Issue 1:
I'm using pandas 0.5.0 with python 2.7 on archlinux.

This example file seems pretty standard and it opens well in Libreoffice: http://dl.dropbox.com/u/40028/countrycode.csv

import pandas
cc = pandas.read_csv('countrycode.csv', index_col=1)
cc
ERROR: An unexpected error occurred while tokenizing input
The following traceback may be corrupted or invalid
The error message is: ('EOF in multi-line statement', (1224, 0))

Out[31]: ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/[path/to/file/anonymized/manually/by/me]/<ipython-input-31-870c06c00566> in <module>()
----> 1 cc

/usr/lib/python2.7/site-packages/IPython/core/displayhook.py in __call__(self, result)
300 self.start_displayhook()
301 self.write_output_prompt()
--> 302 format_dict = self.compute_format_data(result)
303 self.write_format_data(format_dict)
304 self.update_user_ns(result)

/usr/lib/python2.7/site-packages/IPython/core/displayhook.py in compute_format_data(self, result)
213 MIME type representation of the object.
214 """
--> 215 return self.shell.display_formatter.format(result)
216
217 def write_format_data(self, format_dict):

/usr/lib/python2.7/site-packages/IPython/core/formatters.py in format(self, obj, include, exclude)
120 continue
121 try:
--> 122 data = formatter(obj)
123 except:
124 # FIXME: log the exception

/usr/lib/python2.7/site-packages/IPython/core/formatters.py in __call__(self, obj)
441 type_pprinters=self.type_printers,
442 deferred_pprinters=self.deferred_printers)
--> 443 printer.pretty(obj)
444 printer.flush()
445 return stream.getvalue()

/usr/lib/python2.7/site-packages/IPython/lib/pretty.py in pretty(self, obj)
349 if hasattr(obj_class, '_repr_pretty_'):
350 return obj_class._repr_pretty_(obj, self, cycle)
--> 351 return _default_pprint(obj, self, cycle)
352 finally:
353 self.end_group()

/usr/lib/python2.7/site-packages/IPython/lib/pretty.py in _default_pprint(obj, p, cycle)
467 if getattr(klass, '__repr__', None) not in _baseclass_reprs:
468 # A user-provided repr.

--> 469 p.text(repr(obj))
470 return
471 p.begin_group(1, '<')

/usr/lib/python2.7/site-packages/pandas/core/frame.pyc in __repr__(self)
263 buf = StringIO()
264 if len(self.index) < 500 and len(self.columns) <= 10:
--> 265 self.to_string(buf=buf)
266 else:
267 self.info(buf=buf, verbose=self._verbose_info)

/usr/lib/python2.7/site-packages/pandas/core/frame.pyc in to_string(self, buf, columns, colSpace, na_rep, formatters, float_format, sparsify, nanRep, index_names)
569 float_format=float_format,
570 sparsify=sparsify,
--> 571 index_names=index_names)
572
573 if buf is None:

/usr/lib/python2.7/site-packages/pandas/core/frame.pyc in __init__(self, frame, buf, columns, col_space, na_rep, formatters, float_format, sparsify, index_names)
2943 self.column_filter = frame.columns if columns is None else set(columns)
2944
-> 2945 self._write_to_buffer()
2946
2947 def _write_to_buffer(self):

/usr/lib/python2.7/site-packages/pandas/core/frame.pyc in _write_to_buffer(self)
2956 else:
2957 # may include levels names also

-> 2958 str_index = self._get_formatted_index()
2959 str_columns = self._get_formatted_column_labels()
2960

/usr/lib/python2.7/site-packages/pandas/core/frame.pyc in _get_formatted_index(self)
3035 names=show_index_names)
3036 else:
-> 3037 fmt_index = [index.format(name=show_index_names)]
3038
3039 adjoined = adjoin(1, *fmt_index).split('\n')

TypeError: format() got an unexpected keyword argument 'name'

Issue 2:
Encountered via a column with all missing values read from a CSV that are filled by pd.csv_read as NaNs. I had logic to check for duplicate values that used set(df[col]), which I realize I can readily replace with df[col].unique(). However, found an intriguing bug, in that a lengthy list of np.NaN appears to hang the kernel... one core maxes at 100% and just sits there with the fans blasting.

This only seems to occur with NaNs... a similar list of integers or floats will chug but ultimately return.

System is a Gigabyte Aero 15 running Ubuntu 16.04

Python 3.6.1

Pandas 0.20.1

NumPy 1.13.1

Minimal reproduction

import pandas as pd
import numpy as np
ser = pd.Series([np.NaN]*1000000)
set(ser)

I mean, this is really just an entertaining curiosity, as behavior with .unique is fine. Still intriguing, though. Any ideas?