From c80ca5c21dd0fc6bc92cd74c03eb30648f322d5a Mon Sep 17 00:00:00 2001 From: "Christine P. Chai" Date: Sat, 22 Mar 2025 14:43:05 -0700 Subject: [PATCH] DOC: Add punctuation to basics.rst in User Guide --- doc/source/user_guide/basics.rst | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/doc/source/user_guide/basics.rst b/doc/source/user_guide/basics.rst index ffd7a2ad7bb01..14af5d9dc22c8 100644 --- a/doc/source/user_guide/basics.rst +++ b/doc/source/user_guide/basics.rst @@ -36,7 +36,7 @@ of elements to display is five, but you may pass a custom number. Attributes and underlying data ------------------------------ -pandas objects have a number of attributes enabling you to access the metadata +pandas objects have a number of attributes enabling you to access the metadata. * **shape**: gives the axis dimensions of the object, consistent with ndarray * Axis labels @@ -59,7 +59,7 @@ NumPy's type system to add support for custom arrays (see :ref:`basics.dtypes`). To get the actual data inside a :class:`Index` or :class:`Series`, use -the ``.array`` property +the ``.array`` property. .. ipython:: python @@ -88,18 +88,18 @@ NumPy doesn't have a dtype to represent timezone-aware datetimes, so there are two possibly useful representations: 1. An object-dtype :class:`numpy.ndarray` with :class:`Timestamp` objects, each - with the correct ``tz`` + with the correct ``tz``. 2. A ``datetime64[ns]`` -dtype :class:`numpy.ndarray`, where the values have - been converted to UTC and the timezone discarded + been converted to UTC and the timezone discarded. -Timezones may be preserved with ``dtype=object`` +Timezones may be preserved with ``dtype=object``: .. ipython:: python ser = pd.Series(pd.date_range("2000", periods=2, tz="CET")) ser.to_numpy(dtype=object) -Or thrown away with ``dtype='datetime64[ns]'`` +Or thrown away with ``dtype='datetime64[ns]'``: .. ipython:: python