python:具有多个条件的 pandas np.where 与 df.loc

Question

Np.where 一直给我很多错误，所以我正在寻找 df.loc 的解决方案。

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__':

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

我想创建一个额外的标志，如果检查为 0 且重复为 True。

我试过了，没用:

df['flag'] = (np.where((df['checked'] == 'Y') &(df['duplicate'] == 'True'), 'Y', '0'))

TypeError: invalid type comparison

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

我得到了同样的错误!

Answer 1

我认为你的 boolean 不是 string，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

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

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

编辑:

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