Currently, if a column happens to have only nulls, an exception is thrown with the error:
Invalid: Unable to infer type of object array, were all null
It is possible to specify the type of the column, that will be used instead of inferring the type?
Versions:
feather-format==0.3.1
pandas==0.19.1
Sample code:
feather.write_dataframe(pandas.DataFrame([None]*5), '/tmp/test.feather')
Change (or replace) None
to numpy.nan
and it'll work:
In [22]: feather.write_dataframe(pd.DataFrame([np.nan]*5), 'd:/temp/test.feather')
In [23]: feather.read_dataframe('d:/temp/test.feather')
Out[23]:
0
0 NaN
1 NaN
2 NaN
3 NaN
4 NaN
PS NumPy / Pandas / SciPy / etc. have their own representation of Vanilla Python's None
- NaN
(Not A Number) or NaT
(Not A Time for DateTime-like dtypes)