Pandas Is there any fast way to apply crossjoin or join not on two dataframes?

I try to find way to apply cross join on pandas. Failed to find useful suggestion in pandas document. Like SELECT * FROM [GameScores] CROSS JOIN [Departments] or SELECT * FROM [GameScores] JOIN [Departments] on [GameScores].t1 != [Departments].t1

I get one possible answer like: import itertools list=[x for x in itertools.product([a,b,c,d],[1,2,3,4])] df=pd.DataFrame(list) But I'm wondering without numpy tools it might be cost much time while apply this on two large dataframe or series.

Is there any tools in pandas for this two operations?

Comment From: jreback

see #5401