pydata/pandas — pull request #7055 by cpcloud (2014-05-06 14:02:58+00:00)
Title: ENH: use size instead of cythonized count for fallback cases

* use size instead of cythonized count for integer case since we cannot have
`nan` in that case
* not faster perf wise
* compilation time is shorter because count has no int templates except for
dates and times
* any precision issues (don't think there were any) with other types are gone

Anywho, here's the vbench results for this PR vs master:

```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
groupby_int_count | 4.0247 | 4.0337 | 0.9978 |
groupby_multi_count | 7.5080 | 7.4813 | 1.0036 |
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
```