Ah ha I think I got it

Author: hexgnu

pandas/_libs/lib.pyx

@@ -59,6 +59,12 @@ def memory_usage_of_objects(ndarray[object, ndim=1] arr):
     cdef Py_ssize_t i, n
     cdef int64_t s = 0
 
+    # The problem here is that... 
+    # A SparseArray of size 1 that has fill_value = the only value
+    # will cause this
+
+    # n = 1
+    #   
     n = len(arr)
     for i in range(n):
         s += arr[i].__sizeof__()

pandas/core/base.py

@@ -1069,12 +1069,18 @@ def memory_usage(self, deep=False):
         --------
         numpy.ndarray.nbytes
         """
-        if hasattr(self.values, 'memory_usage'):
-            return self.values.memory_usage(deep=deep)
+        # Use sparse values if they exist for memory consumption
+        if hasattr(self.values, 'sp_values'):
+            values = self.values.sp_values
+        else:
+            values = self.values
+
+        if hasattr(values, 'memory_usage'):
+            return values.memory_usage(deep=deep)
 
-        v = self.values.nbytes
+        v = values.nbytes
         if deep and is_object_dtype(self) and not PYPY:
-            v += lib.memory_usage_of_objects(self.values)
+            v += lib.memory_usage_of_objects(values)
         return v
 
     def factorize(self, sort=False, na_sentinel=-1):