我有一个像这样的数据框 df:

      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'

结果完全相同:

      A      B       C            D
1   blue    red    square        succeed
2  orange  yellow  circle        NaN
3  black   grey    circle        NaN

最佳答案

使用:

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

给出警告:

/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'

关于python - Pandas : update value if condition in 3 columns are met，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/21263020/