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 would revert back to something like what you had before with `@dispatch(tables.Table, str)` but expand it to lots of things explicitly like `@dispatch((tables.Table, DataFrame, np.ndarray, list, SQL, ...), str)` and then check to see if that reduces the number of ambiguities.