Is your feature request related to a problem or challenge? Please describe what you are trying to do.
>>> import datafusion as dfn
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": [1, 2, None]})
>>> df.filter(dfn.col("a") is None).count()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "<path>/lib/python3.12/site-packages/datafusion/dataframe.py", line 499, in filter
df = df.filter(ensure_expr(expr))
^^^^^^^^^^^^^^^^^
File "<path>/lib/python3.12/site-packages/datafusion/expr.py", line 250, in ensure_expr
raise TypeError(EXPR_TYPE_ERROR)
TypeError: Use col()/column() or lit()/literal() to construct expressions
>>> df.filter(dfn.col("a") == None).count()
0
>>> df.filter(dfn.col("a").is_null()).count()
1Describe the solution you'd like
I'd like to be able to compare against None like we can do with other scalar types. Ideally using both == and is semantics.
Describe alternatives you've considered
.is_null
Is your feature request related to a problem or challenge? Please describe what you are trying to do.
Describe the solution you'd like
I'd like to be able to compare against None like we can do with other scalar types. Ideally using both
==andissemantics.Describe alternatives you've considered
.is_null