Cannot append pandas DataFrame to another DataFrame

Question

I have two pandas dataframes: df and temp_df. The df has a header, but temp_df does not have it.

df =

   IdTravel   TravelDate               IdProfesional        InformAsign
0  8178429    2017-10-25 11:25:16.550  NaN                  NaN
1  8180074    2017-10-25 13:49:09.640  NaN                  NaN
2  8180287    2017-10-25 14:28:04.000  123                  ABC
3  8182810    2017-10-26 09:55:14.930  NaN                  NaN
4  8182849    2017-10-26 09:59:11.187  NaN                  NaN

temp_df =

   0          1                        2                    3
0  4189915    2017-10-25 13:49:09.640  NaN                  NaN
1  4100334    2017-10-25 14:28:04.000  111                  ABC
2  4102833    2017-10-26 09:55:14.930  NaN                  NaN
3  4102845    2017-10-26 09:59:11.187  NaN                  NaN

I want to append temp_df to df. Expected result:

   IdTravel   TravelDate               IdProfesional        InformAsign
0  8178429    2017-10-25 11:25:16.550  NaN                  NaN
1  8180074    2017-10-25 13:49:09.640  NaN                  NaN
2  8180287    2017-10-25 14:28:04.000  123                  ABC
3  8182810    2017-10-26 09:55:14.930  NaN                  NaN
4  8182849    2017-10-26 09:59:11.187  NaN                  NaN
5  4189915    2017-10-25 13:49:09.640  NaN                  NaN
6  4100334    2017-10-25 14:28:04.000  111                  ABC
7  4102833    2017-10-26 09:55:14.930  NaN                  NaN
8  4102845    2017-10-26 09:59:11.187  NaN                  NaN

I tried:

result = df.append(temp_df)

I was expecting to get a new dataframe with 9 rows. But instead I got a dataframe result with 9 rows and 8 columns.

Also, I tried this, but got the same wrong result:

result = pd.concat([df,temp_df],axis=1,ignore_index=True) # and axis=0

Andrej Kesely · Accepted Answer · 2019-12-30 22:39:59Z

You can rename columns in temp_df to match the original df:

temp_df.columns = ['IdTravel', 'TravelDate', 'IdProfesional', 'InformAsign']
result = df.append(temp_df).reset_index(drop=True)
print(result)

Prints:

   IdTravel               TravelDate  IdProfesional InformAsign
0   8178429  2017-10-25 11:25:16.550            NaN         NaN
1   8180074  2017-10-25 13:49:09.640            NaN         NaN
2   8180287  2017-10-25 14:28:04.000          123.0         ABC
3   8182810  2017-10-26 09:55:14.930            NaN         NaN
4   8182849  2017-10-26 09:59:11.187            NaN         NaN
5   4189915  2017-10-25 13:49:09.640            NaN         NaN
6   4100334  2017-10-25 14:28:04.000          111.0         ABC
7   4102833  2017-10-26 09:55:14.930            NaN         NaN
8   4102845  2017-10-26 09:59:11.187            NaN         NaN

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