diff --git a/tutorial/transport/dantzig_model_linopy.py b/tutorial/transport/dantzig_model_linopy.py
index 4bc15ddd..0a55effe 100644
--- a/tutorial/transport/dantzig_model_linopy.py
+++ b/tutorial/transport/dantzig_model_linopy.py
@@ -14,6 +14,7 @@ def create_parameter(
 
 
 def create_dantzig_model(run: Run) -> linopy.Model:
+    """Creates new linopy.Model for Dantzig's problem based on ixmp4.Run."""
     m = linopy.Model()
     i = pd.Index(run.optimization.indexsets.get("i").elements, name="Canning Plants")
     j = pd.Index(run.optimization.indexsets.get("j").elements, name="Markets")
@@ -60,6 +61,7 @@ def create_dantzig_model(run: Run) -> linopy.Model:
 
 
 def read_dantzig_solution(model: linopy.Model, run: Run) -> None:
+    """Reads the Dantzig solution from linopy.Model to ixmp4.Run."""
     # Handle objective
     # TODO adding fake marginals here until Variables don't require this column anymore
     # Can't add units if this column was not declared above. Better stored as Scalar
@@ -87,7 +89,7 @@ def read_dantzig_solution(model: linopy.Model, run: Run) -> None:
     # The following don't seem to be typed correctly by linopy
     # Add supply data
     supply_data = {
-        "i": ["seattle", "san-diego"],
+        "i": run.optimization.indexsets.get("i").elements,
         "levels": model.constraints["Observe supply limit at plant i"].data.rhs,  # type: ignore
         "marginals": model.constraints["Observe supply limit at plant i"].data.dual,  # type: ignore
     }
@@ -95,7 +97,7 @@ def read_dantzig_solution(model: linopy.Model, run: Run) -> None:
 
     # Add demand data
     demand_data = {
-        "j": ["new-york", "chicago", "topeka"],
+        "j": run.optimization.indexsets.get("j").elements,
         "levels": model.constraints["Satisfy demand at market j"].data.rhs,  # type: ignore
         "marginals": model.constraints["Satisfy demand at market j"].data.dual,  # type: ignore
     }
diff --git a/tutorial/transport/linopy_transport.ipynb b/tutorial/transport/linopy_transport.ipynb
index 17ace268..37e6483d 100644
--- a/tutorial/transport/linopy_transport.ipynb
+++ b/tutorial/transport/linopy_transport.ipynb
@@ -244,7 +244,7 @@
     "a.add(data=a_data)\n",
     "\n",
     "# Demand at market j in cases\n",
-    "b = run.optimization.parameters.create(\"b\", constrained_to_indexsets=\"j\")\n",
+    "b = run.optimization.parameters.create(\"b\", constrained_to_indexsets=[\"j\"])\n",
     "# ... or a pd.DataFrame\n",
     "b_data = pd.DataFrame(\n",
     "    [\n",
@@ -349,7 +349,7 @@
    "source": [
     "### Defining `Variable`s and `Equation`s in the scenario\n",
     "\n",
-    "The levels and marginals of these variables and equations will be imported to the scenario when reading the model solution."
+    "The levels and marginals of these `Variable`s and `Equation`s will be imported to the scenario when reading the model solution."
    ]
   },
   {
@@ -387,7 +387,7 @@
     "\n",
     "In this tutorial, we solve the tutorial using the ``highs`` solver in linopy. \n",
     "\n",
-    "The ``create_dantzig_model()`` function is a convenience shortcut for setting up a linopy model correctly for the datzig scenario. Please see ``linopy_model.py`` for details.\n",
+    "The ``create_dantzig_model()`` function is a convenience shortcut for setting up a linopy model correctly for the dantzig scenario. Please see ``linopy_model.py`` for details.\n",
     "\n",
     "The solution data are stored with the model object automatically. ``store_dantzig_solution()`` then stores them in the ixmp4 objects."
    ]
@@ -403,10 +403,10 @@
     "    read_dantzig_solution,\n",
     ")\n",
     "\n",
-    "m = create_dantzig_model(run=run)\n",
-    "m.solve(\"highs\")\n",
+    "linopy_model = create_dantzig_model(run=run)\n",
+    "linopy_model.solve(\"highs\")\n",
     "\n",
-    "read_dantzig_solution(model=m, run=run)"
+    "read_dantzig_solution(model=linopy_model, run=run)"
    ]
   },
   {
@@ -433,7 +433,7 @@
    "outputs": [],
    "source": [
     "# Display the quantities transported from canning plants to demand locations\n",
-    "x.data"
+    "pd.DataFrame(x.data)"
    ]
   },
   {