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This biggest problem with the convention keyword is that is completely undocumented (also mentioned in #5023 as the general issue about resample's docs).
As a result, I am also not sure what the convention keyword should actually do, but I think it is meant for the case when you upsample a period-based timeseries (based on some tests we have). Eg, in the following case you can see the effect:
In [140]: pts = pd.Series([1, 2], index=pd.period_range('2012-01-01', freq='A', periods=2))
In [142]: pts.resample('M', convention='start').asfreq()
Out[142]:
2012-01 1.0
2012-02 NaN
2012-03 NaN
2012-04 NaN
2012-05 NaN
2012-06 NaN
2012-07 NaN
2012-08 NaN
2012-09 NaN
2012-10 NaN
2012-11 NaN
2012-12 NaN
2013-01 2.0
2013-02 NaN
2013-03 NaN
2013-04 NaN
2013-05 NaN
2013-06 NaN
2013-07 NaN
2013-08 NaN
2013-09 NaN
2013-10 NaN
2013-11 NaN
2013-12 NaN
Freq: M, dtype: float64
In [143]: pts.resample('M', convention='end').asfreq()
Out[143]:
2012-12 1.0
2013-01 NaN
2013-02 NaN
2013-03 NaN
2013-04 NaN
2013-05 NaN
2013-06 NaN
2013-07 NaN
2013-08 NaN
2013-09 NaN
2013-10 NaN
2013-11 NaN
2013-12 2.0
Freq: M, dtype: float64
Code Sample, a copy-pastable example if possible
Problem description
The convention argument does not seem to have any function on start on end when Month is passed as the resample period for a datetime index.
Expected Output
Actual Output
Output of
pd.show_versions()
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: 3.3.0
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: 0.9.2
apiclient: 1.6.1
sqlalchemy: 1.1.5
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext lo64)
jinja2: 2.9.4
boto: 2.45.0
pandas_datareader: None
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