resample() silently ignores misstyped str kwargs, e.g. for label

[cchwala]

Code Sample, a copy-pastable example if possible

In [1]: import pandas as pd

In [2]: df = pd.DataFrame(index=pd.date_range(start='2010-01-23', periods=1000, freq='min'), data={'foo': pd.np.random.rand(1000)})

In [3]: df.resample('h').mean().tail()
Out[3]: 
                          foo
2010-01-23 12:00:00  0.477997
2010-01-23 13:00:00  0.488294
2010-01-23 14:00:00  0.426095
2010-01-23 15:00:00  0.549081
2010-01-23 16:00:00  0.466148

In [4]: df.resample('h', label='right').mean().tail()
Out[4]: 
                          foo
2010-01-23 13:00:00  0.477997
2010-01-23 14:00:00  0.488294
2010-01-23 15:00:00  0.426095
2010-01-23 16:00:00  0.549081
2010-01-23 17:00:00  0.466148

In [5]: 

In [5]: df.resample('h', label='right_wrong').mean().tail()
Out[5]: 
                          foo
2010-01-23 12:00:00  0.477997
2010-01-23 13:00:00  0.488294
2010-01-23 14:00:00  0.426095
2010-01-23 15:00:00  0.549081
2010-01-23 16:00:00  0.466148

# The last command should fail!

Problem description

Recently (and maybe many times before without noticing...) I mistyped the string passed as kwarg label in resample, e.g. df.resample('5min', label='rigth') and wondered later why the alignment of my resampled data with the raw data was wrong. It turns out that the actual string passed as kwarg label is never checked to be either left or right. Hence, if it is

Is this on purpose, or should this be fixed?

If yes, a check could be inserted here. Or maybe deeper in the class hierarchy? Maybe other kwargs, like closed could also be affected.

If I get a pointer I could come up with a PR.

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.14.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: None.None

pandas: 0.21.0
pytest: 3.2.5
pip: 9.0.1
setuptools: 36.7.2
Cython: None
numpy: 1.13.3
scipy: 1.0.0
pyarrow: 0.7.1
xarray: 0.10.0
IPython: 5.5.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: None
numexpr: None
feather: 0.4.0
matplotlib: 2.1.0
openpyxl: None
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: 2.7.3.2 (dt dec pq3 ext lo64)
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[chris-b1]

I agree this should raise, and I think where you pointed (TimeGrouper.__init__ ) is the right spot to do it.

I also agree that closed can & should be checked. convention looks like it raises an error eventually.

df.index = df.index.to_period()
df.resample('h', convention='junk').mean().tail()
ValueError: How must be one of S or E

So a PR is definitely welcome!