将多个数据框连接在一起，并确保正确的数字进入同一列 [英] Joining multiple dataframes together and making sure the right numbers go to the same column

问题描述

我有一些数据框，它们都希望在同一列中包含脏价"和因子".当我尝试执行此操作时，当我将第二个数据框连接在一起时会发生什么，然后pandas创建了一个新的"Dirty Price_x"和"Factor_x"，但是我不希望新列合并到符合条件的同一列中我指定.

I have a few dataframes that all have a "Dirty Price" and "Factor" that I want to have in the same column. When I try to do this what happens when I join the second dataframe together then pandas creates a new "Dirty Price_x" and "Factor_x" but I don't want new columns I want them to me merged into the same column that match the criteria I specify.

这就是我所做的:

df = df.merge(gs[['CUSIP', 'temp_Counterparty','Dirty Price','Factor']], how = 'left', on = ['CUSIP', 'temp_Counterparty'])
df = df.merge(nomura[['CUSIP', 'temp_Counterparty','Dirty Price','Factor']], how = 'left', on = ['CUSIP', 'temp_Counterparty'])

我在这里做错什么了吗?

Is there something I am doing wrong here?

推荐答案

由于gs和nomura不共享CUSIP和Counterpary的相同组合，因此可以合并这两个数据帧，然后执行合并

Since gs and nomura do not share the same combination of CUSIP and Counterpary, you can concat these two dataframes and then do the merge

df_concat = pd.concat([ gs[['CUSIP', 'temp_Counterparty','Dirty Price','Factor']] , 
                        nomura[['CUSIP', 'temp_Counterparty','Dirty Price','Factor']]
                      ], axis = 0)


df = df.merge(df_concat, how='left', on=['CUSIP', 'temp_Counterparty'])

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