DOC: Clarify parentheses vs. brackets usage (GH#62314) updated

Author: AnandMukherjee2004

doc/source/getting_started/intro_tutorials/11_brackets_vs_parenthesis.rst

@@ -1,6 +1,7 @@
-.. _10min_tut_11_brackets_vs_parenthesis:
+In both Python and pandas, it’s important to understand the difference between parentheses ``()`` and square brackets ``[]``:
 
-Parentheses vs. Square Brackets in Python and pandas
-====================================================
+- **Parentheses** are used to call functions and methods. For example, ``df.mean()`` calculates the mean of a DataFrame, and parentheses are also used to group expressions, such as ``(a + b) * c``, or to create tuples: ``(1, 2, 3)``.
+- **Square brackets** are used for indexing, selecting data, and defining lists. In pandas, you use square brackets to select columns or filter data—for instance, ``df['A']`` selects column ``A``, while ``df[0:3]`` selects rows by position. In standard Python, square brackets are also used to define a list, as in ``my_list = [1, 2, 3]``.
 
-In Python and pandas, parentheses ``()`` and square brackets ``[]`` have distinct uses, which can sometimes be confusing for new users. Parentheses are used to call functions and methods (for example, ``df.mean()``), to group expressions in calculations (such as ``(a + b) * c``), and to create tuples. Square brackets, on the other hand, are used for defining lists and for indexing or selecting data—in both core Python and pandas. For example, ``df['A']`` selects column ``A`` from a DataFrame, and ``df[0:3]`` selects rows by position. In pandas, square brackets are always used when you want to select or filter data, while parentheses are used any time you are calling a method or function. Remember: use ``[]`` for selection or indexing, and ``()`` for function calls and grouping.
+Remember:  
+**Use [] for selection or indexing, and () for calling functions or grouping expressions.**