into(pytables Table, csv) with option to ignore errors in CSV files

This PR is for the use case of having a large quantity of CSV files with almost (but not entirely) perfect data. CSV reading is dispatched to `pd.read_csv` with the result appended to a pytables `Table`. Keyword argument flags for `read_csv` are propagated through the `into` call. In particular, something like this works:

```
tble = into(table, "some_ok_data.csv", error_bad_lines=False)
```
which gives the keyword argument ```error_bad_lines``` to ```read_csv``` as documented [here] (http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html)
It provides some use as it is, but marked as WIP since it is probably more useful once it supports a glob of CSVs. Additionally, @mrocklin had some ideas about other ways to specify the pytables Table in the `into` call.

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Although this is also an issue:

```Python
In [1]: import blaze
/home/mrocklin/workspace/multipledispatch/multipledispatch/dispatcher.py:20: AmbiguityWarning: 
Ambiguities exist in dispatched function into

The following signatures may result in ambiguous behavior:
	[object, unicode], [type, object]
	[object, unicode], [w_array, Iterable]
	[object, str], [DataDescriptor, Iterable]
	[object, unicode], [DataDescriptor, Iterable]
	[object, unicode], [ndarray, Iterable]
	[object, str], [type, object]
	[object, str], [ndarray, Iterable]


Consider making the following additions:

@dispatch(type, unicode)
def into(...)

@dispatch(w_array, unicode)
def into(...)

@dispatch(DataDescriptor, str)
def into(...)

@dispatch(DataDescriptor, unicode)
def into(...)

@dispatch(ndarray, unicode)
def into(...)

@dispatch(type, str)
def into(...)

@dispatch(ndarray, str)
def into(...)
  warn(warning_text(dispatcher.name, ambiguities), AmbiguityWarning)
```

Perhaps it'd be best to specify a few types explicitly for which you'd like resource to be used.