dummy_funcs.py

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