[英]Drop pandas dataframe row based on max value of a column
I have a Dataframe like so: 我有一个像这样的数据帧:
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? 如何摆脱第四行,因为它的最大值为sq_resid? note: the max will change from dataset to dataset so just removing the 4th row isn't enough. 注意:最大值将从数据集更改为数据集,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. 我已经尝试了几样的东西,比如我可以删除最大值,这样就像下面那样留下了数据帧但是却无法删除整行。
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
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 drop
using idxmax
which will return the label row of the max value: 或drop
使用idxmax
这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
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