PERF: fix JSON performance regression from 0.12 (GH5765)
This fixes the main JSON performance regression  in v0.13 (closes #5765). The main bottleneck was the use of intermediate NumPy scalars (from PR #4498). I introduced code to avoid the use of NumPy scalars. Also:
- checks current locale so locale fudging is only done if necessary
- added numpy 1.6 preprocessor switches as it still requires the use of scalars due to its weird datetime handling
- reorgranised some of the if/else checks in `objToJSON.c` based on likelihood.
- added some JSON benchmarks to vbench to try and avoid future regressions.

0.12

``` python
In [1]: import pandas as pd, numpy as np

In [2]: df = pd.DataFrame(np.random.rand(100000,10))

In [3]: %timeit df.to_json(orient='split')
10 loops, best of 3: 119 ms per loop

In [4]: pd.__version__, np.__version__
Out[4]: ('0.12.0', '1.8.0')
```

This PR

``` python
In [1]: import pandas as pd, numpy as np

In [2]: df = pd.DataFrame(np.random.rand(100000,10))

In [3]: %timeit df.to_json(orient='split')
10 loops, best of 3: 119 ms per loop

In [4]: pd.__version__, np.__version__
Out[4]: ('0.13.0-406-ga18e5e6', '1.8.0')
```

While this solves the main performance issue, using vbench this PR still appears to be a bit slower than v0.12 (~ 2 - 5%) but it's unclear where the slowdown is coming from.

@jreback do you still have a windows box / vm that you could test on?

```

-------------------------------------------------------------------------------
Test name                                    | head[ms] | base[ms] |  ratio   |
-------------------------------------------------------------------------------
packers_write_json                           |  23.3610 |  42.2543 |   0.5529 |
packers_write_json_date_index                |  31.3267 |  45.5254 |   0.6881 |
packers_read_json                            |  39.0206 |  39.3570 |   0.9915 |
packers_read_json_date_index                 |  39.2287 |  39.2920 |   0.9984 |
-------------------------------------------------------------------------------
Test name                                    | head[ms] | base[ms] |  ratio   |
-------------------------------------------------------------------------------

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

Target [0975572] : Merge branch 'json-0.13-slowdown' of https://github.com/Komnomnomnom/pandas into Komnomnomnom-json-0.13-slowdown
Base   [464c1f9] : Add Scatter-CI link to README.md
```
 looks good....tested fine on windows , fyi you can watch this: http://scatterci.github.io/ScatterCI-Pandas/

for all builds (linux/windows/sparc builds too)
 Awesome! That looks pretty sweet, thanks.
