kosiew commented on code in PR #1221:
URL:
https://github.com/apache/datafusion-python/pull/1221#discussion_r2347813005
##########
docs/source/user-guide/dataframe/index.rst:
##########
@@ -126,6 +126,53 @@ DataFusion's DataFrame API offers a wide range of
operations:
# Drop columns
df = df.drop("temporary_column")
+String Columns and Expressions
+------------------------------
+
+Some ``DataFrame`` methods accept plain strings when an argument refers to an
+existing column. These include:
+
+* :py:meth:`~datafusion.DataFrame.select`
+* :py:meth:`~datafusion.DataFrame.sort`
+* :py:meth:`~datafusion.DataFrame.drop`
+* :py:meth:`~datafusion.DataFrame.join` (``on`` argument)
+* :py:meth:`~datafusion.DataFrame.aggregate` (grouping columns)
+
+Note that :py:meth:`~datafusion.DataFrame.join_on` expects
``col()``/``column()`` expressions rather than plain strings.
+
+For such methods, you can pass column names directly:
+
+.. code-block:: python
+
+ from datafusion import col, functions as f
+
+ df.sort('id')
+ df.aggregate('id', [f.count(col('value'))])
+
+The same operation can also be written with explicit column expressions, using
either ``col()`` or ``column()``:
+
+.. code-block:: python
+
+ from datafusion import col, column, functions as f
+
+ df.sort(col('id'))
+ df.aggregate(column('id'), [f.count(col('value'))])
+
+Note that ``column()`` is an alias of ``col()``, so you can use either name;
the example above shows both in action.
+
+Whenever an argument represents an expression—such as in
+:py:meth:`~datafusion.DataFrame.filter` or
+:py:meth:`~datafusion.DataFrame.with_column`—use ``col()`` to reference columns
+and wrap constant values with ``lit()`` (also available as ``literal()``):
+
+.. code-block:: python
+
+ from datafusion import col, lit
+ df.filter(col('age') > lit(21))
+
+Without ``lit()`` DataFusion would treat ``21`` as a column name rather than a
+constant value.
Review Comment:
You're right.
The comparison operators on Expr automatically convert any non-Expr value
into a literal expression,
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