指定一个新列以对项目的值进行分类



我使用从excel导入了一个数据帧

data = pd.read_csv('transaction.csv')

并且有一个看起来像的数据帧

Date      Time  Transaction           Item
0  2016-10-30  09:58:11            1          water
1  2016-10-30  10:05:34            2   french fries
2  2016-10-30  10:05:34            2       Icecream
3  2016-10-30  10:07:57            3      chocolate
4  2016-10-30  10:07:57            3        Cookies

我创建了一个字典,将每个项目分配给食物或饮料类别,如下所示:

Food = ('french fries', 'Icecream', 'chocolate', 'Cookies')
Drink = ('water')
Category = {Food : "Food", Drink : "Drink"}

我想将类别分配给另一列,但结果是NaN。我用了这个代码:

data['Classification'] = data['Item'].map(Category)

Date      Time  Transaction           Item Food or Drink
0  2016-10-30  09:58:11            1          water           NaN
1  2016-10-30  10:05:34            2   french fries           NaN
2  2016-10-30  10:05:34            2       icecream           NaN
3  2016-10-30  10:07:57            3      chocolate           NaN
4  2016-10-30  10:07:57            3        cookies           NaN

解决这个问题的最佳方法是什么?

通过dict.fromkeys为每个类别创建字典,并将它们合并在一起:

Food = ('french fries', 'Icecream', 'chocolate', 'Cookies')
Drink = ('water',)
Category = {**dict.fromkeys(Food, "Food"), **dict.fromkeys(Drink, "Drink")}
print (Category)
{'french fries': 'Food', 'Icecream': 'Food', 
'chocolate': 'Food', 'Cookies': 'Food', 'water': 'Drink'}
data['Classification'] = data['Item'].map(Category)
print (data)
Date      Time  Transaction          Item Classification
0  2016-10-30  09:58:11            1         water          Drink
1  2016-10-30  10:05:34            2  french fries           Food
2  2016-10-30  10:05:34            2      Icecream           Food
3  2016-10-30  10:07:57            3     chocolate           Food
4  2016-10-30  10:07:57            3       Cookies           Food

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