Python 序列到数据帧转换期间的误导性索引

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

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_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