How to concatenate two dataframes when there are different number of columns?

Asked Jun 29 '21 at 17:08

Active Jun 29 '21 at 17:13

Viewed 106 times

I have two dataframes: df1 looks like below:

A    B    C    D    E    F    G    H
2    6    8    1    3    9    2    3

df2 looks like below:

A    C    D    G
3    2    4    9

Now, I want to add the data of df2 to df1. But, I want to insert "N/A" for df2 when any column which exists in df1 but not present in df2. You can think, my I want something like below:

A    B    C    D    E    F    G    H
2    6    8    1    3    9    2    3
3   N/A   2    4   N/A  N/A   9    N/A

Can anyone please help, how can I do this?

asked Jun 29 '21 at 17:08

sksoumik

1

merge? `df1.merge(df2,how='outer')` or `df.append(df2)` – anky Jun 29 '21 at 17:09
@anky Would be a concat, not a merge, right? https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.concat.html – Nick ODell Jun 29 '21 at 17:10
@NickODell in this usecase, an outer merge should suffice as well? set index (col A) with concat would work too I agree – anky Jun 29 '21 at 17:11
@NickODell added an append dupe as well incase the OP wants to concat based on index, Thanks for pointing that – anky Jun 29 '21 at 17:14
`df.append(df2)` works in my case. Thank you. – sksoumik Jun 29 '21 at 17:41

How to concatenate two dataframes when there are different number of columns?

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