DesignMatrix should have to_dataframe() method

This would be useful, for example, when I really want to be able to use a design matrix as both a raw numpy array and a pandas dataframe.

I suppose I could specify return_type="dataframe" and then get the numpy array from df.values, and it's also not hard to build the dataframe from scratch, but this would be particularly handy for interactive use, where it would provide a useful shortcut (e.g., X.to_dataframe().plot() or X.to_dataframe().head()).

To do this right, the new method would be factored out of build_design_matrices. Roughly speaking, it would look like this:

def to_dataframe(self):
    if not have_pandas:
        raise PatsyError("pandas.DataFrame was requested, but "
                         "pandas is not installed")
    di = self.design_info
    df = pandas.DataFrame(self, columns=di.column_names,
                          index=di.pandas_index)
    df.design_info = di
    return df

The main design change would be that DesignInfo (or DesignMatrix) would need to gain a pandas_index attribute, which would keep track of any index from the original data.

If this seems reasonable, I could put together a pull request.

Start by reading build_design_matrices and the DesignMatrix and DesignInfo definitions to understand how matrix data and original pandas indexes are currently handled. The work is complete when DesignMatrix exposes the requested dataframe conversion, preserves the relevant index and column metadata, and handles missing pandas as specified in the issue.