'input (df):
asof_date  sid  timestamp  value  other
0 2014-01-01   65 2014-01-01      0      1
1 2014-01-01   66 2014-01-01      1      2
2 2014-01-01   67 2014-01-01      2      3
3 2014-01-02   65 2014-01-02      1      2
4 2014-01-02   66 2014-01-02      2      3
5 2014-01-02   67 2014-01-02      3      4
6 2014-01-03   65 2014-01-03      2      3
7 2014-01-03   66 2014-01-03      3      4
8 2014-01-03   67 2014-01-03      4      5
output (expected):
value  other
2014-01-01 Equity(65 [A])      0      1
Equity(66 [B])      1      2
Equity(67 [C])      2      3
2014-01-02 Equity(65 [A])      1      2
Equity(66 [B])      2      3
Equity(67 [C])      3      4
2014-01-03 Equity(65 [A])      2      3
Equity(66 [B])      3      4
Equity(67 [C])      4      5'

def test_id_multiple_columns(self):

    df = self.df.copy()
    df['other'] = (df.value + 1)
    fields = OrderedDict(self.dshape.measure.fields)
    fields['other'] = fields['value']
    expected = df.drop(['timestamp', 'asof_date', 'sid'], axis=1)
    expected.index = pd.MultiIndex.from_product((self.dates, self.asset_finder.retrieve_all(self.asset_finder.sids)))
    self._test_id(df, (var * Record(fields)), expected, self.asset_finder, ('value', 'int_value', 'other'))
