pandas:如果满足3列条件,则更新值

Question

我有这样的数据帧:

In[1]: df
Out[1]:
      A      B       C            D
1   blue    red    square        NaN
2  orange  yellow  circle        NaN
3  black   grey    circle        NaN

我想在满足3个条件时更新D列.例如:

df.ix[ np.logical_and(df.A=='blue', df.B=='red', df.C=='square'), ['D'] ] = 'succeed'

它适用于前两个条件,但它不适用于第三个条件,因此:

df.ix[ np.logical_and(df.A=='blue', df.B=='red', df.C=='triangle'), ['D'] ] = 'succeed'

有完全相同的结果:

In[1]: df
Out[1]:
      A      B       C            D
1   blue    red    square        succeed
2  orange  yellow  circle        NaN
3  black   grey    circle        NaN

Answer 1

运用

df[ (df.A=='blue') & (df.B=='red') & (df.C=='square') ]['D'] = 'succeed'

给出以下警告

/usr/local/lib/python2.7/dist-packages/ipykernel_launcher.py:2: 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

实现这一目标的更好方式似乎是

df.loc[(df['A'] == 'blue') & (df['B'] == 'red') & (df['C'] == 'square'),'D'] = 'M5'

Answer 2

你可以试试这个:

df[ (df.A=='blue') & (df.B=='red') & (df.C=='square') ]['D'] = 'succeed'

Answer 3

你可以尝试：

df['D'] = np.where((df.A=='blue') & (df.B=='red') & (df.C=='square'), 'succeed')

这个答案可能会为您的问题提供详细的答案： Update row values where certain condition is met in pandas