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DOC: Add missing punctuation in text.rst
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doc/source/user_guide/text.rst

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@@ -13,7 +13,7 @@ Text data types
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There are two ways to store text data in pandas:
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1. ``object`` -dtype NumPy array.
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1. ``object`` dtype NumPy array.
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2. :class:`StringDtype` extension type.
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We recommend using :class:`StringDtype` to store text data.
@@ -40,20 +40,20 @@ to significantly increase the performance and lower the memory overhead of
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and parts of the API may change without warning.
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For backwards-compatibility, ``object`` dtype remains the default type we
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infer a list of strings to
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infer a list of strings to:
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.. ipython:: python
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pd.Series(["a", "b", "c"])
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To explicitly request ``string`` dtype, specify the ``dtype``
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To explicitly request ``string`` dtype, specify the ``dtype``:
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.. ipython:: python
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pd.Series(["a", "b", "c"], dtype="string")
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pd.Series(["a", "b", "c"], dtype=pd.StringDtype())
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Or ``astype`` after the ``Series`` or ``DataFrame`` is created
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Or ``astype`` after the ``Series`` or ``DataFrame`` is created:
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.. ipython:: python
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@@ -88,7 +88,7 @@ Behavior differences
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^^^^^^^^^^^^^^^^^^^^
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These are places where the behavior of ``StringDtype`` objects differ from
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``object`` dtype
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``object`` dtype:
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l. For ``StringDtype``, :ref:`string accessor methods<api.series.str>`
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that return **numeric** output will always return a nullable integer dtype,
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s.str.count("a")
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s.dropna().str.count("a")
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Both outputs are ``Int64`` dtype. Compare that with object-dtype
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Both outputs are ``Int64`` dtype. Compare that with object-dtype:
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.. ipython:: python
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