Update analytics_fetch_and_rendering.py

analytics_fetch_and_rendering.py

@@ -265,6 +265,52 @@ def plot_interaction_metrics(data):
     plt.tight_layout(rect=[0, 0, 1, 0.96])  # Leave space for suptitle
     return fig
 
+from collections import defaultdict
+import matplotlib.pyplot as plt
+
+def compute_eb_content_ratio(posts):
+    if not posts:
+        return []
+
+    monthly_counts = defaultdict(lambda: {"eb_count": 0, "total": 0})
+
+    for post in posts:
+        try:
+            month = post["when"][:7]  # YYYY-MM
+            category = post.get("category", "None")
+            monthly_counts[month]["total"] += 1
+            if category and category.strip() != "None":
+                monthly_counts[month]["eb_count"] += 1
+        except Exception:
+            continue
+
+    results = []
+    for month in sorted(monthly_counts.keys()):
+        data = monthly_counts[month]
+        ratio = (data["eb_count"] / data["total"]) * 100 if data["total"] else 0
+        results.append({"month": month, "eb_ratio": round(ratio, 2)})
+
+    return results
+
+def plot_eb_content_ratio(data):
+    if not data:
+        fig, ax = plt.subplots(figsize=(10, 5))
+        ax.text(0.5, 0.5, 'No EB content data.', ha='center', va='center', transform=ax.transAxes)
+        ax.set_title('EB Content Ratio (%)')
+        ax.set_xticks([]); ax.set_yticks([])
+        return fig
+
+    months = [d["month"] for d in data]
+    ratios = [d["eb_ratio"] for d in data]
+
+    fig, ax = plt.subplots(figsize=(12, 6))
+    ax.plot(months, ratios, label="EB Content Ratio (%)", marker="o", color="#2ca02c")
+    ax.set(title="Monthly EB Content Ratio (%)", xlabel="Month", ylabel="EB Content %")
+    ax.tick_params(axis='x', rotation=45)
+    ax.legend()
+    plt.tight_layout()
+    return fig
+
 
 def fetch_and_render_analytics(client_id, token):
     loading = gr.update(value="<p>Loading follower count...</p>", visible=True)
@@ -279,6 +325,8 @@ def fetch_and_render_analytics(client_id, token):
         posts, org_name, sentiments = fetch_posts_and_stats(client_id, token, count=30)
         engagement_data = compute_monthly_avg_engagement_rate(posts)
         interaction_data = compute_post_interaction_metrics(posts)
+        eb_data = compute_eb_content_ratio(posts)
+
  
 
         count_html = f"""
@@ -289,7 +337,7 @@ def fetch_and_render_analytics(client_id, token):
             <p style='font-size:0.9em; color:#777;'>(As of latest data)</p>
         </div>
         """
-        return gr.update(value=count_html, visible=True), gr.update(value=plot_follower_gains(gains), visible=True), gr.update(value=plot_growth_rate(gains, count), visible=True), gr.update(value=plot_avg_engagement_rate(engagement_data), visible=True), gr.update(value=plot_interaction_metrics(interaction_data), visible=True)
+        return gr.update(value=count_html, visible=True), gr.update(value=plot_follower_gains(gains), visible=True), gr.update(value=plot_growth_rate(gains, count), visible=True), gr.update(value=plot_avg_engagement_rate(engagement_data), visible=True), gr.update(value=plot_interaction_metrics(interaction_data), visible=True), gr.update(value=plot_eb_content_ratio(eb_data)
 
     except Exception as e:
         error = display_error("Analytics load failed.", e).get('value', "<p style='color:red;'>Error loading data.</p>")