MicroDataFrame.merge() returns a DataFrame

[MaxGhenis]

Example:

d = mdf.MicroDataFrame(dict(g=["a", "a", "b"], y=[1, 2, 3]), weights=[4, 5, 6])
d2 = mdf.MicroDataFrame(dict(g=["a", "b"], z=[1, 2]), weights=[4, 5])
merged = d.merge(d2, on="g")
merged.__class__

pandas.core.frame.DataFrame

merged

	g	y	__tmp_weights	z
0	a	1	4.0	1
1	a	2	5.0	1
2	b	3	6.0	2

I think mdf1.merge(mdf2) should return a MicroDataFrame that preserves mdf1's weights.