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doc/source/basics.rst

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@@ -76,7 +76,7 @@ The exact details of what an :class:`~pandas.api.extensions.ExtensionArray` is a
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beyond the scope of this introduction. See :ref:`basics.dtypes` for more.
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If you know you need a NumPy array, use :meth:`~Series.to_numpy`
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or :meth:`np.asarray`.
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or :meth:`numpy.ndarray.asarray`.
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.. ipython:: python
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@@ -88,13 +88,13 @@ an :class:`~pandas.api.extensions.ExtensionArray`, :meth:`~Series.to_numpy`
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may involve copying data and coercing values. See :ref:`basics.dtypes` for more.
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:meth:`~Series.to_numpy` gives some control over the ``dtype`` of the
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resulting :class:`ndarray`. For example, consider datetimes with timezones.
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resulting :class:`numpy.ndarray`. For example, consider datetimes with timezones.
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NumPy doesn't have a dtype to represent timezone-aware datetimes, so there
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are two possibly useful representations:
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1. An object-dtype :class:`np.ndarray` with :class:`Timestamp` objects, each
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1. An object-dtype :class:`numpy.ndarray` with :class:`Timestamp` objects, each
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with the correct ``tz``
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2. A ``datetime64[ns]`` -dtype :class:`np.ndarray`, where the values have
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2. A ``datetime64[ns]`` -dtype :class:`numpy.ndarray`, where the values have
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been converted to UTC and the timezone discarded
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Timezones may be preserved with ``dtype=object``

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