What is the difference between join and merge in Pandas?

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Suppose I have two DataFrames like so:

left = pd.DataFrame({'key1': ['foo', 'bar'], 'lval': [1, 2]})

right = pd.DataFrame({'key2': ['foo', 'bar'], 'rval': [4, 5]})

I want to merge them, so I try something like this:

pd.merge(left, right, left_on='key1', right_on='key2')

And I’m happy

    key1    lval    key2    rval
0   foo     1       foo     4
1   bar     2       bar     5

But I’m trying to use the join method, which I’ve been lead to believe is pretty similar. 

left.join(right, on=['key1', 'key2'])

And I get this:

//anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc in _validate_specification(self)
    406             if self.right_index:
    407                 if not ((len(self.left_on) == self.right.index.nlevels)):
--> 408                     raise AssertionError()
    409                 self.right_on = [None] * n
    410         elif self.right_on is not None:

AssertionError:

What am I missing?

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