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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I think we should err if there isn't any `output_path` with a really informative message about what they should do instead.  Also, for known keyword arguments I suggest putting them in the signature

    def into(a, b, output_path=None, **kwargs):
         if output_path is None:
            raise ValueError("You actually need to type something like this .... ")