Python Pandas merge only certain columns

You want to use TWO brackets, so if you are doing a VLOOKUP sort of action:

df = pd.merge(df,df2[['Key_Column','Target_Column']],on='Key_Column', how='left')

This will give you everything in the original df + add that one corresponding column in df2 that you want to join.

python merge pandas

You could merge the sub-DataFrame (with just those columns):

df2[list('xab')]  # df2 but only with columns x, a, and bdf1.merge(df2[list('xab')])

python merge pandas

If you want to drop column(s) from the target data frame, but the column(s) are required for the join, you can do the following:

df1 = df1.merge(df2[['a', 'b', 'key1']], how = 'left',                left_on = 'key2', right_on = 'key1').drop(columns= ['key1'])

The .drop('key1') part will prevent 'key1' from being kept in the resulting data frame, despite it being required to join in the first place.

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