diff --git a/src/aki_prj23_transparenzregister/ui/company_elements.py b/src/aki_prj23_transparenzregister/ui/company_elements.py
index 938f42f..3859417 100644
--- a/src/aki_prj23_transparenzregister/ui/company_elements.py
+++ b/src/aki_prj23_transparenzregister/ui/company_elements.py
@@ -15,10 +15,11 @@ from aki_prj23_transparenzregister.ui import (
     sentiment_elements,
 )
 from aki_prj23_transparenzregister.utils.networkx.network_2d import create_2d_graph
-from aki_prj23_transparenzregister.utils.networkx.network_base import initialize_network
+from aki_prj23_transparenzregister.utils.networkx.network_base import (
+    initialize_network_without_metrics,
+)
 from aki_prj23_transparenzregister.utils.networkx.networkx_data import (
-    create_edge_and_node_list_for_company,
-    find_company_relations,
+    get_relations_until_level_3,
 )
 
 COLORS = {
@@ -414,20 +415,16 @@ def network_layout(selected_company_id: int) -> html.Div:
     Returns:
         The html div to create the network tab of the company page.
     """
-    person_relations, company_relations = find_company_relations(selected_company_id)
-
-    # Create Edge and Node List from data
-    nodes, edges = create_edge_and_node_list_for_company(company_relations)
+    nodes, edges = get_relations_until_level_3(f"c_{str(selected_company_id)}")
     # Initialize the Network and receive the Graph and a DataFrame with Metrics
     if nodes != {}:
-        graph, metrics = initialize_network(nodes=nodes, edges=edges)
-        metric = "None"
+        graph = initialize_network_without_metrics(nodes=nodes, edges=edges)
         figure = create_2d_graph(
             graph,
             nodes,
             edges,
-            metrics,
-            metric,
+            pd.DataFrame(),
+            metric="None",
             layout="Spring",
             edge_annotation=True,
             edge_thickness=1,
diff --git a/src/aki_prj23_transparenzregister/ui/pages/person.py b/src/aki_prj23_transparenzregister/ui/pages/person.py
index dff55e3..2391ea6 100644
--- a/src/aki_prj23_transparenzregister/ui/pages/person.py
+++ b/src/aki_prj23_transparenzregister/ui/pages/person.py
@@ -31,12 +31,7 @@ def layout(value: str = "1") -> html.Div:
     # get all necessary data of the selected person
     selected_person_stats = data_elements.get_person_data(session).loc[person_id]
     selected_person_name = f"{selected_person_stats['person_firstname']} {selected_person_stats['person_lastname']}"
-    return (
-        person_elements.create_person_widgets(person_id, selected_person_name),
-        html.Div(
-            className="person-network", children=["Hier kann der Social Graph hin"]
-        ),
-    )
+    return person_elements.create_person_widgets(person_id, selected_person_name)
 
 
 @callback(
diff --git a/src/aki_prj23_transparenzregister/ui/person_elements.py b/src/aki_prj23_transparenzregister/ui/person_elements.py
index 0bfcb7c..ee13f7a 100644
--- a/src/aki_prj23_transparenzregister/ui/person_elements.py
+++ b/src/aki_prj23_transparenzregister/ui/person_elements.py
@@ -1,9 +1,15 @@
 """Dash elements for person page."""
 import networkx as nx
-from dash import html
+import pandas as pd
+from dash import dcc, html
 
+from aki_prj23_transparenzregister.utils.networkx.network_2d import create_2d_graph
+from aki_prj23_transparenzregister.utils.networkx.network_base import (
+    initialize_network_without_metrics,
+)
 from aki_prj23_transparenzregister.utils.networkx.networkx_data import (
     get_relations_number_from_id,
+    get_relations_until_level_3,
 )
 
 
@@ -44,7 +50,7 @@ def create_person_widgets(selected_person_id: int, selected_person_name: str) ->
     """
     try:
         first_level, second_level, third_level = get_relations_number_from_id(
-            selected_person_id
+            f"p_{selected_person_id}"
         )
 
