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I am trying to add a column from one pandas data-frame to another pandas data-frame.

Here is data frame 1: 

print (df.head())
ID   Name    Gender
1    John    Male 
2    Denver  0 
             0
3    Jeff    Male

Note: Both ID and Name are indexes

Here is the data frame 2:

print (df2.head())
ID    Appointed
1         R
2          
3         SL

Note: ID is the index here.

I am trying to add the Appointed column from df2 to df1 based on the ID. I tried inserting the column and copying the column from df2 but the Appointed column keeps returning all NAN values. So far I had no luck any suggestions would be greatly appreciated.

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  • 2
    did you try df1['Appointed'] = df2['Appointed']? what happened? Commented Mar 20, 2018 at 16:30
  • And also you have empty index in df1 ? Commented Mar 20, 2018 at 16:33
  • yap it gives me all nan values. Commented Mar 20, 2018 at 16:35
  • I think you're not simply trying to "add a column". It seems like you're looking to merge columns based on ID. If so, try out my solution. Commented Mar 20, 2018 at 16:43
  • Nope, the index for df1 is ID and Name. I couldn.t provide the original data frame due to non-disclosure reason. Commented Mar 20, 2018 at 16:44

2 Answers 2

Reset to default
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If I understand your problem correctly, you should get what you need using this:

df1.reset_index().merge(df2.reset_index(), left_on='ID', right_on='ID')

   ID    Name Gender Appointed
0   1    John   Male         R
1   2  Denver      0       NaN
2   3    Jeff   Male        SL

Or, as an alternative, as pointed out by Wen, you could use join:

df1.join(df2)

              Gender Appointed
ID Name                   
1  John     Male         R
2  Denver      0       NaN
0  NaN       NaN       NaN
3  Jeff     Male        SL
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3 Comments

why not join :-)
That's a good point, thanks! I never use join, but that's just out of habit. In this case maybe it makes more sense, I'll include it as a second solution if you don't mind...
yw~ :-) feel free to add :-)
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Reset index for both datafrmes and then create a column named 'Appointed' in df1 and assign the same column of df2 in it.

After resetting index,both datafrmes have index beginning from 0. When we assign the column, they automatically align according to index which is a property of pandas dataframe

df1.reset_index()
df2.reset_index()
df1['Appointed'] = df2['Appointed']
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2 Comments

Just tried that out still giving me all NAN values for the Appointed column
While this code may answer the question, providing additional context regarding why and/or how this code answers the question improves its long-term value.

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