diff --git a/mesa/examples/advanced/epstein_civil_violence/app.py b/mesa/examples/advanced/epstein_civil_violence/app.py
index 538ef186f57..99304cd4618 100644
--- a/mesa/examples/advanced/epstein_civil_violence/app.py
+++ b/mesa/examples/advanced/epstein_civil_violence/app.py
@@ -25,7 +25,7 @@ def citizen_cop_portrayal(agent):
         return
 
     portrayal = {
-        "size": 25,
+        "size": 50,
     }
 
     if isinstance(agent, Citizen):
@@ -36,6 +36,13 @@ def citizen_cop_portrayal(agent):
     return portrayal
 
 
+def post_process(ax):
+    ax.set_aspect("equal")
+    ax.set_xticks([])
+    ax.set_yticks([])
+    ax.get_figure().set_size_inches(10, 10)
+
+
 model_params = {
     "height": 40,
     "width": 40,
@@ -47,8 +54,13 @@ def citizen_cop_portrayal(agent):
     "max_jail_term": Slider("Max Jail Term", 30, 0, 50, 1),
 }
 
-space_component = make_space_component(citizen_cop_portrayal)
-chart_component = make_plot_measure([state.name.lower() for state in CitizenState])
+space_component = make_space_component(
+    citizen_cop_portrayal, post_process=post_process, draw_grid=False
+)
+
+chart_component = make_plot_measure(
+    {state.name.lower(): agent_colors[state] for state in CitizenState}
+)
 
 epstein_model = EpsteinCivilViolence()
 
diff --git a/mesa/examples/advanced/pd_grid/app.py b/mesa/examples/advanced/pd_grid/app.py
index 6edf8140536..d5bfd626e3c 100644
--- a/mesa/examples/advanced/pd_grid/app.py
+++ b/mesa/examples/advanced/pd_grid/app.py
@@ -13,7 +13,7 @@ def pd_agent_portrayal(agent):
     """
     return {
         "color": "blue" if agent.move == "C" else "red",
-        "shape": "s",  # square marker
+        "marker": "s",  # square marker
         "size": 25,
     }
 
diff --git a/mesa/examples/advanced/sugarscape_g1mt/app.py b/mesa/examples/advanced/sugarscape_g1mt/app.py
index 752998891bd..39969e24079 100644
--- a/mesa/examples/advanced/sugarscape_g1mt/app.py
+++ b/mesa/examples/advanced/sugarscape_g1mt/app.py
@@ -1,9 +1,9 @@
 import numpy as np
 import solara
 from matplotlib.figure import Figure
-from sugarscape_g1mt.model import SugarscapeG1mt
-from sugarscape_g1mt.trader_agents import Trader
 
+from mesa.examples.advanced.sugarscape_g1mt.agents import Trader
+from mesa.examples.advanced.sugarscape_g1mt.model import SugarscapeG1mt
 from mesa.visualization import SolaraViz, make_plot_measure
 
 
@@ -57,6 +57,6 @@ def portray(g):
     model1,
     components=[SpaceDrawer, make_plot_measure(["Trader", "Price"])],
     name="Sugarscape {G1, M, T}",
-    play_interval=1500,
+    play_interval=150,
 )
 page  # noqa
diff --git a/mesa/examples/basic/conways_game_of_life/app.py b/mesa/examples/basic/conways_game_of_life/app.py
index 7a45125a30a..168681b7ba6 100644
--- a/mesa/examples/basic/conways_game_of_life/app.py
+++ b/mesa/examples/basic/conways_game_of_life/app.py
@@ -6,7 +6,17 @@
 
 
 def agent_portrayal(agent):
-    return {"c": "white" if agent.state == 0 else "black", "marker": "s"}
+    return {
+        "color": "white" if agent.state == 0 else "black",
+        "marker": "s",
+        "size": 25,
+    }
+
+
+def post_process(ax):
+    ax.set_aspect("equal")
+    ax.set_xticks([])
+    ax.set_yticks([])
 
 
 model_params = {
@@ -22,7 +32,9 @@ def agent_portrayal(agent):
 # Under the hood these are just classes that receive the model instance.
 # You can also author your own visualization elements, which can also be functions
 # that receive the model instance and return a valid solara component.
-SpaceGraph = make_space_component(agent_portrayal)
+SpaceGraph = make_space_component(
+    agent_portrayal, post_process=post_process, draw_grid=False
+)
 
