[Improvement] Deterministic value_counts

Code Sample, a copy-pastable example if possible

import pandas as pd

df = pd.DataFrame(["a", "b", "c"], columns=["test"])

print(df["test"].value_counts())

Problem description

Using value_counts in a testsuite can be a problem, when the resulting values have the same count as they permutade on each call, e.g.:

$ python pandas_value_counts.py
a    1
b    1
c    1
Name: test, dtype: int64

$ python pandas_value_counts.py
c    1
a    1
b    1
Name: test, dtype: int64

Expected Output

Some stable/deterministic output or optionally additionally sorting of the keys, if they have the same counts

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.0.final.0 python-bits: 32 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 94 Stepping 3, GenuineIntel byteorder: little LC_ALL: None LANG: de_DE.UTF-8 LOCALE: None.None

pandas: 0.19.2 nose: 1.3.7 pip: 9.0.1 setuptools: 27.2.0 Cython: 0.25.2 numpy: 1.11.3 scipy: 0.18.1 statsmodels: 0.6.1 xarray: None IPython: 5.1.0 sphinx: 1.5.1 patsy: 0.4.1 dateutil: 2.6.0 pytz: 2016.10 blosc: None bottleneck: 1.2.0 tables: 3.2.2 numexpr: 2.6.1 matplotlib: 2.0.0 openpyxl: 2.4.1 xlrd: 1.0.0 xlwt: 1.2.0 xlsxwriter: 0.9.6 lxml: 3.7.2 bs4: 4.5.3 html5lib: None httplib2: None apiclient: None sqlalchemy: 1.1.5 pymysql: None psycopg2: None jinja2: 2.9.4 boto: 2.45.0 pandas_datareader: None

[tomspur]

Yes, I would need this for testing and would like to have the highest count of the data. With just getting the first item of the value_counts, this is some random value, that has the maximum count and it would be great to have always the same value.

[jreback]

see discussion in these related issues.

xref #12679 xref #11227 xref #14860

This is not guaranteed in any way, nor is performant to do so. Further why should this be anything but an arbitrary ordering? This is a mapping of value -> count.