@@ -36,7 +36,7 @@ of elements to display is five, but you may pass a custom number.
3636Attributes and underlying data
3737------------------------------
3838
39- pandas objects have a number of attributes enabling you to access the metadata
39+ pandas objects have a number of attributes enabling you to access the metadata.
4040
4141* **shape **: gives the axis dimensions of the object, consistent with ndarray
4242* Axis labels
@@ -59,7 +59,7 @@ NumPy's type system to add support for custom arrays
5959(see :ref: `basics.dtypes `).
6060
6161To get the actual data inside a :class: `Index ` or :class: `Series `, use
62- the ``.array `` property
62+ the ``.array `` property.
6363
6464.. ipython :: python
6565
@@ -88,18 +88,18 @@ NumPy doesn't have a dtype to represent timezone-aware datetimes, so there
8888are two possibly useful representations:
8989
90901. An object-dtype :class: `numpy.ndarray ` with :class: `Timestamp ` objects, each
91- with the correct ``tz ``
91+ with the correct ``tz ``.
92922. A ``datetime64[ns] `` -dtype :class: `numpy.ndarray `, where the values have
93- been converted to UTC and the timezone discarded
93+ been converted to UTC and the timezone discarded.
9494
95- Timezones may be preserved with ``dtype=object ``
95+ Timezones may be preserved with ``dtype=object ``:
9696
9797.. ipython :: python
9898
9999 ser = pd.Series(pd.date_range(" 2000" , periods = 2 , tz = " CET" ))
100100 ser.to_numpy(dtype = object )
101101
102- Or thrown away with ``dtype='datetime64[ns]' ``
102+ Or thrown away with ``dtype='datetime64[ns]' ``:
103103
104104.. ipython :: python
105105
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