Python 序列到数据帧转换期间的误导性索引
我已在pandas中创建聚合函数并保存结果:Python 序列到数据帧转换期间的误导性索引,python,pandas,Python,Pandas,我已在pandas中创建聚合函数并保存结果: import pandas as pd _dwh = df2_date[df2_date.STATUS == 'A'] .groupby('Party_id') .DURATION_DWH.agg(np.mean) 结果如下所示: 然后,我尝试切换到熊猫数据帧,如下所示: df2_dwh = pd.DataFrame(_dwh) 它返回了一些令人困惑的结果: 如何创建索引为1、…、n、Party_id和Duration
import pandas as pd
_dwh = df2_date[df2_date.STATUS == 'A']
.groupby('Party_id')
.DURATION_DWH.agg(np.mean)
结果如下所示:
然后,我尝试切换到熊猫数据帧,如下所示:
df2_dwh = pd.DataFrame(_dwh)
它返回了一些令人困惑的结果:
如何创建索引为1、…、n、Party_id和Duration_DWH的正常数据帧
谢谢您需要将参数添加为\u index=False或:
_dwh=df2_date[df2_date.STATUS=='A'].groupby('Party_id', as_index=False).DURATION_DWH.mean()
print (_dwh)
Party_id DURATION_DWH
0 214BB440D604466275DFBB 574.0
1 214BB440D604466276D1B3 574.0
2 214BB440D604466371D1B2 558.5
3 214BB440D604466371DDB1 578.0
4 214BB440D604466373DBB5 578.0
_dwh=df2_date[df2_date.STATUS=='A'].groupby('Party_id', as_index=False).DURATION_DWH
.mean()
.reset_index()
print (_dwh)
Party_id DURATION_DWH
0 214BB440D604466275DFBB 574.0
1 214BB440D604466276D1B3 574.0
2 214BB440D604466371D1B2 558.5
3 214BB440D604466371DDB1 578.0
4 214BB440D604466373DBB5 578.0