Set column names when stacking pandas DataFrame

So here's one way that you may find a bit cleaner, using the fact that columns and Series can also carry names.

In [45]: df
Out[45]: 
               value  value2
id date                     
1  2015-09-31    100     200
2  2015-09-31     95      57
3  2015-09-31     42      27

In [46]: df.columns.name = 'var_name'

In [47]: s = df.stack()

In [48]: s.name = 'value'

In [49]: s.reset_index()
Out[49]: 
   id        date var_name  value
0   1  2015-09-31    value    100
1   1  2015-09-31   value2    200
2   2  2015-09-31    value     95
3   2  2015-09-31   value2     57
4   3  2015-09-31    value     42
5   3  2015-09-31   value2     27

pd.melt is often useful for converting DataFrames from "wide" to "long" format. You could use pd.melt here if you convert the id and date index levels to columns first:

In [56]: pd.melt(df.reset_index(), id_vars=['id', 'date'], value_vars=['value', 'value2'], var_name='var_name', value_name='value')
Out[56]: 
   id        date var_name  value
0   1  2015-09-31    value    100
1   2  2015-09-31    value     95
2   3  2015-09-31    value     42
3   1  2015-09-31   value2    200
4   2  2015-09-31   value2     57
5   3  2015-09-31   value2     27