Assignment / modification of values in an indexed subframe in Pandas

Question

The documentation for indexing has few examples of assignment of a non-scalar right hand side.

In this case, I want to modify a subset of my dataframe, and what I did prior to v.13 no longer works.

import pandas as pd
from numpy import *

data = {'me':list('rttti'),'foo': list('aaade'), 'bar': arange(5)*1.34+2, 'bar2': arange(5)*-.34+2}
df = pd.DataFrame(data).set_index('me')

print df

df.loc['r',['bar','bar2']]*=2.0
print df
df.loc['t','bar']*=2.5
# Above fails: ValueError: Must have equal len keys and valuewhen setting with an iterable
print df
df.loc['t',['bar','bar2']]*=2.0
# Above fails: *** InvalidIndexError: Reindexing only valid with uniquely valued Index objects
print df

I want to be able to assign a matrix of values to a matrix of locations using loc or, in this simplifed case, I just want to modify them by some simple operation like multiplication.

The first modification works (the index value is unique), and the others do not, though they give different errors.