pandas:如果3列中的条件为m，则更新值

Question

我有一个这样的数据框：

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个条件时更新列D。例如：

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

它适用于前两种情况，但不适用于第三种情况，因此：

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

结果完全相同：

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

你可以试试这个：

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

Answer 2

使用：

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

发出警告：

/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法似乎是：

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

Answer 3

你可以试试：

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