BUG: Read SAS fails
cc: @kshedden
#### Code Sample, a copy-pastable example if possible

https://github.com/pydata/pandas/blob/8857008178eb90b59ca67874507ef860b3faf88f/pandas/io/tests/sas/data/test17.sas7bdat

Do you want a PR with this test case?
#### Expected Output

pandas reads the file without crashing :)
I tracked the problem to _process_columntext_subheader. It seems like there is an encoding issue...

You might need to apply  PR #12658 first to see this issue.

FWIW, here is an AWFUL HACK to make pandas read the file "almost" correctly (I get column names as bytes instead of str in this case).

``` diff
@@ -524,17 +524,17 @@ class SAS7BDATReader(BaseIterator):

         offset += self._int_length
         text_block_size = self._read_int(offset, _text_block_size_length)

         buf = self._read_bytes(offset, text_block_size)
-        self.column_names_strings.append(
-            buf[0:text_block_size].rstrip(b"\x00 ").decode())
+        self.column_names_strings.append(buf)
         if len(self.column_names_strings) == 1:
             column_name = self.column_names_strings[0]
             compression_literal = ""
             for cl in _compression_literals:
+                cl = bytes(cl, 'ascii')
                 if cl in column_name:
                     compression_literal = cl
             self.compression = compression_literal
             offset -= self._int_length
```
#### output of `pd.show_versions()`

commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 69 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.0
nose: 1.3.7
pip: 8.1.0
setuptools: 20.2.2
Cython: None
numpy: 1.10.4
scipy: None
statsmodels: None
xarray: None
IPython: 4.1.2
sphinx: 1.3.1
patsy: None
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.6
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: None
xlsxwriter: 0.8.4
lxml: 3.5.0
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