     except nx.exception.NetworkXError:
@@ -67,13 +73,56 @@ def create_person_widgets(selected_person_id: int, selected_person_name: str) ->
                 ],
             ),
             create_small_widget(
-                ["Anzahl Verbindungen", html.Br(), " - erste Ebene"], [first_level]
+                ["Anzahl Verbindungen", html.Br(), "1. Ebene"], [first_level]
             ),
             create_small_widget(
-                ["Anzahl Verbindungen", html.Br(), " - dritte Ebene"], [second_level]
+                ["Anzahl Verbindungen", html.Br(), "2. Ebene"], [second_level]
             ),
             create_small_widget(
-                ["Anzahl Verbindungen", html.Br(), " - dritte Ebene"], [third_level]
+                ["Anzahl Verbindungen", html.Br(), "3. Ebene"], [third_level]
             ),
+            network_layout(selected_person_id),
+        ],
+    )
+
+
+def network_layout(selected_person_id: int) -> html.Div:
+    """Create network tab.
+
+    Args:
+        selected_person_id: Id of the chosen person in the dropdown.
+
+    Returns:
+        The html div to create the network tab of the person page.
+    """
+    nodes, edges = get_relations_until_level_3(f"p_{selected_person_id}")
+    # Initialize the Network and receive the Graph and a DataFrame with Metrics
+    if nodes != {}:
+        graph = initialize_network_without_metrics(nodes=nodes, edges=edges)
+        figure = create_2d_graph(
+            graph,
+            nodes,
+            edges,
+            pd.DataFrame([]),
+            metric="None",
+            layout="Spring",
+            edge_annotation=True,
+            edge_thickness=1,
+        )
+        return html.Div(
+            children=[
+                dcc.Graph(figure=figure, id="person-graph", className="graph-style")
+            ]
+        )
+
+    return html.Div(
+        className="choose-metric",
+        children=[
+            html.H3(
+                className="metrics-title",
+                children=[
+                    "Für diese Person wurden leider keine Verflechtungen gefunden."
+                ],
+            )
         ],
     )
diff --git a/src/aki_prj23_transparenzregister/utils/networkx/network_2d.py b/src/aki_prj23_transparenzregister/utils/networkx/network_2d.py
index 8bd993d..c6ee701 100644
--- a/src/aki_prj23_transparenzregister/utils/networkx/network_2d.py
+++ b/src/aki_prj23_transparenzregister/utils/networkx/network_2d.py
@@ -72,6 +72,8 @@ def create_2d_graph(  # noqa PLR0913
         node_x.append(x)
         node_y.append(y)
 
+    edge_type_list = [row["type"] for row in edges]
+
     # Add the Edges to the scatter plot according to their Positions.
     edge_trace = go.Scatter(
         x=edge_x,
@@ -80,16 +82,29 @@ def create_2d_graph(  # noqa PLR0913
         hoverinfo="none",
         mode="lines",
     )
+
     # Add the Edge description text to the scatter plot according to its Position.
-    edge_weights_trace = go.Scatter(
-        x=edge_weight_x,
-        y=edge_weight_y,
-        mode="text",
-        marker_size=0.5,
-        text=[0.45, 0.7, 0.34],
-        textposition="top center",
-        hovertemplate="Relation: %{text}<extra></extra>",
-    )
+    if edge_annotation is True:
+        edge_weights_trace = go.Scatter(
+            x=edge_weight_x,
+            y=edge_weight_y,
+            mode="text",
+            marker_size=0.5,
+            text=[0.45, 0.7, 0.34],
+            textposition="top center",
+            hoverinfo="none",
+        )
+    else:
+        edge_weights_trace = go.Scatter(
+            x=edge_weight_x,
+            y=edge_weight_y,
+            mode="text",
+            marker_size=0.5,
+            text=[0.45, 0.7, 0.34],
+            textposition="top center",
+            hovertemplate="Relation: %{hovertext}<extra></extra>",
+            hovertext=edge_type_list,
+        )
 
     # Add the Nodes to the scatter plot according to their Positions.
     node_trace = go.Scatter(
@@ -106,9 +121,7 @@ def create_2d_graph(  # noqa PLR0913
     # # Set Color by using the nodes DataFrame with its Color Attribute. The sequence matters!
     colors = list(nx.get_node_attributes(graph, "color").values())
     node_names = list(nx.get_node_attributes(graph, "name").values())
-    # ids = list(nx.get_node_attributes(graph, "id").values())
 
-    # # Get the Node Text
     node_trace.marker.color = colors
     node_trace.marker.line = {"color": "#2e2c2f", "width": 0.5}
     node_trace.text = node_names
@@ -118,10 +131,7 @@ def create_2d_graph(  # noqa PLR0913
         node_trace.marker.size = list(np.sqrt(metrics[metric]) * 200)
 
     # Add Relation_Type as a Description for the edges.
-    if edge_annotation:
-        edge_type_list = [
-            row["type"] for row in edges
-        ]  # this code be moved and used as hover data
+    if edge_annotation is True:  # this code be moved and used as hover data
         edge_weights_trace.text = edge_type_list
 
     # Return the Plotly Figure
diff --git a/src/aki_prj23_transparenzregister/utils/networkx/networkx_data.py b/src/aki_prj23_transparenzregister/utils/networkx/networkx_data.py
index 19f3b9c..47aebd8 100644
--- a/src/aki_prj23_transparenzregister/utils/networkx/networkx_data.py
+++ b/src/aki_prj23_transparenzregister/utils/networkx/networkx_data.py
@@ -283,6 +283,52 @@ def find_company_relations(
     return pd.DataFrame(), company_relations  # company_relations
 
