pydata/pandas — pull request #7342 by jreback (2014-06-04 17:02:55+00:00)
Title: PERF: better dtype inference for perf gains (GH7332)

closes #7332

for some reason ``int64`` was not being looked up correctly in the _TYPE_MAP table.
changing to work on name/kind makes this more efficient.

separately better inference of timedelta conversions from i8 were not being done
so that yields a big boost

```
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------
dtype_infer_timedelta64_2 | 3.9814 | 1765.3640 | 0.0023 |
dtype_infer_datetime64 | 4.8450 | 1825.3207 | 0.0027 |
dtype_infer_int64 | 0.7904 | 18.5820 | 0.0425 |
dtype_infer_float64 | 0.8090 | 1.0493 | 0.7710 |
dtype_infer_float32 | 0.3430 | 0.3823 | 0.8971 |
dtype_infer_int32 | 0.3897 | 0.4017 | 0.9701 |
dtype_infer_uint32 | 0.5450 | 0.5583 | 0.9762 |
dtype_infer_timedelta64_1 | 118.2277 | 117.6037 | 1.0053 |
-------------------------------------------------------------------------------
Test name | head[ms] | base[ms] | ratio |
-------------------------------------------------------------------------------

Ratio < 1.0 means the target commit is faster then the baseline.
Seed used: 1234

Target [e2f5a50] : PERF: use names/kinds for dtype inference on known types
Base [87660ef] : Merge pull request #6968 from ahlmss/AHLMSS_0.13.1_ahl1
```