pandas 根据列的最大值删除熊猫数据框行
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Drop pandas dataframe row based on max value of a column
提问by Fungie
I have a Dataframe like so:
我有一个像这样的数据框：
p_rel y_BET sq_resid
1 0.069370 41.184996 0.292942
2 0.116405 43.101090 0.010953
3 0.173409 44.727748 0.036832
4 0.225629 46.681293 0.540616
5 0.250682 46.980616 0.128191
6 0.294650 47.446113 0.132367
7 0.322530 48.078038 0.235047
How do I get rid of the fourth row because it has the max value of sq_resid? note: the max will change from dataset to dataset so just removing the 4th row isn't enough.
如何摆脱第四行，因为它具有 sq_resid 的最大值？注意：最大值会随数据集变化而变化，因此仅删除第 4 行是不够的。
I have tried several things such as I can remove the max value which leaves the dataframe like below but haven't been able to remove the whole row.
我已经尝试了几件事，例如我可以删除最大值，该最大值会留下如下所示的数据框，但无法删除整行。
p_rel y_BET sq_resid
1 0.069370 41.184996 0.292942
2 0.116405 43.101090 0.010953
3 0.173409 44.727748 0.036832
4 0.225629 46.681293 Nan
5 0.250682 46.980616 0.128191
6 0.294650 47.446113 0.132367
7 0.322530 48.078038 0.235047
回答by EdChum
You could just filter the df like so:
您可以像这样过滤 df：
In [255]:
df.loc[df['sq_resid']!=df['sq_resid'].max()]
Out[255]:
p_rel y_BET sq_resid
1 0.069370 41.184996 0.292942
2 0.116405 43.101090 0.010953
3 0.173409 44.727748 0.036832
5 0.250682 46.980616 0.128191
6 0.294650 47.446113 0.132367
or dropusing idxmaxwhich will return the label row of the max value:
或drop使用idxmaxwhich 将返回最大值的标签行：
In [257]:
df.drop(df['sq_resid'].idxmax())
Out[257]:
p_rel y_BET sq_resid
1 0.069370 41.184996 0.292942
2 0.116405 43.101090 0.010953
3 0.173409 44.727748 0.036832
5 0.250682 46.980616 0.128191
6 0.294650 47.446113 0.132367
7 0.322530 48.078038 0.235047
