diff --git a/docs/examples/model/grid_extensions_examples.ipynb b/docs/examples/model/grid_extensions_examples.ipynb
index 63ccf6c..e60b71a 100644
--- a/docs/examples/model/grid_extensions_examples.ipynb
+++ b/docs/examples/model/grid_extensions_examples.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "## Adding columns to the Grid arrays\n",
     "\n",
-    "Output variables are not present in the basic Grid as defined in gpm-ds, since these might or might not be useful to specific projects.\n",
+    "Output variables are not present in the basic Grid as defined in pgm-ds, since these might or might not be useful to specific projects.\n",
     "To add these as you please you can extend the definitions of the arrays in your own project.\n"
    ]
   },
diff --git a/docs/examples/utils/grid_from_txt_examples.ipynb b/docs/examples/utils/grid_from_txt_examples.ipynb
index f2a2890..66c71dd 100644
--- a/docs/examples/utils/grid_from_txt_examples.ipynb
+++ b/docs/examples/utils/grid_from_txt_examples.ipynb
@@ -20,7 +20,7 @@
     "If you follow a specific syntax, you can use the input from the\n",
     "graph editor to transfer your drawing to pgm-ds:\n",
     "\n",
-    "- A _source node_ should be prefixed with `S`\n",
+    "- A _substation node_ should be prefixed with `S`\n",
     "  - e.g: `S1`, `S2`\n",
     "- A _line_ is defined as `<from_node> <to_node>`\n",
     "  - From nodes can be both regular nodes and source nodes\n",
@@ -61,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -84,29 +84,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
     "from power_grid_model_ds import Grid\n",
     "\n",
     "grid = Grid.from_txt(\n",
-    "    [\n",
-    "        \"S1 2\",\n",
-    "        \"S1 3 open\",\n",
-    "        \"2 7\",\n",
-    "        \"3 5\",\n",
-    "        \"3 6 transformer\",\n",
-    "        \"5 7\",\n",
-    "        \"7 8\",\n",
-    "        \"8 9\",\n",
-    "    ]\n",
+    "    \"S1 2\",\n",
+    "    \"S1 3 open\",\n",
+    "    \"2 7\",\n",
+    "    \"3 5\",\n",
+    "    \"3 6 transformer\",\n",
+    "    \"5 7\",\n",
+    "    \"7 8\",\n",
+    "    \"8 9\",\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -132,7 +130,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "venv",
    "language": "python",
    "name": "python3"
   },
@@ -146,7 +144,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.1"
+   "version": "3.13.0"
   }
  },
  "nbformat": 4,
diff --git a/docs/model_interface.ipynb b/docs/model_interface.ipynb
index c87a9a1..525254f 100644
--- a/docs/model_interface.ipynb
+++ b/docs/model_interface.ipynb
@@ -87,23 +87,25 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "```py\n",
     "target_line = grid.arrays.line.get(1)\n",
-    "grid.make_active(target_branch_array=target_line)\n"
+    "grid.make_active(target_branch_array=target_line)\n",
+    "```\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As seen above you can also make batch modification using the `grid.append` method.\n",
+    "As seen above, you can also apply multiple modifications in one go using the `grid.append` method.\n",
     "\n",
     "## Array interface\n",
     "\n",
-    "The array container is build around a extension of numpy arrays with the `FancyArray` class. This allows for easy and consistent definition of array types, recognition of array-type from it's class and features which improve readability such as dot-notation and autocompletion. It contains a `._data` attribute with the base numpy array and extra settings can be provided using `._defaults` and `._str_lengths`. Note these values should only be used in defining the array classes and remain private when using the arrays.\n",
+    "The array container is build around a extension of numpy arrays with the `FancyArray` class. This allows for easy and consistent definition of array types, recognition of array-type from its class and features which improve readability such as dot-notation and autocompletion. It contains a `._data` attribute with the base numpy array and extra settings can be provided using `._defaults` and `._str_lengths`. Note these values should only be used in defining the array classes and remain private when using the arrays.\n",
     "\n",
     "### Array definition\n",
     "\n",
-    "You can create your own array by subclassing FancyArray.\n",
+    "You can create your own array by subclassing `FancyArray`.\n",
     "Array-columns can be defined by adding class attributes with the column name and the numpy dtype.\n",
     "\n",
     "Example:\n"
@@ -148,7 +150,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "These are used when initializing an array with the .empty method\n"
+    "These are used when initializing an array with the `.empty` method\n"
    ]
   },
   {
@@ -190,7 +192,7 @@
     "\n",
     "### Array loops\n",
     "\n",
-    "Looping over large arrays can be a performance hit, this is caused by casting each row to the original `FancyArray` subclass. When you want to implement a faster loop over the array you can choose to access the `array.data` directly and create the loop using\n"
+    "Looping over large arrays can incur a performance hit caused by conversion of each element to the original `FancyArray` subclass. When you want to implement a faster loop over the array you can choose to access the `array.data` directly and create the loop using\n"
    ]
   },
   {