PERF: DataFrame groupby with fast transform
from [SO](http://stackoverflow.com/questions/36286803/how-to-speed-up-the-replacement-of-missing-values-for-each-groupby-group-in-pand)

```
import pandas as pd
import numpy as np

df = pd.DataFrame({'group': np.repeat(np.arange(1000), 10),
                   'B': np.nan,
                   'C': np.nan})

df.ix[4::10, 'B':'C'] = 5 # every 4th row of a group is non-null

df.groupby('group').transform('first')
```

This is then iterating over groups. Last I can see this was changed is: [here](https://github.com/pydata/pandas/pull/9994). My recollection is that this was ONLY supposed to hit in a special case, and the general case is simply a repeat based on the indices. 

This seems to be hitting in all cases makes transform back to super SLOW.
