pydata/pandas — pull request #6604 by jseabold (2014-03-11 19:35:54+00:00)
Title: ENH: Allow update to use an on keyword. Allow one to many update.

Scratch an itch I had. Use case

df = DataFrame([[np.nan, 'A'],
[np.nan, 'A'],
[np.nan, 'A'],
[1.5, 'B'],
[2.2, 'C'],
[3.1, 'C'],
[1.2,' B']], columns=['number', 'name'])

df2 = pd.DataFrame([[3.5, 'A']], columns=['number', 'name'])

df.update(df2, on='name')

The tests fail though because when you reset the index, the column order is not preserved and `self = self[col_order]` doesn't seem to do what I'd expect it to do. Maybe there's a better way to go about doing all of this?

Also, I dropped reindex_like because you were just iterating through columns of NaNs in `other`.