pandas: merge (join) two data frames on multiple columns

I am trying to join two pandas data frames using two columns:

    new_df = pd.merge(A_df, B_df,  how='left', left_on='[A_c1,c2]', right_on = '[B_c1,c2]')

but got the following error:

    pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4164)()

    pandas/index.pyx in pandas.index.IndexEngine.get_loc (pandas/index.c:4028)()

    pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13166)()

    pandas/src/hashtable_class_helper.pxi in pandas.hashtable.PyObjectHashTable.get_item (pandas/hashtable.c:13120)()

    KeyError: '[B_1, c2]'

Any idea what should be the right way to do this? Thanks!

Try this

    new_df = pd.merge(A_df, B_df,  how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])

http://pandas.pydata.org/pandas-docs/version/0.19.1/generated/pandas.DataFrame.merge.html

left_on : label or list, or array-like Field names to join on in left DataFrame. Can be a vector or list of vectors of the length of the DataFrame to use a particular vector as the join key instead of columns

right_on : label or list, or array-like Field names to join on in right DataFrame or vector/list of vectors per left_on docs

From: stackoverflow.com/q/41815079

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