pandas :如果满足3列中的条件，则更新值

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我有一个像这样的数据框:

I have a dataframe like this:

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

，并且我想在D列满足3个条件时进行更新.例如:

and I want to update column D when it meets 3 conditions. Ex:

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，但不适用于第三个条件，因此:

It works for the first two conditions, but it doesn't work for the third, thus:

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

具有完全相同的结果:

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

推荐答案

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:

A better way of achieving this seems to be:

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