 
+def find_person_relations(
+    selected_person_id: int,
+) -> pd.DataFrame:
+    """Finds all Relations for the given Person id.
+
+    Args:
+        selected_person_id: Id of the Person which Relations should be returned.
+
+    Returns:
+        DataFrame
+    """
+    session = SessionHandler.session
+    assert session  # noqa: S101
+    relations_person_data = (
+        session.query(
+            entities.Company.id.label("id_company"),
+            entities.Company.name.label("name_company"),
+            entities.PersonRelation.relation.label("relation_type"),
+            entities.Person.id.label("id_person"),
+            entities.Person.lastname.label("lastname"),
+            entities.Person.firstname.label("firstname"),
+            entities.Person.date_of_birth.label("date_of_birth"),
+        )
+        .join(
+            entities.PersonRelation,
+            entities.PersonRelation.company_id == entities.Company.id,
+        )
+        .join(
+            entities.Person,
+            entities.PersonRelation.person_id == entities.Person.id,
+        )
+        .filter(entities.Person.id == selected_person_id)
+        .all()
+    )
+    person_relations = pd.DataFrame(relations_person_data)  # type: ignore
+
+    person_relations["id_company"] = person_relations["id_company"].apply(
+        lambda x: f"c_{x}"
+    )
+    person_relations["id_person"] = person_relations["id_person"].apply(
+        lambda x: f"p_{x}"
+    )
+
+    return person_relations
+
+
 def create_edge_and_node_list_for_company(
     company_relations: pd.DataFrame,
 ) -> tuple[dict, list]:
@@ -347,6 +393,18 @@ def get_all_metrics_from_id(company_id: int) -> pd.Series:
     return filtered_metrics.iloc[0]
 
 
+def filter_sets(sets: list[set]) -> set:
+    """Filters the list of sets given to only contain unique entries.
+
+    Args:
+        sets (list[set]): List of sets to be filtered.
+
+    Returns:
+        list[set]: List of sets with only unique entries.
+    """
+    return set.union(*sets)
+
+
 @lru_cache
 def get_relations_number_from_id(id: str) -> tuple[int, int, int]:
     """Returns all Relation in 1, 2 and 3 lvl of one Node.
@@ -365,20 +423,80 @@ def get_relations_number_from_id(id: str) -> tuple[int, int, int]:
     nodes_tmp, edges_tmp = create_edge_and_node_list(person_df, company_df)
     graph = initialize_network_without_metrics(nodes=nodes_tmp, edges=edges_tmp)
 
-    neighbors = nx.all_neighbors(graph, id)
+    try:
+        neighbors = nx.all_neighbors(graph, id)
 
-    relations_lv1 = set(neighbors)
-    relations_lv2 = set()
-    relations_lv3 = set()
+        relations_lv1 = set(neighbors)
+        relations_lv2 = set()
+        relations_lv3 = set()
 
-    for node in relations_lv1:
-        relations_lv2 |= set(nx.all_neighbors(graph, node))
+        for node in relations_lv1:
+            relations_lv2 |= set(nx.all_neighbors(graph, node))
 
-    relations_lv2.discard(id)
+        relations_lv2.discard(id)
 
-    for sub_node in relations_lv2:
-        relations_lv3 |= set(nx.all_neighbors(graph, sub_node))
+        for sub_node in relations_lv2:
+            relations_lv3 |= set(nx.all_neighbors(graph, sub_node))
 
-    relations_lv2.difference(relations_lv3)
+        unique_entires = filter_sets([relations_lv1, relations_lv2])
+        relations_lv3 = {key for key in relations_lv3 if key not in unique_entires}
 
-    return len(relations_lv1), len(relations_lv2), len(relations_lv3)
+        return len(relations_lv1), len(relations_lv2), len(relations_lv3)
+    except nx.exception.NetworkXError:
+        return 0, 0, 0
+
+
+@lru_cache
+def get_relations_until_level_3(id: str) -> tuple[dict, list]:
+    """Returns all Relation in 1, 2 and 3 lvl of one Node.
+
+    Args:
+        id: String of the Company or Person Id.
+
+    Returns:
+       tuple[dict, list]: nodes, edges
+    """
+    # Get Data
+    person_df = get_all_person_relations()
+    company_df = get_all_company_relations()
+
+    # Create Edge and Node List from data
+    nodes_tmp, edges_tmp = create_edge_and_node_list(person_df, company_df)
+    graph = initialize_network_without_metrics(nodes=nodes_tmp, edges=edges_tmp)
+
+    try:
+        neighbors = nx.all_neighbors(graph, id)
+
+        relations_lv1 = set(neighbors)
+        relations_lv2 = set()
+        relations_lv3 = set()
+
+        for node in relations_lv1:
+            relations_lv2 |= set(nx.all_neighbors(graph, node))
+
+        relations_lv2.discard(id)
+
+        for sub_node in relations_lv2:
+            relations_lv3 |= set(nx.all_neighbors(graph, sub_node))
+
+        unique_entires = filter_sets([relations_lv1, relations_lv2])
+        relations_lv3 = {key for key in relations_lv3 if key not in unique_entires}
+
+        nodes = {
+            key: value
+            for key, value in nodes_tmp.items()
+            if (
+                key in relations_lv1
+                or key in relations_lv2
+                or key in relations_lv3
+                or key == id
+            )
+        }
+        edges = [
+            edge
+            for edge in edges_tmp
+            if (edge["from"] in nodes and edge["to"] in nodes)
+        ]
+        return nodes, edges
+    except nx.exception.NetworkXError:
+        return {}, []