pandas TypeError: Series.name must be a hashable type
#### Code Sample, a copy-pastable example if possible

This is the following SO issue: http://stackoverflow.com/questions/37195658/pandas-typeerror-series-name-must-be-a-hashable-type

Call to Func_df(df):

pattern_tmp1 = grouped[['sprd1','cost1']].apply(Func_df)[0]

Input df to Func_df(df): 

sprd1  cost1
date  
2016-01-31     -19.02       -436.31

def Func_df(df):
    cases_list =  [monthly_pattern_check(x,y) for x,y in zip(df[[0]].values,df[[1]].values)]
    print collections.Counter(cases_list)
    return dict(collections.Counter(cases_list))

def monthly_pattern_check(r,c):
    if r > c > 0:
        return 'A'
    elif  c > r > 0 :
        return 'B'
    elif r > 0 > c:
         return 'C'
    elif r == 0 and c > 0:
         return 'D'
    elif r < c < 0:
        return '-A'
    elif c < r < 0:
        return '-B'
    elif r < 0 < c:
        return '-C'
    elif r == 0 and c < 0:
        return '-D'
#### Expected Output

pattern_tmp1  should be assigned to the the [0] index value of Counter({'-B': 1})
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Darwin
OS-release: 13.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.1
setuptools: 20.7.0
Cython: 0.22.1
numpy: 1.10.4
scipy: 0.16.0
statsmodels: None
xarray: None
IPython: 4.0.0
sphinx: 1.3.1
patsy: 0.3.0
dateutil: 2.4.2
pytz: 2015.4
blosc: None
bottleneck: 1.0.0
tables: 3.2.0
numexpr: 2.4.4
matplotlib: 1.4.3
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 1.0.0
xlsxwriter: 0.7.3
lxml: 3.4.4
bs4: 4.3.2
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.5
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.38.0
pandas_datareader: None
