Create esg_statistics.py

esg_statistics.py

@@ -0,0 +1,45 @@
+import plotly.graph_objects as go
+
+
+def compute_esg_keyword_distribution(text):
+    text = text.lower()
+
+    environmental_keywords = ["emission", "carbon", "climate", "energy", "waste"]
+    social_keywords = ["diversity", "employee", "community", "health", "safety"]
+    governance_keywords = ["board", "compliance", "audit", "ethics", "policy"]
+
+    e_count = sum(text.count(word) for word in environmental_keywords)
+    s_count = sum(text.count(word) for word in social_keywords)
+    g_count = sum(text.count(word) for word in governance_keywords)
+
+    total = max(e_count + s_count + g_count, 1)
+
+    return {
+        "Environmental": e_count,
+        "Social": s_count,
+        "Governance": g_count,
+        "Total": total
+    }
+
+
+def generate_esg_statistics_chart(text):
+    stats = compute_esg_keyword_distribution(text)
+
+    fig = go.Figure(data=[
+        go.Pie(
+            labels=["Environmental", "Social", "Governance"],
+            values=[
+                stats["Environmental"],
+                stats["Social"],
+                stats["Governance"]
+            ],
+            hole=0.5
+        )
+    ])
+
+    fig.update_layout(
+        title="ESG Keyword Distribution (Donut Chart)",
+        template="plotly_dark"
+    )
+
+    return fig