Update app.py

app.py

@@ -1,102 +1,69 @@
+import pandas as pd
 import networkx as nx
 import matplotlib.pyplot as plt
-import gradio as gr
 from io import BytesIO
 from PIL import Image
+import gradio as gr
 
-# Define investors and their companies
-investors = {
-    "Accel": ["Meta", "Dropbox", "Spotify", "Adroll", "PackLink", "Zoom", "Slack"],
-    "Andreessen Horowitz": [
-        "Airbnb", "Lyft", "Pinterest", "Coinbase", "Robinhood", "Slack"
-    ],
-    "Google Ventures": ["Uber", "LendingClub"],
-    "Greylock": ["Workday", "Palo Alto Networks"],
-    "Lightspeed Venture Partners": ["Snap", "Grubhub", "AppDynamics"],
-    "Benchmark": ["Snap", "Uber", "WeWork"],
-    "Norwest Venture Partners": ["LendingClub", "Opendoor"],
-    "Emergence Capital Partners": ["Zoom", "Box", "Salesforce"],
-    "Trinity Ventures": ["New Relic", "Care.com", "TubeMogul"],
-    "Citi Ventures": ["Square", "Nutanix"],
-    "Sequoia": ["Alphabet (Google)", "NVIDIA", "Dropbox", "Airbnb", "Meta"],
-    "Y Combinator": ["Dropbox", "Airbnb", "Coinbase", "DoorDash", "Reddit"]
-}
-
-# Example market capitalization values (in billions USD)
-market_cap = {
-    "Meta": 900,
-    "Dropbox": 10,
-    "Spotify": 30,
-    "Zoom": 20,
-    "Slack": 27,
-    "Airbnb": 100,
-    "Lyft": 4,
-    "Pinterest": 14,
-    "Coinbase": 70,
-    "Robinhood": 10,
-    "Uber": 60,
-    "LendingClub": 1,
-    "Snap": 18,
-    "Grubhub": 6,
-    "AppDynamics": 1,
-    "WeWork": 0.9,
-    "Opendoor": 3,
-    "Box": 4,
-    "Salesforce": 200,
-    "Square": 90,
-    "Nutanix": 10,
-    "Alphabet (Google)": 1500,
-    "NVIDIA": 1200
-}
-
-# Assign default size for missing companies
-default_size = 5
-
-# Define a color map for the investors
-investor_colors = {
-    "Accel": "#1f77b4",
-    "Andreessen Horowitz": "#ff7f0e",
-    "Google Ventures": "#2ca02c",
-    "Greylock": "#d62728",
-    "Lightspeed Venture Partners": "#9467bd",
-    "Benchmark": "#8c564b",
-    "Norwest Venture Partners": "#e377c2",
-    "Emergence Capital Partners": "#7f7f7f",
-    "Trinity Ventures": "#bcbd22",
-    "Citi Ventures": "#17becf",
-    "Sequoia": "#1b9e77",
-    "Y Combinator": "#d95f02"
-}
-
+# Load and preprocess the dataset
+file_path = "cbinsights_data.csv"  # Replace with your file path
+data = pd.read_csv(file_path)
+
+# Rename columns based on the first row and drop the header row
+data.columns = data.iloc[0]
+data = data[1:]
+data.columns = ["Company", "Valuation_Billions", "Date_Joined", "Country", "City", "Industry", "Select_Investors"]
+
+# Clean and prepare data
+data["Valuation_Billions"] = data["Valuation_Billions"].str.replace('$', '').str.split('.').str[0]
+data["Valuation_Billions"] = pd.to_numeric(data["Valuation_Billions"], errors='coerce')
+data = data.applymap(lambda x: x.strip() if isinstance(x, str) else x)
+
+# Parse the "Select_Investors" column to map investors to companies
+investor_company_mapping = {}
+for _, row in data.iterrows():
+    company = row["Company"]
+    investors = row["Select_Investors"]
+    if pd.notnull(investors):
+        for investor in investors.split(","):
+            investor = investor.strip()
+            if investor not in investor_company_mapping:
+                investor_company_mapping[investor] = []
+            investor_company_mapping[investor].append(company)
+
+# Gradio app function
 def generate_graph(selected_investors):
     if not selected_investors:
-        selected_investors = list(investors.keys())
-
+        selected_investors = list(investor_company_mapping.keys())
+    
     G = nx.Graph()
 
     # Add edges and nodes based on selected investors
     for investor in selected_investors:
-        companies = investors[investor]
+        companies = investor_company_mapping.get(investor, [])
         for company in companies:
-            G.add_edge(investor, company, color=investor_colors[investor])
+            G.add_edge(investor, company)
 
-    # Get edge colors
-    edge_colors = [G[u][v]['color'] for u, v in G.edges]
+    # Node sizes based on valuation
+    node_sizes = []
+    for node in G.nodes:
+        if node in investor_company_mapping:  # Fixed size for investors
+            node_sizes.append(2000)
+        else:  # Company size based on valuation
+            valuation = data.loc[data["Company"] == node, "Valuation_Billions"].values
+            node_sizes.append(valuation[0] * 100 if len(valuation) > 0 else 100)
 
-    # Set node colors and sizes
+    # Node colors
     node_colors = []
-    node_sizes = []
     for node in G.nodes:
-        if node in investor_colors:
-            node_colors.append(investor_colors[node])
-            node_sizes.append(2000)  # Fixed size for investors
+        if node in investor_company_mapping:
+            node_colors.append("#FF5733")  # Distinct color for investors
         else:
-            node_colors.append("#F0E68C")  # Khaki for companies
-            node_sizes.append(market_cap.get(node, default_size) * 100)  # Scale up sizes
+            node_colors.append("#33FF57")  # Distinct color for companies
 
-    # Create plot
+    # Create the graph plot
     plt.figure(figsize=(18, 18))
-    pos = nx.spring_layout(G, k=0.2, seed=42)  # Fixed seed for consistency
+    pos = nx.spring_layout(G, k=0.2, seed=42)  # Fixed seed for consistent layout
     nx.draw(
         G, pos,
         with_labels=True,
@@ -104,13 +71,13 @@ def generate_graph(selected_investors):
         node_color=node_colors,
         font_size=10,
         font_weight="bold",
-        edge_color=edge_colors,
-        width=2
+        edge_color="gray",
+        width=1.5
     )
-    plt.title("Venture Funded Companies as a Densely Connected Subgraph", fontsize=20)
+    plt.title("Venture Funded Companies Visualization", fontsize=20)
     plt.axis('off')
 
-    # Save plot to a BytesIO object
+    # Save plot to BytesIO object
     buf = BytesIO()
     plt.savefig(buf, format="png", bbox_inches="tight")
     plt.close()
@@ -120,10 +87,9 @@ def generate_graph(selected_investors):
     image = Image.open(buf)
     return image
 
-# Define Gradio interface
+# Gradio Interface
 def main():
-    # Create a sorted list of investors for better UX
-    investor_list = sorted(investors.keys())
+    investor_list = sorted(investor_company_mapping.keys())
 
     iface = gr.Interface(
         fn=generate_graph,
@@ -134,7 +100,11 @@ def main():
         ),
         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 market capitalization.",
+        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."
+        ),
         flagging_mode="never"
     )