 
 # Create the SolaraViz page. This will automatically create a server and display the
diff --git a/mesa/examples/basic/schelling/app.py b/mesa/examples/basic/schelling/app.py
index 53fab7ba0f0..86f5a2941fd 100644
--- a/mesa/examples/basic/schelling/app.py
+++ b/mesa/examples/basic/schelling/app.py
@@ -28,13 +28,13 @@ def agent_portrayal(agent):
 
 model1 = Schelling(20, 20, 0.8, 0.2, 3)
 
-HappyPlot = make_plot_measure("happy")
+HappyPlot = make_plot_measure({"happy": "tab:green"})
 
 page = SolaraViz(
     model1,
     components=[
         make_space_component(agent_portrayal),
-        make_plot_measure("happy"),
+        HappyPlot,
         get_happy_agents,
     ],
     model_params=model_params,
diff --git a/mesa/examples/basic/virus_on_network/app.py b/mesa/examples/basic/virus_on_network/app.py
index 7cf54f308d5..8e82a72830c 100644
--- a/mesa/examples/basic/virus_on_network/app.py
+++ b/mesa/examples/basic/virus_on_network/app.py
@@ -1,44 +1,27 @@
 import math
 
 import solara
-from matplotlib.figure import Figure
-from matplotlib.ticker import MaxNLocator
 
 from mesa.examples.basic.virus_on_network.model import (
     State,
     VirusOnNetwork,
     number_infected,
 )
-from mesa.visualization import Slider, SolaraViz, make_space_component
-
+from mesa.visualization import (
+    Slider,
+    SolaraViz,
+    make_plot_measure,
+    make_space_component,
+)
 
-def agent_portrayal(graph):
-    def get_agent(node):
-        return graph.nodes[node]["agent"][0]
 
-    edge_width = []
-    edge_color = []
-    for u, v in graph.edges():
-        agent1 = get_agent(u)
-        agent2 = get_agent(v)
-        w = 2
-        ec = "#e8e8e8"
-        if State.RESISTANT in (agent1.state, agent2.state):
-            w = 3
-            ec = "black"
-        edge_width.append(w)
-        edge_color.append(ec)
+def agent_portrayal(agent):
     node_color_dict = {
         State.INFECTED: "tab:red",
         State.SUSCEPTIBLE: "tab:green",
         State.RESISTANT: "tab:gray",
     }
-    node_color = [node_color_dict[get_agent(node).state] for node in graph.nodes()]
-    return {
-        "width": edge_width,
-        "edge_color": edge_color,
-        "node_color": node_color,
-    }
+    return {"color": node_color_dict[agent.state], "size": 10}
 
 
 def get_resistant_susceptible_ratio(model):
@@ -46,25 +29,9 @@ def get_resistant_susceptible_ratio(model):
     ratio_text = r"$\infty$" if ratio is math.inf else f"{ratio:.2f}"
     infected_text = str(number_infected(model))
 
-    return f"Resistant/Susceptible Ratio: {ratio_text}<br>Infected Remaining: {infected_text}"
-
-
-def make_plot(model):
-    # This is for the case when we want to plot multiple measures in 1 figure.
-    fig = Figure()
-    ax = fig.subplots()
-    measures = ["Infected", "Susceptible", "Resistant"]
-    colors = ["tab:red", "tab:green", "tab:gray"]
-    for i, m in enumerate(measures):
-        color = colors[i]
-        df = model.datacollector.get_model_vars_dataframe()
-        ax.plot(df.loc[:, m], label=m, color=color)
-    fig.legend()
-    # Set integer x axis
-    ax.xaxis.set_major_locator(MaxNLocator(integer=True))
-    ax.set_xlabel("Step")
-    ax.set_ylabel("Number of Agents")
-    return solara.FigureMatplotlib(fig)
+    return solara.Markdown(
+        f"Resistant/Susceptible Ratio: {ratio_text}<br>Infected Remaining: {infected_text}"
+    )
 
 
 model_params = {
@@ -120,6 +87,9 @@ def make_plot(model):
 }
 
 SpacePlot = make_space_component(agent_portrayal)
+StatePlot = make_plot_measure(
+    {"Infected": "tab:red", "Susceptible": "tab:green", "Resistant": "tab:gray"}
+)
 
 model1 = VirusOnNetwork()
 
@@ -127,8 +97,8 @@ def make_plot(model):
     model1,
     [
         SpacePlot,
-        make_plot,
-        # get_resistant_susceptible_ratio,  # TODO: Fix and uncomment
+        StatePlot,
+        get_resistant_susceptible_ratio,
     ],
     model_params=model_params,
     name="Virus Model",