python panda: return indexes of common rows

Question

Apologies, if this is a fairly newbie question. I was trying to find which rows are common between two data frames. The return values should be the row indexes of df2

Answer 1

New column with join values is not necessary, merge by default inner merge by both columns and if need values of df2.index add reset_index:

df1 = pd.DataFrame({'col1':['cx','cx','cx2'], 'col2':[1,4,12]})
df2 = pd.DataFrame({'col1':['cx','cx','cx','cx','cx2','cx2'], 'col2':[1,3,5,10,12,12]})

df3 = pd.merge(df1,df2.reset_index(), on = ['col1','col2'])
print (df3)
  col1 col2  index
0   cx    1      0
1  cx2   12      4
2  cx2   12      5

For both indexes need:

df4 = pd.merge(df1.reset_index(),df2.reset_index(), on = ['col1','col2'])
print (df4)

   index_x col1  col2  index_y
0        0   cx     1        0
1        2  cx2    12        4
2        2  cx2    12        5

For only intersection of both DataFrames:

df5 = pd.merge(df1,df2, on = ['col1','col2'])
#if 2 column DataFrame   
#df5 = pd.merge(df1,df2)
print (df5)

  col1  col2
0   cx     1
1  cx2    12
2  cx2    12

Answer 2

This can easily be done by merging (inner join) both dataframes:

common_rows = pd.merge(df1, df2.reset_index(), how='inner', on=['idx_values'])