Code Sample, a copy-pastable example if possible
>>> import pandas as pd
>>> pd.PeriodDtype()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/tesla/Projects/pandas/pandas/core/dtypes/dtypes.py", line 149, in __repr__
return str(self)
File "/home/tesla/Projects/pandas/pandas/core/dtypes/dtypes.py", line 880, in __str__
return self.name
File "/home/tesla/Projects/pandas/pandas/core/dtypes/dtypes.py", line 884, in name
return "period[{freq}]".format(freq=self.freq.freqstr)
AttributeError: 'NoneType' object has no attribute 'freqstr'
Problem description
Currently if you instantiate a PeriodDtype it is not required to set the freq since the __new__ method passes a freq=None, which eventually leads to the error shown in the first code snippet.
Having a default None frequency doesn't really make sense. In fact there shouldn't be any default value of frequency. The freq should be a required argument.
Expected Output
>>> import pandas as pd
>>> pd.Period
pd.Period( pd.PeriodDtype( pd.PeriodIndex(
>>> pd.PeriodDtype()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: __new__() missing 1 required positional argument: 'freq'
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 269d36814e471880627109a5e5ea63d4a5fdc5a6
python : 3.7.3.final.0
python-bits : 64
OS : Linux
OS-release : 5.2.0-arch2-1-ARCH
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 0.25.0rc0+62.g269d36814
numpy : 1.16.4
pytz : 2019.1
dateutil : 2.8.0
pip : 19.1.1
setuptools : 41.0.1
Cython : 0.29.11
pytest : 5.0.0
hypothesis : 4.23.6
sphinx : 1.8.5
blosc : None
feather : None
xlsxwriter : 1.1.8
lxml.etree : 4.3.4
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.10.1
IPython : 7.6.1
pandas_datareader: None
bs4 : 4.7.1
bottleneck : 1.2.1
fastparquet : 0.3.0
gcsfs : None
lxml.etree : 4.3.4
matplotlib : 3.1.0
numexpr : 2.6.9
odfpy : None
openpyxl : 2.6.2
pandas_gbq : None
pyarrow : 0.11.1
pytables : None
s3fs : 0.2.1
scipy : 1.2.1
sqlalchemy : 1.3.5
tables : 3.5.2
xarray : 0.12.1
xlrd : 1.2.0
xlwt : 1.3.0
xlsxwriter : 1.1.8
Comment From: WillAyd
I think this makes sense though @jbrockmendel or @jschendel might have additional input.
FWIW there is a comment about pickle compat driving the None handling in the past. We just upped our minimum pickle compat so maybe not an issue anymore:
https://github.com/pandas-dev/pandas/blob/269d36814e471880627109a5e5ea63d4a5fdc5a6/pandas/core/dtypes/dtypes.py#L822