熊猫与重复指数之和

Question

我有一个按日期索引的数据帧。

transactions_ind
Out[25]: 
                   Ticker     Transaction  Number_of_units      Price
Date                                                                 
2012-10-11  ROG VX Equity             Buy            12000  182.00000
2012-10-16  ROG VX Equity            Sell            -5000  184.70000
2012-11-16  ROG VX Equity            Sell            -5000  175.51580
2012-12-07  ROG VX Equity             Buy             5000  184.90000
2012-12-11  ROG VX Equity            Sell            -3000  188.50000
2012-12-11  ROG VX Equity  Reversal: Sell             3000  188.50000
2012-12-11  ROG VX Equity            Sell            -3000  188.50000
2012-12-11  ROG VX Equity  Reversal: Sell             3000  188.50000
2012-12-11  ROG VX Equity            Sell            -3000  188.50000
2012-12-20  ROG VX Equity            Sell            -5000  185.80000

我想对重复的索引值(2012-12-11)进行求和，但只对列"Number_of_units“求和。

transactions_ind
Out[25]: 
                   Ticker     Transaction  Number_of_units      Price
Date                                                                 
2012-10-11  ROG VX Equity             Buy            12000  182.00000
2012-10-16  ROG VX Equity            Sell            -5000  184.70000
2012-11-16  ROG VX Equity            Sell            -5000  175.51580
2012-12-07  ROG VX Equity             Buy             5000  184.90000
2012-12-11  ROG VX Equity            Sell            -3000  188.50000
2012-12-20  ROG VX Equity            Sell            -5000  185.80000

使用

transactions_ind.groupby(transactions_ind.index).sum()

删除列"Ticker“和"Transaction”，因为这些列都填充了非数字值。另外，当我与"Number_of_units“列相加时，我想知道如何处理”Transaction“列中的不同字符串。希望熊猫有一条单线。谢谢你的帮忙!

Answer 1

您可以将agg与first和sum结合使用

df = df.groupby(df.index).agg({'Ticker': 'first',
                                'Transaction': 'first',
                                'Number_of_units':sum, 
                                'Price': 'first'})
#reorder columns
df = df[['Ticker','Transaction','Number_of_units','Price']]
print df
                   Ticker Transaction  Number_of_units     Price
Date                                                            
2012-10-11  ROG VX Equity         Buy            12000  182.0000
2012-10-16  ROG VX Equity        Sell            -5000  184.7000
2012-11-16  ROG VX Equity        Sell            -5000  175.5158
2012-12-07  ROG VX Equity         Buy             5000  184.9000
2012-12-11  ROG VX Equity        Sell            -3000  188.5000
2012-12-20  ROG VX Equity        Sell            -5000  185.8000

Answer 2

如果您只有一个索引列(就像您的情况一样)，则接受的答案非常有用。如果您有一个MultiIndex，它将不幸地将其缩减为元组。以下是恢复MultiIndex的方法：

import pandas as pd
index_names = df.index.names
df = df.groupby(df.index).agg({...})
df.index = pd.MultiIndex.from_tuples(df.index, names=index_names)