Question

我有一个df列，如下所示：

col1
Non Profit
Other-501c3
501c3
Sole Proprietor

如何创建字典对象或映射层（向所有建议开放），如果它符合标准并更改了键值，则可以在其中传递任何值？

例如，如果值为Other-501c3，则将其更改为non-profit。

示例（等号之后的所有内容都必须更改为等号之前的值）：

1. non-profit = (Non Profit, Other-501c3, 501c3,NON-Profit, Not-for-profit).

2. Sole Proprietor = (Sole Proprietor,Sole Proprietorship)

该解决方案应该具有可扩展性，我可以添加更多“键值”对

先谢谢您。

Answer 1

从key s创建字典，将它们与map合并：

L1 = ['Non Profit', 'Other-501c3', '501c3','NON-Profit', 'Not-for-profit']
d1 = dict.fromkeys(L1, 'non-profit')

L2 = ['Sole Proprietor','Sole Proprietorship']
d2 = dict.fromkeys(L2, 'Sole Proprietor')

d = {**d1, **d2}
print (d)
{'Non Profit': 'non-profit', 
 'Other-501c3': 'non-profit', 
 '501c3': 'non-profit',
 'NON-Profit': 'non-profit', 
 'Not-for-profit': 'non-profit', 
 'Sole Proprietor': 'Sole Proprietor',
 'Sole Proprietorship': 'Sole Proprietor'}

df['new'] = df['col1'].map(d)
print (df)
              col1              new
0       Non Profit       non-profit
1      Other-501c3       non-profit
2            501c3       non-profit
3  Sole Proprietor  Sole Proprietor

Answer 2

与@jezrael's类似的解决方案，但是您可以使用collections.ChainMap来代替创建新词典：

from collections import ChainMap

# dataframe setup
df = pd.DataFrame({'col1': ['Non Profit', 'Other-501c3', '501c3', 'Sole Proprietor']})

# create ChainMap
L1 = ['Non Profit', 'Other-501c3', '501c3','NON-Profit', 'Not-for-profit']
L2 = ['Sole Proprietor','Sole Proprietorship']
d = ChainMap(dict.fromkeys(L1, 'non-profit'), dict.fromkeys(L2, 'Sole Proprietor'))

# map values
df['new'] = df['col1'].map(d.get)

print(df)

              col1              new
0       Non Profit       non-profit
1      Other-501c3       non-profit
2            501c3       non-profit
3  Sole Proprietor  Sole Proprietor

如何将键映射到多个值到dataframe列？

2 个答案: