read_docx?
#### Problem description

I sometimes need to extract tables from docx files, rather than from HTML. Given that docx XML is very HTML-like when it comes to tables, it seems appropriate to reuse Pandas' loading facilities, ideally without first converging the whole docx to html.

Here is a hacky solution, which simply:
* reads 'word/document.xml' from the docx zipfile
* translates WordprocessingML's `tbl` to `table` and `tc` to `td`. (I've not looked into how Word marks things corresponding to `th`, `thead` and `tfoot`.)

Working implementation invoked by `pd.read_html('file://path/to/my.docx', flavor='docx')`

```py
from pandas.io.html import _LxmlFrameParser, _valid_parsers
from pandas.io.common import _is_url, urlopen


class _LxmlDocxParser(_LxmlFrameParser):
    def _build_doc(self):
        import zipfile
        from lxml.html import parse, HTMLParser
        from lxml.etree import XMLSyntaxError
        parser = HTMLParser(recover=True, encoding=self.encoding)

        if _is_url(self.io):
            with urlopen(self.io) as zipf:
                zf = zipfile.ZipFile(zipf)
                with zf.open('word/document.xml') as f:
                    r = parse(f, parser=parser)
        else:
            zf = zipfile.ZipFile(self.io)
            with zf.open('word/document.xml') as f:
                r = parse(f, parser=parser)
        try:
            r = r.getroot()
        except AttributeError:
            pass
        if not hasattr(r, 'text_content'):
            raise XMLSyntaxError("no text parsed from document", 0, 0, 0)

        # HACK: translate WordprocessingML tags to HTML tags
        for el in r.xpath('//tbl'):
            el.tag = 'table'
        for el in r.xpath('//tc'):
            el.tag = 'td'
        return r


_valid_parsers['docx'] = _LxmlDocxParser

```

Let me know what interest there is, or feel free to use this code in an implementation.
