Problem with DataFrame.lookup()
If the row and/or column labels are not present in the DataFrame, the lookup() method returns ... whatever it wants, apparently. I would expect either a NaN or an exception, personally - but whatever the result, it shouldn't be the wrong piece of data.

> > > df = pandas.DataFrame({'A': pandas.Series(['A', 'B', 'C', 'D', 'E'], index=range(5))})
> > > 
> > > df.lookup([2], ['A'])              # Correct
> > > array([C], dtype=object)
> > > 
> > > df.lookup([10], ['A'])            # 10 is not present in the index, so we get .. the last value in A?
> > > array([E], dtype=object)
> > > 
> > > df.lookup([3], ['B'])               # There is no column 'B', so we get ... the value from the last column (A) in that row?
> > > array([C], dtype=object)
> > > 
> > > df.lookup([10], ['B'])             # Neither row or column label is valid, so we get ... I can't rationalize this one.
> > > array([D], dtype=object)
