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funnycrabTomAugspurger
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DOC: Fix a typo in indexing.rst (#15916)
* DOC: Fix a typo in indexing.rst * more typos fixed
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doc/source/indexing.rst

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@@ -69,7 +69,7 @@ Different Choices for Indexing
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.. versionadded:: 0.11.0
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Object selection has had a number of user-requested additions in order to
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support more explicit location based indexing. pandas now supports three types
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support more explicit location based indexing. Pandas now supports three types
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of multi-axis indexing.
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- ``.loc`` is primarily label based, but may also be used with a boolean array. ``.loc`` will raise ``KeyError`` when the items are not found. Allowed inputs are:
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This is sometimes called ``chained assignment`` and should be avoided.
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See :ref:`Returning a View versus Copy <indexing.view_versus_copy>`
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pandas provides a suite of methods in order to get **purely integer based indexing**. The semantics follow closely python and numpy slicing. These are ``0-based`` indexing. When slicing, the start bounds is *included*, while the upper bound is *excluded*. Trying to use a non-integer, even a **valid** label will raise a ``IndexError``.
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Pandas provides a suite of methods in order to get **purely integer based indexing**. The semantics follow closely python and numpy slicing. These are ``0-based`` indexing. When slicing, the start bounds is *included*, while the upper bound is *excluded*. Trying to use a non-integer, even a **valid** label will raise an ``IndexError``.
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The ``.iloc`` attribute is the primary access method. The following are valid inputs:
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