Python: adding a column to the pandas data frame

Question

I have the two data frames my first data frame, start_df_1, looks like this:

start_df_1

              0
0   3Degrees_Inc 
1   3Degrees_Inc
2   3Degrees_Inc
3   3Degrees_Inc
4   3Degrees_Inc
5   3Degrees_Inc
6   3Degrees_Inc
7   3Degrees_Inc
8   3Degrees_Inc
9   3Degrees_Inc
10  3Degrees_Inc

my second data frame friends_df looks like this:

friends_df
            0
0      MEGreenPower
1       LympheDIVAs
2     Ecopreneurist
3     issielapowsky
4     NatureClimate
5      miketuritzin
6         greenbang
7     GoodCleanTech
8            EDFbiz
9         adavies47
10        petedanko

I am trying to make a new data frame, something like:

  concatenated_df          

               User        Follower
0      MEGreenPower    3Degrees_Inc
1       LympheDIVAs    3Degrees_Inc
2     Ecopreneurist    3Degrees_Inc
3     issielapowsky    3Degrees_Inc
4     NatureClimate    3Degrees_Inc
5      miketuritzin    3Degrees_Inc
6         greenbang    3Degrees_Inc
7     GoodCleanTech    3Degrees_Inc
8            EDFbiz    3Degrees_Inc
9         adavies47    3Degrees_Inc
10        petedanko1   3Degrees_Inc

note that the new column is added, and first column and the second column is named as "User" and "Follower", respectively. I tried:

EDGE_LIST1 = pandas.DataFrame.from_dict({'User':friends_df, 
                                         'Follower': start_df_1}, orient='columns')

however it is throwing me an error:

ValueError: If using all scalar values, you must must pass an index

could you please help me out? thank you.

Jin-Dominique · Accepted Answer · 2013-10-26 20:22:02Z

1

I found a solution; you just do:

EDGE_LIST1 = pandas.concat({'User':start_df_1, 'Follower': friends_df}, axis=1)

answered Oct 26, 2013 at 20:22

Jin-Dominique

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