pandas.json.dumps gives incorrect results with numpy 1.6.1
I ran into this nasty error when building / testing OSX wheels.

```
======================================================================
ERROR: test_timedelta (pandas.io.tests.test_json.test_pandas.TestPandasContainer)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/Users/buildslave/osx-10.6-clean/scipy-stack-2_7_6-wheel-requires/build/venv/lib/python2.7/site-packages/pandas/io/tests/test_json/test_pandas.py", line 611, in test_timedelta
    assert_series_equal(s, pd.read_json(s.to_json(),typ='series').apply(converter))
  File "/Users/buildslave/osx-10.6-clean/scipy-stack-2_7_6-wheel-requires/build/venv/lib/python2.7/site-packages/pandas/core/series.py", line 1998, in apply
    mapped = lib.map_infer(values, f, convert=convert_dtype)
  File "inference.pyx", line 1016, in pandas.lib.map_infer (pandas/lib.c:53184)
  File "/Users/buildslave/osx-10.6-clean/scipy-stack-2_7_6-wheel-requires/build/venv/lib/python2.7/site-packages/pandas/io/tests/test_json/test_pandas.py", line 607, in <lambda>
    converter = lambda x: pd.to_timedelta(x,unit='ms')
  File "/Users/buildslave/osx-10.6-clean/scipy-stack-2_7_6-wheel-requires/build/venv/lib/python2.7/site-packages/pandas/tseries/timedeltas.py", line 69, in to_timedelta
    return _coerce_scalar_to_timedelta_type(arg, unit=unit)
  File "/Users/buildslave/osx-10.6-clean/scipy-stack-2_7_6-wheel-requires/build/venv/lib/python2.7/site-packages/pandas/tseries/timedeltas.py", line 123, in _coerce_scalar_to_timedelta_type
    return tslib.convert_to_timedelta(r,unit)
  File "tslib.pyx", line 1361, in pandas.tslib.convert_to_timedelta (pandas/tslib.c:22899)
  File "tslib.pyx", line 1427, in pandas.tslib.convert_to_timedelta64 (pandas/tslib.c:23733)
ValueError: Invalid type for timedelta scalar: <class 'pandas.tslib.Timestamp'>
```

(see http://nipy.bic.berkeley.edu/builders/scipy-stack-2.7.6-wheel-requires/builds/88/steps/shell_10/logs/stdio)

After some tiring debugging, it turns out that the error is caused by an incorrect output of `pandas.json.dumps` if pandas is compiled against numpy 1.6. This script:

```
from datetime import timedelta
from pandas import Series
import pandas.json

s = Series([timedelta(23), timedelta(seconds=5)])
print pandas.json.dumps(s,
                        orient='index',
                        double_precision=10,
                        ensure_ascii=True,
                        date_unit='ms',
                        iso_dates=False,
                        default_handler=None)
```

gives the (I think) correct output below when pandas is compiled against numpy 1.7.1:

```
{"0":1987200000,"1":5000}
```

If pandas is compiled against numpy 1.6.1 (current recorded dependency) then the same script gives:

```
{"0":1987200000000000,"1":5000000000}
```

This in turn leads to the error at the top of this issue because the correct JSON passed into pandas.read_json generates a series of numpy.int64 whereas the incorrect JSON generates numpy.datetime64 elements:

```
In [10]: pd.read_json('{"0":1987200000,"1":5000}', typ='series')
Out[10]: 
0    1987200000
1          5000
dtype: int64

In [12]: pd.read_json('{"0":1987200000000000,"1":5000000000}', typ='series')
Out[12]: 
0   2032-12-21 00:00:00
1   1970-01-01 01:23:20
dtype: datetime64[ns]
```

Should the numpy dependency be updated to 1.7.1?  I was afraid when I looked at the `dumps` C code but maybe there is some way of making it more robust to numpy version.
