Pandas: 根据一列的条件来替换另一列的值

dataframe是这样的

df.head(10)

 RT (min)    Area (Ab*s) Quality patch   similarity
8   10.167      23278313    64      NaN     NaN
9   10.167      23278313    47      NaN     NaN
10  10.167      23278313    38      NaN     NaN
28  10.333      3407159     49      10.167  0.983935
29  10.333      3407159     22      10.167  0.983935
30  10.333      3407159     16      10.167  0.983935
48  10.390      3299202     38      10.333  0.994514
49  10.390      3299202     35      10.333  0.994514
50  10.390      3299202     32      10.333  0.994514
68  10.516      2015786     50      10.390  0.988018

当 df['similarity']>0.99的时候，df['RT(min)'] = df['patch'],例如处理后的结果应该是这样的

  RT (min)    Area (Ab*s) Quality patch   similarity
8   10.167      23278313    64      NaN     NaN
9   10.167      23278313    47      NaN     NaN
10  10.167      23278313    38      NaN     NaN
28  10.333      3407159     49      10.167  0.983935
29  10.333      3407159     22      10.167  0.983935
30  10.333      3407159     16      10.167  0.983935
48  10.333      3299202     38      10.333  0.994514
49  10.333      3299202     35      10.333  0.994514
50  10.333      3299202     32      10.333  0.994514
68  10.516      2015786     50      10.390  0.988018

48,49,50行的RT(min) 被相应的patch值给取代了

解决方法

利用mask

参数解释： Where cond is False, keep the original value. Where True, replace with corresponding value fromother. 也就是说，只有条件是true的 ，参会返回value

df['RT'] = df['RT'].mask(df['similarity'] > 0.99, df['patch'])