quantile() does not work with columns of type Decimal

[mavroprovato]

Code Sample, a copy-pastable example if possible

This snippet does not work (returns an empty DataFrame)

pd.DataFrame([
    Decimal(162.7646939720129171), Decimal(162.5470404198062433),
    Decimal(162.9334883683360258), Decimal(161.7975872981700753),
    Decimal(160.9450499461786868), Decimal(163.1648865446716900),
]).quantile(0.8)

Expected Output

This snippet works as expected (returns a Series with one value)

pd.DataFrame([
    162.7646939720129171, 162.5470404198062433,
    162.9334883683360258, 161.7975872981700753,
    160.9450499461786868, 163.1648865446716900,
]).quantile(0.8)

Shouldn't both snippets work the same way?

output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.4.3.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-86-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 20.9.0
Cython: None
numpy: 1.11.0
scipy: None
statsmodels: None
xarray: None
IPython: 4.2.0
sphinx: None
patsy: None
dateutil: 2.5.2
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: 0.7.2.None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
pandas_datareader: None

[TomAugspurger]

I don't think this is supported. numpy.percentile doesn't even work on Decimals, so not much we can do.

[jreback]

its possible (esp in the new way .quantile works), but we don't support Decimal very much.

[jreback]

what we really need is Block support for Decimal. Though I don't see much actual utility for this.

closing as no action, but if you'd like to submit a PR would be ok with it.

[jorisvandenbossche]

Some things do work, eg mean, also in numpy:

In [57]: a = np.array([Decimal(160.9450499461786868), Decimal(163.1648865446716900)])

In [58]: a
Out[58]:
array([Decimal('160.94504994617869897410855628550052642822265625'),
       Decimal('163.164886544671702495179488323628902435302734375')], dtype=object)

In [59]: a.mean()
Out[59]: Decimal('162.0549682454252007346440223')

So I would rather raise this issue on the numpy side, rather than starting to implement a specific Block for this