ENH: guarantee pandas.Series.value_counts "sort=False" to be original ordering
Hello,

I'm trying to make a new DataFrame that contains the value counts of a column of an existing DataFrame ([spreadsheet.xlsx](https://github.com/pydata/pandas/files/181629/spreadsheet.xlsx)), but I want the rows in the new DataFrame to be in the same order as the old one.

When I do:

``` python
import pandas as pd
df = pd.read_excel('./spreadsheet.xlsx')
print(df[0].value_counts(sort=False))
```

I get the DataFrame:

``` python
h4  8
ct1 6
f2  2
s1  2
EST2    2
f5  2
E4  8
h2  8
hd2 7
f3  2
ART1    2
s2  2
f1  2
h3  8
EST1    2
s3  2
E6  8
ART2    2
DGT2    2
ct2 6
s4  2
ct3 6
f4  2
DGT1    2
s5  2
```

When what I really want is:

``` python
h2  8
h3  8
h4  8
hd2 7
E4  8
E6  8
ct1 6
.
.
.
```

...because that's the order in which the values occur in the original DataFrame.

I can't tell how it's sorting them, but it is somehow. Is this the expected behavior?

Thanks

``` python
Installed versions:
commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.3.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.0
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.10.4
scipy: 0.17.0
statsmodels: None
xarray: None
IPython: 4.1.2
sphinx: 1.3.5
patsy: 0.4.0
dateutil: 2.5.0
pytz: 2016.1
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: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: 0.9.2
apiclient: 1.5.0
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
```
