Populate NaN value in column A of data frame 1 with corresponding value from data frame 2 based on condition

Question

I am new to pandas and am having a really difficult time with this. I have two data frames:

Df1
Address            Zip            Parcel Number
123 Main St        12345          1234-567-890
456 Broadway Ave   55555          NaN

Df2
Address            Zip            Parcel Number
456 Main St        66666          5555-555-555
456 Broadway Ave   55555          7777-777-777

What I would like to do is: If the address & zip code columns in df1 are equal to the address & zip code columns of df2, populate the NaN value in the parcel number column of df1 with the corresponding parcel number value from df2.

Any help would be appreciated!

Answer 1

This is called combine_first . Index your dataframes on ['Address', 'Zip'] first:

Df1.set_index(['Address', 'Zip'], inplace=True)
Df2.set_index(['Address', 'Zip'], inplace=True)
Df1.combine_first(Df2)

You can reset_index the resulting dataframe if you want to keep Address and Zip as columns