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iBeMeltin
Asked: 2024-04-12 02:10:30 +0800 CST

从 groupby 执行计算后创建新的数据框

  • 772

我有一个如下所示的数据框：

ID  TradeDate    party    Deal   Asset  Start       Expire      Fixed   Quantity  MTM      Float
1   04/11/2024   party1   Sell   HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Buy    HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Buy    HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   WTI    01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   WTI    01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Buy    WTI    01/01/2024  02/01/2024  10.00   1000     2500.00   10.00

我按开始、资产和交易对数据进行分组，然后执行计算将数据帧转换为：

groups = df.groupby(['Start', 'Asset', 'Deal'])

ID  TradeDate    party    Deal   Asset  Start       Expire      Fixed   Quantity  MTM      Float
1   04/11/2024   party1   Sell   HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
total                                                                   3000     7500.00   

ID  TradeDate    party    Deal   Asset  Start       Expire      Fixed   Quantity  MTM      Float
1   04/11/2024   party1   Buy    HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Buy    HO     01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
total                                                                   3000     5000.00   

ID  TradeDate    party    Deal   Asset  Start       Expire      Fixed   Quantity  MTM      Float
1   04/11/2024   party1   Sell   WTI    01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
1   04/11/2024   party1   Sell   WTI    01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
total                                                                   3000     5000.00   

ID  TradeDate    party    Deal   Asset  Start       Expire      Fixed   Quantity  MTM      Float
1   04/11/2024   party1   Buy    WTI    01/01/2024  02/01/2024  10.00   1000     2500.00   10.00
total                                                                   1000     2500.00

我的目标是再次转换这些组，以便我可以只输出我需要的数据。此步骤的预期输出应如下所示：

party   Deal  Asset Start        MTM       Float
party1  Sell  HO    01/01/2024   7500.00   10.00 
party1  Buy   HO    01/01/2024   5000.00   10.00
party1  Sell  WTI   01/01/2024   5000.00   10.00
party1  Buy   WTi   01/01/2024   2500.00   10.00

我需要执行另一次某种分组吗？或者还有其他功能可以实现这一目标吗？任何建议都会有所帮助。

注意：在第二步中，这些是来自列表的单独数据帧。您可能需要一个中间步骤将它们连接在一起，然后得到最终输出。

python

1 个回答

  1. Best Answer

    我认为你只需要pd.Groupby+ .agg：

    out = df.groupby(["Start", "Asset", "Deal"], sort=False, as_index=False).agg(
    {"party": "first", "MTM": "sum", "Float": "first"}
)
print(out)

    印刷：

            Start Asset  Deal   party     MTM  Float
0  01/01/2024    HO  Sell  party1  7500.0   10.0
1  01/01/2024    HO   Buy  party1  5000.0   10.0
2  01/01/2024   WTI  Sell  party1  5000.0   10.0
3  01/01/2024   WTI   Buy  party1  2500.0   10.0
    • 1

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