docs: clarify usage of datafusion.col and datafusion.lit in DataFrame method documentation

Author: kosiew

python/datafusion/dataframe.py

@@ -421,6 +421,9 @@ def filter(self, *predicates: Expr) -> DataFrame:
         out. If more than one predicate is provided, these predicates will be
         combined as a logical AND. Each ``predicate`` must be an
         :class:`~datafusion.expr.Expr` created using helper functions such as
+        :func:`datafusion.col` or :func:`datafusion.lit`.
+        If more complex logic is required, see the logical operations in
+        :py:mod:`~datafusion.functions`.
 
         Example::
 
@@ -442,7 +445,7 @@ def with_column(self, name: str, expr: Expr) -> DataFrame:
         """Add an additional column to the DataFrame.
 
         The ``expr`` must be an :class:`~datafusion.expr.Expr` constructed with
-        accepted.
+        :func:`datafusion.col` or :func:`datafusion.lit`.
 
         Example::
 
@@ -465,7 +468,8 @@ def with_columns(
 
         By passing expressions, iterables of expressions, or named expressions.
         All expressions must be :class:`~datafusion.expr.Expr` objects created via
-        accepted. To pass named expressions use the form ``name=Expr``.
+        :func:`datafusion.col` or :func:`datafusion.lit`.
+        To pass named expressions use the form ``name=Expr``.
 
         Example usage: The following will add 4 columns labeled ``a``, ``b``, ``c``,
         and ``d``::
@@ -762,9 +766,8 @@ def join_on(
         """Join two :py:class:`DataFrame` using the specified expressions.
 
         Join predicates must be :class:`~datafusion.expr.Expr` objects, typically
-        built with :func:`datafusion.col`; On
-        expressions are used to support in-equality predicates. Equality predicates
-        are correctly optimized.
+        built with :func:`datafusion.col`. On expressions are used to support 
+        in-equality predicates. Equality predicates are correctly optimized.
 
         Example::