python：pandas np.where 与 df.loc 具有多种条件
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python: pandas np.where vs. df.loc with multiple conditions
提问by jeangelj
Np.where has been giving me a lot of errors, so I am looking for a solution with df.loc instead.
Np.where 给了我很多错误，所以我正在寻找 df.loc 的解决方案。
This is the np.where error I have been getting:
这是我遇到的 np.where 错误：
C:\Users\xxx\AppData\Local\Continuum\Anaconda2\lib\site-packages\ipykernel\__main__.py:1: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
if __name__ == '__main__':
I am working with the following dataframe df:
我正在使用以下数据框 df：
df = pd.DataFrame({'Column_A': ['AAA','AAA','ABC','CDE'],'checked': ['0','0','1','0'],'duplicate': ['True','True','False','False']})
Column_A checked duplicate
0 AAA 0 True
1 AAA 0 True
2 ABC 1 False
3 CDE 0 False
I want to create an additional flag, if checked is 0 and duplicate is True.
我想创建一个额外的标志，如果检查为 0 并且重复为 True。
I tried this and it didn't work:
我试过这个，但没有用：
df['flag'] = (np.where((df['checked'] == 'Y') &(df['duplicate'] == 'True'), 'Y', '0'))
TypeError: invalid type comparison
I tried it with df.loc:
我用 df.loc 试了一下：
df['flag'] = (df.loc[df['checked'] == 'Y']& df.loc[df['duplicate'] == 'True'], 'Y','0')
TypeError: invalid type comparison
and I get the same error!
我得到了同样的错误！
回答by jezrael
I think your booleanare not strings, so need remove ':
我认为你boolean不是strings，所以需要删除'：
df = pd.DataFrame({'Column_A': ['AAA','AAA','ABC','CDE'],
'checked': ['0','0','1','0'],
'duplicate': [True, True, False, False]})
df['flag'] = np.where((df['checked'] == 'Y') &(df['duplicate'] == True), 'Y', '0')
print (df)
Column_A checked duplicate flag
0 AAA 0 True 0
1 AAA 0 True 0
2 ABC 1 False 0
3 CDE 0 False 0
Or if compare with booleancolumn, == Truecan be omited:
或者如果与boolean列比较，== True可以省略：
df['flag'] = np.where((df['checked'] == 'Y') &(df['duplicate']), 'Y', '0')
print (df)
Column_A checked duplicate flag
0 AAA 0 True 0
1 AAA 0 True 0
2 ABC 1 False 0
3 CDE 0 False 0
Also if need check checkedneed 'because strings:
此外，如果需要检查checked需要，'因为strings：
df['flag'] = np.where((df['checked'] == '0') &(df['duplicate'] == True), 'Y', '0')
print (df)
Column_A checked duplicate flag
0 AAA 0 True Y
1 AAA 0 True Y
2 ABC 1 False 0
3 CDE 0 False 0
EDIT:
编辑：
Solution with loc:
解决方案loc：
df['flag'] = '0'
mask = (df['checked'] == '0') &(df['duplicate'])
df.loc[mask, 'flag'] = 'Y'
print (df)
Column_A checked duplicate flag
0 AAA 0 True Y
1 AAA 0 True Y
2 ABC 1 False 0
3 CDE 0 False 0
