': 'fruits'}

然后可以进行映射.

>>> pd.Series(['fish','apple','meat']).map(reversed_dict)
0      food
1    fruits
2      food
dtype: object

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