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		:ref:`To user guide <text>`

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	How to use parentheses vs square brackets?
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	:ref:`Straight to tutorial...<10min_tut_11_brackets_vs_parenthesis>`

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	Understanding the difference between parentheses and square brackets is crucial for pandas users. Parentheses are used for function calls and grouping, while square brackets are for indexing and selection.

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	:ref:`To introduction tutorial <10min_tut_11_brackets_vs_parenthesis>`

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	:ref:`To user guide <indexing>`

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	.. _10min_tut_11_brackets_vs_parenthesis:

	Parentheses vs. Square Brackets in Python and pandas
	====================================================

	In both Python and pandas, it is important to understand the difference between parentheses ``()`` and square brackets ``[]``:

	- Parentheses are used to call functions and methods. For example, ``df.mean()`` calculates the mean of a DataFrame. 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]``.

	Remember: Use ``[]`` for selection or indexing, and ``()`` for calling functions or grouping expressions.

	For more explanation, see `Brackets in Python and pandas <https://python-public-policy.afeld.me/en/columbia/brackets.html>`__.

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