Intersect two dataframes in Pandas with respect to first dataframe?

Question

I want to intersect two Pandas dataframes (1 and 2) based on two columns (A and B) present in both dataframes. However, I would like to return a dataframe that only has data with respect to the data in the first dataframe, omitting anything that is not found in the second dataframe.

So for example:

Dataframe 1: 
A | B | Extra | Columns | In | 1 |
----------------------------------
1 | 2 | Extra | Columns | In | 1 |
1 | 3 | Extra | Columns | In | 1 |
1 | 5 | Extra | Columns | In | 1 |

Dataframe 2: 
A | B | Extra | Columns | In | 2 |
----------------------------------
1 | 3 | Extra | Columns | In | 2 |
1 | 4 | Extra | Columns | In | 2 |
1 | 5 | Extra | Columns | In | 2 |

should return:

A | B | Extra | Columns | In | 1 |
----------------------------------
1 | 3 | Extra | Columns | In | 1 |
1 | 5 | Extra | Columns | In | 1 |

Is there a way I can do this simply?

Answer 1

You can use df.merge :

df = df1.merge(df2, on=['A','B'], how='inner').drop('2', axis=1)

how='inner' is default . Just put it there for your understanding of how df.merge works.

As @piRSquared suggested, you can do:

df1.merge(df2[['A', 'B']], how='inner')