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So I have a DataFrame, df1, that has 3 columns, A, B, and C as such:

 A B C Arizona 0 2.800000 5.600000 California 0 18.300000 36.600000 Colorado 0 2.666667 5.333333 Connecticut 0 0.933333 1.866667 Delaware 0 0.100000 0.200000 Florida 0 0.833333 1.666667 Georgia 0 0.000000 0.000000 Hawaii 0 1.000000 2.000000 Illinois 0 3.366667 6.733333 Indiana 0 0.000000 0.000000 Iowa 0 0.000000 0.000000

I then have another dataframe, df2, that has just one column, D:

 D Arizona 13 California 18 Colorado 5 Connecticut 15 Delaware 7 Florida 5 Georgia 13 Hawaii 3 Illinois 21 Indiana 2 Iowa 4

What I'd like to do is add the values of column D to all the columns in df1. By add I mean take the value of [Arizona, A] and add it to the value of [Arizona, D] not add column D as a new column. So far I tried using

df1 + df2 #returned all NaN df1 + df2['D'] #Also returned all NaN df1['A'] + df2['D'] #Returned a new dataframe with each as a separate column

I'm now not entirely sure where to go from here so I'd love some advice on how to solve this. It doesn't seem like it should be difficult and I'm probably missing something obvious. Any help would be appreciated.

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2 Answers 2

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you can use add() method:

In [22]: df1.add(df2.D, axis='index') Out[22]: A B C Arizona 13.0 15.800000 18.600000 California 18.0 36.300000 54.600000 Colorado 5.0 7.666667 10.333333 Connecticut 15.0 15.933333 16.866667 Delaware 7.0 7.100000 7.200000 Florida 5.0 5.833333 6.666667 Georgia 13.0 13.000000 13.000000 Hawaii 3.0 4.000000 5.000000 Illinois 21.0 24.366667 27.733333 Indiana 2.0 2.000000 2.000000 Iowa 4.0 4.000000 4.000000
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7 Comments

Your answer was very quick. How did you generate the dataframe in ipython so quickly?
@NehalJWani, read_clipboard
Fantastic! Hadn't thought to use axis = 'index'. Somewhat interesting side note, using df2.D works, but using df2[[0]] doesn't and returns a df filled with NaN. Will accept as answer in 6 minutes when it lets me
@JSolomonCulp, because df2[[0]] - returns dataframe, not a series. You can either add series with or a dataframe of the same shape (in both cases it will be aligned by indexes)... But you can do it this way: df.add(df2.ix[:, 0], axis='index')
@JSolomonCulp, sure, as i showed before: df2.ix[:, 0] - gives you 0-th column
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are you trying to do something like this?

df1 = DataFrame({'A':{'a':1, 'b':2}, 'B':{'a':10, 'b':20}}) df2 = DataFrame({'C':{'a':2, 'b':2}}) df1['A+C'] = df1['A'] + df2['C'] df1['B+C'] = df1['B'] + df2['C'] print (df1) A B A+C B+C a 1 10 3 12 b 2 20 4 22
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