DOC: Clarify broadcasting behavior when using lists in DataFrame arithmetic (GH18857)

doc/source/user_guide/basics.rst

@@ -209,6 +209,10 @@ either match on the *index* or *columns* via the **axis** keyword:
    df.sub(column, axis="index")
    df.sub(column, axis=0)
 
+Be careful when using raw Python lists in binary operations with DataFrames.
+Unlike NumPy arrays or Series, lists are not broadcast across rows or columns.
+Instead, pandas attempts to match the entire list against a single axis, which may lead to confusing results such as Series of arrays.
+To ensure proper broadcasting behavior, use a NumPy array or Series with explicit index or shape.
 Furthermore you can align a level of a MultiIndexed DataFrame with a Series.
 
 .. ipython:: python

doc/source/user_guide/dsintro.rst

@@ -650,6 +650,13 @@ row-wise. For example:
 
    df - df.iloc[0]
 
+Use .add(array, axis=0) to apply row-wise broadcasting when the array length matches the number of rows — 
+this ensures element-wise operations are performed across each row, rather than mistakenly aligning with columns.
+
+.. ipython:: python
+
+    df.add(np.array([1, 2, 3]), axis=0) 
+
 For explicit control over the matching and broadcasting behavior, see the
 section on :ref:`flexible binary operations <basics.binop>`.