How to merge two Pandas DataFrames when two columns are the same

Question

I have these two dataframes:

  orderItemId     orderId                  orderDate         latestDeliveryDate  
0  BFC0000332253518  2648507110  2019-11-10T21:08:30+01:00  2019-11-11T00:00:00+01:00  
0  BFC0000332123047  2647717360  2019-11-10T15:42:39+01:00  2019-11-11T00:00:00+01:00  
0  BFC0000332291194  2648712140  2019-11-10T22:24:56+01:00  2019-11-11T00:00:00+01:00 

          orderItemId     orderId shipmentId   shipmentReference               shipmentDate
0    BFC0000332253518  2648507110  689508122  081234500926730318  2019-11-11T00:10:06+01:00
1    BFC0000332123047  2647717360  689505054  081234500926572451  2019-11-10T23:55:38+01:00
2    BFC0000332291194  2648712140  689505045  081234500926710549  2019-11-10T23:55:37+01:00

How can I merge those together with Pandas merge? Because they have two columns that are the same. Can I use multiple on= values?

use `pd.merge(df1, df2, on=['orderItemId','orderId'])` – jezrael Nov 11 '19 at 06:59 — jezrael, Nov 11 '19 at 06:59

score 0 · Answer 1 · answered Nov 11 '19 at 07:00

Yes you can use multiple on values. I suppose from your example above, you want to merge on orderItemId and orderId right?

Just use:

final_df = pd.merge(df1, df2, how = 'inner', left_on = ['orderItemId','orderId'], right_on = ['orderItemId','orderId'])

How to merge two Pandas DataFrames when two columns are the same

1 Answers1