Stripped timedelta[s] series represented as timedelta[ns] #12425
Description
In [2]: s = pd.Series(range(61)).astype('timedelta64[s]') In [3]: s.tail(1) Out[3]: 60 00:01:00 dtype: timedelta64[s] In [4]: str(s).splitlines()[-2] Out[4]: '60 00:00:00.000000' ... because the snipped representation interprets the content of the series as nanoseconds rather than milliseconds. The same happens with timedelta[ms] and probably any other resolution (if there are).
In [5]: pd.show_versions() INSTALLED VERSIONS ------------------ commit: 404819358e90da57c8025a259ab58cd75426069f python: 3.4.3.final.0 python-bits: 64 OS: Linux OS-release: 4.3.0-1-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: it_IT.utf8 pandas: 0.18.0rc1+35.g4048193 nose: 1.3.6 pip: 1.5.6 setuptools: 20.1.1 Cython: 0.23.2 numpy: 1.10.0.post2 scipy: 0.16.0 statsmodels: 0.8.0.dev0+755fa81 xarray: None IPython: 4.1.1 sphinx: 1.3.1 patsy: 0.3.0-dev dateutil: 2.4.2 pytz: 2015.6 blosc: None bottleneck: None tables: 3.2.2 numexpr: 2.4.3 matplotlib: 1.5.dev1 openpyxl: None xlrd: 0.9.4 xlwt: None xlsxwriter: 0.7.3 lxml: None bs4: 4.4.0 html5lib: 0.999 httplib2: 0.9.1 apiclient: None sqlalchemy: 1.0.11 pymysql: None psycopg2: None jinja2: 2.8