Update app.py

app.py

@@ -32,31 +32,43 @@ for _, row in data.iterrows():
             investor_company_mapping[investor].append(company)
 
 # Gradio app function
-def generate_graph(selected_investors):
-    if not selected_investors:
-        selected_investors = list(investor_company_mapping.keys())
-    
-    G = nx.Graph()
+def generate_graph(selected_investors, selected_country, selected_industry):
+    filtered_data = data
+
+    # Apply country filter
+    if selected_country != "All":
+        filtered_data = filtered_data[filtered_data["Country"] == selected_country]
+
+    # Apply industry filter
+    if selected_industry != "All":
+        filtered_data = filtered_data[filtered_data["Industry"] == selected_industry]
 
-    # Add edges and nodes based on selected investors
-    for investor in selected_investors:
-        companies = investor_company_mapping.get(investor, [])
+    # Filter the investor-to-company mapping
+    filtered_mapping = {}
+    for investor, companies in investor_company_mapping.items():
+        filtered_companies = [c for c in companies if c in filtered_data["Company"].values]
+        if filtered_companies:
+            filtered_mapping[investor] = filtered_companies
+
+    # Use the filtered mapping to build the graph
+    G = nx.Graph()
+    for investor, companies in filtered_mapping.items():
         for company in companies:
             G.add_edge(investor, company)
 
     # Node sizes based on valuation
     node_sizes = []
     for node in G.nodes:
-        if node in investor_company_mapping:  # Fixed size for investors
+        if node in filtered_mapping:  # Fixed size for investors
             node_sizes.append(2000)
         else:  # Company size based on valuation
-            valuation = data.loc[data["Company"] == node, "Valuation_Billions"].values
+            valuation = filtered_data.loc[filtered_data["Company"] == node, "Valuation_Billions"].values
             node_sizes.append(valuation[0] * 100 if len(valuation) > 0 else 100)
 
     # Node colors
     node_colors = []
     for node in G.nodes:
-        if node in investor_company_mapping:
+        if node in filtered_mapping:
             node_colors.append("#FF5733")  # Distinct color for investors
         else:
             node_colors.append("#33FF57")  # Distinct color for companies
@@ -90,20 +102,34 @@ def generate_graph(selected_investors):
 # Gradio Interface
 def main():
     investor_list = sorted(investor_company_mapping.keys())
+    country_list = ["All"] + sorted(data["Country"].dropna().unique())
+    industry_list = ["All"] + sorted(data["Industry"].dropna().unique())
 
     iface = gr.Interface(
         fn=generate_graph,
-        inputs=gr.CheckboxGroup(
-            choices=investor_list,
-            label="Select Investors",
-            value=investor_list  # Default to all selected
-        ),
+        inputs=[
+            gr.CheckboxGroup(
+                choices=investor_list,
+                label="Select Investors",
+                value=investor_list  # Default to all selected
+            ),
+            gr.Dropdown(
+                choices=country_list,
+                label="Filter by Country",
+                value="All"  # Default to no filter
+            ),
+            gr.Dropdown(
+                choices=industry_list,
+                label="Filter by Industry",
+                value="All"  # Default to no filter
+            )
+        ],
         outputs=gr.Image(type="pil", label="Venture Network Graph"),
         title="Venture Networks Visualization",
         description=(
-            "Select investors to visualize their investments in various companies. "
-            "The graph shows connections between investors and the companies they've invested in. "
-            "Node sizes represent company valuations."
+            "Select investors and apply optional filters by country and industry "
+            "to visualize their investments. The graph shows connections between "
+            "investors and the companies they've invested in. Node sizes represent company valuations."
         ),
         flagging_mode="never"
     )