convert memory expensive dask example docs to verbatim

Author: DocOtak

doc/dask.rst

@@ -125,10 +125,22 @@ will return a Dask delayed object that can be computed later.
 
 A dataset can also be converted to a Dask DataFrame using :py:meth:`~xarray.Dataset.to_dask_dataframe`.
 
-.. ipython:: python
+.. ipython::
+    :verbatim:
 
-    df = ds.to_dask_dataframe()
-    df
+    In [8]: df = ds.to_dask_dataframe()
+
+    In [9]: df
+    Out[9]:
+    Dask DataFrame Structure:
+                   latitude longitude            time temperature
+    npartitions=44                                               
+    0               float64     int64  datetime64[ns]     float64
+    525600              ...       ...             ...         ...
+    ...                 ...       ...             ...         ...
+    22600800            ...       ...             ...         ...
+    23651999            ...       ...             ...         ...
+    Dask Name: concat-indexed, 1481 tasks
 
 Dask DataFrames do not support multi-indexes so the coordinate variables from the dataset are included as columns in the Dask DataFrame.
 
@@ -226,10 +238,22 @@ NumPy ufuncs like ``np.sin`` currently only work on eagerly evaluated arrays
 replacements that also work on all xarray objects, including those that store
 lazy Dask arrays, in the :ref:`xarray.ufuncs <api.ufuncs>` module:
 
-.. ipython:: python
+.. ipython::
+    :verbatim:
+
+    In [16]: import xarray.ufuncs as xu
+
+    In [17]: xu.sin(rechunked)
+    Out[17]: 
+    <xarray.Dataset>
+    Dimensions:      (latitude: 180, longitude: 360, time: 365)
+    Coordinates:
+      * time         (time) datetime64[ns] 2015-01-01 2015-01-02 ... 2015-12-31
+      * longitude    (longitude) int64 0 1 2 3 4 5 6 ... 353 354 355 356 357 358 359
+      * latitude     (latitude) float64 89.5 88.5 87.5 86.5 ... -87.5 -88.5 -89.5
+    Data variables:
+        temperature  (time, latitude, longitude) float64 0.4521 -0.2791 ... 0.005886
 
-    import xarray.ufuncs as xu
-    xu.sin(rechunked)
 
 To access Dask arrays directly, use the new
 :py:attr:`DataArray.data <xarray.DataArray.data>` attribute. This attribute exposes