Update app.py

app.py

@@ -108,6 +108,60 @@ def ask_gpt4o_for_visualization(query, df, llm):
         st.error("⚠️ GPT-4o failed to generate a valid suggestion.")
         return None
 
+def add_stats_to_figure(fig, df, y_axis, chart_type):
+    # Calculate statistics
+    min_val = df[y_axis].min()
+    max_val = df[y_axis].max()
+    avg_val = df[y_axis].mean()
+    median_val = df[y_axis].median()
+    std_dev_val = df[y_axis].std()
+
+    # Stats summary text
+    stats_text = (
+        f"📊 **Statistics**\n\n"
+        f"- **Min:** ${min_val:,.2f}\n"
+        f"- **Max:** ${max_val:,.2f}\n"
+        f"- **Average:** ${avg_val:,.2f}\n"
+        f"- **Median:** ${median_val:,.2f}\n"
+        f"- **Std Dev:** ${std_dev_val:,.2f}"
+    )
+
+    # Charts suitable for stats annotations
+    if chart_type in ["bar", "line", "scatter"]:
+        # Add annotation box
+        fig.add_annotation(
+            text=stats_text,
+            xref="paper", yref="paper",
+            x=1.05, y=1,
+            showarrow=False,
+            align="left",
+            font=dict(size=12, color="black"),
+            bordercolor="black",
+            borderwidth=1,
+            bgcolor="rgba(255, 255, 255, 0.8)"
+        )
+
+        # Add horizontal lines for min, median, avg, max
+        fig.add_hline(y=min_val, line_dash="dot", line_color="red", annotation_text="Min", annotation_position="bottom right")
+        fig.add_hline(y=median_val, line_dash="dash", line_color="orange", annotation_text="Median", annotation_position="top right")
+        fig.add_hline(y=avg_val, line_dash="dashdot", line_color="green", annotation_text="Avg", annotation_position="top right")
+        fig.add_hline(y=max_val, line_dash="dot", line_color="blue", annotation_text="Max", annotation_position="top right")
+
+    elif chart_type == "box":
+        # Box plots already show distribution (no extra stats needed)
+        pass
+
+    elif chart_type == "pie":
+        # Pie charts don't need statistical overlays
+        st.info("📊 Pie charts focus on proportions. No additional stats displayed.")
+    
+    else:
+        st.warning(f"⚠️ No stats added for unsupported chart type: {chart_type}")
+
+    return fig
+
+
+
 # Dynamically generate Plotly visualizations based on GPT-4o suggestions
 def generate_visualization(suggestion, df):
     chart_type = suggestion.get("chart_type", "bar").lower()
@@ -162,59 +216,6 @@ def generate_visualization(suggestion, df):
         return None
 
 
-def add_stats_to_figure(fig, df, y_axis, chart_type):
-    # Calculate statistics
-    min_val = df[y_axis].min()
-    max_val = df[y_axis].max()
-    avg_val = df[y_axis].mean()
-    median_val = df[y_axis].median()
-    std_dev_val = df[y_axis].std()
-
-    # Stats summary text
-    stats_text = (
-        f"📊 **Statistics**\n\n"
-        f"- **Min:** ${min_val:,.2f}\n"
-        f"- **Max:** ${max_val:,.2f}\n"
-        f"- **Average:** ${avg_val:,.2f}\n"
-        f"- **Median:** ${median_val:,.2f}\n"
-        f"- **Std Dev:** ${std_dev_val:,.2f}"
-    )
-
-    # Charts suitable for stats annotations
-    if chart_type in ["bar", "line", "scatter"]:
-        # Add annotation box
-        fig.add_annotation(
-            text=stats_text,
-            xref="paper", yref="paper",
-            x=1.05, y=1,
-            showarrow=False,
-            align="left",
-            font=dict(size=12, color="black"),
-            bordercolor="black",
-            borderwidth=1,
-            bgcolor="rgba(255, 255, 255, 0.8)"
-        )
-
-        # Add horizontal lines for min, median, avg, max
-        fig.add_hline(y=min_val, line_dash="dot", line_color="red", annotation_text="Min", annotation_position="bottom right")
-        fig.add_hline(y=median_val, line_dash="dash", line_color="orange", annotation_text="Median", annotation_position="top right")
-        fig.add_hline(y=avg_val, line_dash="dashdot", line_color="green", annotation_text="Avg", annotation_position="top right")
-        fig.add_hline(y=max_val, line_dash="dot", line_color="blue", annotation_text="Max", annotation_position="top right")
-
-    elif chart_type == "box":
-        # Box plots already show distribution (no extra stats needed)
-        pass
-
-    elif chart_type == "pie":
-        # Pie charts don't need statistical overlays
-        st.info("📊 Pie charts focus on proportions. No additional stats displayed.")
-    
-    else:
-        st.warning(f"⚠️ No stats added for unsupported chart type: {chart_type}")
-
-    return fig
-
-
 # Function to create TXT file
 def create_text_report_with_viz_temp(report, conclusion, visualizations):
     content = f"### Analysis Report\n\n{report}\n\n### Visualizations\n"