diff --git a/vizro-core/docs/pages/tutorials/explore-components.md b/vizro-core/docs/pages/tutorials/explore-components.md
index 18c9de56a..fb69c4a34 100644
--- a/vizro-core/docs/pages/tutorials/explore-components.md
+++ b/vizro-core/docs/pages/tutorials/explore-components.md
@@ -459,11 +459,10 @@ You can apply selectors to configure [`Filters`][vizro.models.Filter] and [`Para
 - [`Slider`][vizro.models.Slider]
 
 ## 4. The final touches
-Each page is added to the dashboard using the following line of code: `vm.Dashboard(pages=[first_page, second_page])`. 
-This ensures that all the pages are accessible.
 
-By default, a navigation panel is added on the left side to switch between the two pages. 
+Each page is added to the dashboard using the following line of code: `vm.Dashboard(pages=[first_page, second_page])`. This ensures that all the pages are accessible.
 
+By default, a navigation panel is added on the left side to switch between the two pages.
 
 !!! example "Final dashboard"
     === "Code"
@@ -572,7 +571,6 @@ Vizro doesn't end here, and we only covered the key features, but there is still
 - How to use [Actions](../user-guides/actions.md) for example, for chart interaction or custom controls.
 - How to create dashboards from `yaml`, `dict` or `json` following the [dashboard guide](../user-guides/dashboard.md).
 
-[finalpage]: ../../assets/tutorials/dashboard/dashboard4.png
 [finalpage1]: ../../assets/tutorials/dashboard/dashboard2.png
 [finalpage2]: ../../assets/tutorials/dashboard/dashboard3.png
 [firstpage1]: ../../assets/tutorials/dashboard/dashboard21.png
diff --git a/vizro-core/examples/scratch_dev/app.py b/vizro-core/examples/scratch_dev/app.py
index 881961dab..403e2bd0e 100644
--- a/vizro-core/examples/scratch_dev/app.py
+++ b/vizro-core/examples/scratch_dev/app.py
@@ -6,8 +6,7 @@
 
 df = px.data.gapminder()
 gapminder_data = (
-    df.groupby(by=["continent", "year"]).
-    agg({"lifeExp": "mean", "pop": "sum", "gdpPercap": "mean"}).reset_index()
+    df.groupby(by=["continent", "year"]).agg({"lifeExp": "mean", "pop": "sum", "gdpPercap": "mean"}).reset_index()
 )
 first_page = vm.Page(
     title="First Page",
@@ -22,14 +21,23 @@
         ),
         vm.Graph(
             id="box_cont",
-            figure=px.box(gapminder_data, x="continent", y="lifeExp", color="continent",
-                          labels={"lifeExp": "Life Expectancy", "continent": "Continent"}),
+            figure=px.box(
+                gapminder_data,
+                x="continent",
+                y="lifeExp",
+                color="continent",
+                labels={"lifeExp": "Life Expectancy", "continent": "Continent"},
+            ),
         ),
         vm.Graph(
             id="line_gdp",
-            figure=px.line(gapminder_data, x="year", y="gdpPercap", color="continent",
-                           labels={"year": "Year", "continent": "Continent",
-                                   "gdpPercap": "GDP Per Cap"}),
+            figure=px.line(
+                gapminder_data,
+                x="year",
+                y="gdpPercap",
+                color="continent",
+                labels={"year": "Year", "continent": "Continent", "gdpPercap": "GDP Per Cap"},
+            ),
         ),
     ],
     controls=[
@@ -43,27 +51,30 @@
     components=[
         vm.Graph(
             id="scatter_iris",
-            figure=px.scatter(iris_data, x="sepal_width", y="sepal_length", color="species",
-                              color_discrete_map={"setosa": "#00b4ff", "versicolor": "#ff9222"},
-                              labels={"sepal_width": "Sepal Width", "sepal_length": "Sepal Length",
-                                      "species": "Species"},
-                              ),
+            figure=px.scatter(
+                iris_data,
+                x="sepal_width",
+                y="sepal_length",
+                color="species",
+                color_discrete_map={"setosa": "#00b4ff", "versicolor": "#ff9222"},
+                labels={"sepal_width": "Sepal Width", "sepal_length": "Sepal Length", "species": "Species"},
+            ),
         ),
         vm.Graph(
             id="hist_iris",
-            figure=px.histogram(iris_data, x="sepal_width", color="species",
-                                color_discrete_map={"setosa": "#00b4ff", "versicolor": "#ff9222"},
-                                labels={"sepal_width": "Sepal Width", "count": "Count",
-                                        "species": "Species"},
-                                ),
+            figure=px.histogram(
+                iris_data,
+                x="sepal_width",
+                color="species",
+                color_discrete_map={"setosa": "#00b4ff", "versicolor": "#ff9222"},
+                labels={"sepal_width": "Sepal Width", "count": "Count", "species": "Species"},
+            ),
         ),
     ],
     controls=[
         vm.Parameter(
-            targets=["scatter_iris.color_discrete_map.virginica",
-                     "hist_iris.color_discrete_map.virginica"],
-            selector=vm.Dropdown(
-                options=["#ff5267", "#3949ab"], multi=False, value="#3949ab", title="Color Virginica"),
+            targets=["scatter_iris.color_discrete_map.virginica", "hist_iris.color_discrete_map.virginica"],
+            selector=vm.Dropdown(options=["#ff5267", "#3949ab"], multi=False, value="#3949ab", title="Color Virginica"),
         ),
         vm.Parameter(
             targets=["scatter_iris.opacity"],