Create arrow object

_episodes/02-data.md

@@ -145,6 +145,14 @@ e.g. how many dimensions does our array have, and of what size?
 This is represented by the `shape` of an array, which denotes the length of the array in each dimension.
 e.g. for the toy arrow example above:
 ~~~
+import numpy as np  # this is how numpy is traditionally loaded
+
+# Our arrow as displayed in the figure above
+arrow = np.array([[255, 255, 255,   0],
+                  [  0, 255,   0, 255],
+                  [  0,   0, 255, 255],
+                  [  0,   0,   0, 255]])
+
 print(arrow.shape)
 print(arrow.ndim)
 ~~~
@@ -163,7 +171,6 @@ section).
 
 Finally, we might want to calculate some summary statistics for our array like the mean or standard deviation.
 ~~~
-import numpy as np  # this is how numpy is traditionally installed
 print(np.mean(raw))
 print(np.std(raw))
 ~~~