In [46]: result = pd.merge(left, right, how="right", on=["key1", "key2"])

​

df_merge_col = pd.merge(df_row, df3, on='id')

​

df_merge_col

>>> df1.merge(df2, left_on='lkey', right_on='rkey')

  lkey  value_x rkey  value_y

0  foo        1  foo        5

1  foo        1  foo        8

2  foo        5  foo        5

3  foo        5  foo        8

4  bar        2  bar        6

5  baz        3  baz        7

​

In [41]: result = pd.merge(left, right, on="key")

df_cd = pd.merge(df_SN7577i_c, df_SN7577i_d, how='inner', left_on = 'Id', right_on = 'Id')

result = pd.merge(left, right, on="key")

DataFrame_name.merge(right, how='inner', on=None, left_on=None, right_on=None, left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'), copy=True, indicator=False, validate=None)

pd.merge(df1, df2, on="movie_title")

prop_rates = pd.DataFrame([1000, 5000, 12000], index=['Rural','Semiurban','Urban'],columns=['rates'])

prop_rates