Update app.py

app.py

@@ -1451,128 +1451,279 @@ else:
         </div>
         """, unsafe_allow_html=True)
 
-        # ===============================================================
-        # PLOT FUNCTION — UPDATED: color for slope=0 is now #FFD700
-        # ===============================================================
-        def plot_chart(data, title):
-            if data.empty:
-                fig = go.Figure()
-                fig.add_annotation(
-                    text="No Data",
-                    x=0.5, y=0.5,
-                    showarrow=False,
-                    font_size=16
-                )
-                fig.update_layout(height=350, title=dict(text=title, x=0.5))
-                return fig
-
-            data_sorted = data.sort_values('weekly_avg', ascending=False)
-
-            def get_color(slope):
-                if slope == 0:
-                    return "#FFD700"  # ✅ Kuning untuk One Time Event
-                elif slope > 0:
-                    if slope < 0.5:
-                        return "#ffcdd2"
-                    elif slope < 1.0:
-                        return "#ef9a9a"
-                    elif slope < 1.5:
-                        return "#e57373"
-                    else:
-                        return "#d32f2f"
-                else:  # slope < 0
-                    if slope > -0.5:
-                        return "#c8e6c9"
-                    elif slope > -1.0:
-                        return "#a5d6a7"
-                    elif slope > -1.5:
-                        return "#81c784"
-                    else:
-                        return "#388e3c"
-
-            colors = [get_color(s) for s in data_sorted["slope"]]
-
-            bar_trace = go.Bar(
-                x=data_sorted[col_operator].astype(str),
-                y=data_sorted["weekly_avg"],
-                marker=dict(
-                    color=colors,
-                    line=dict(width=2, color="rgba(0,0,0,0.2)")
-                ),
-                text=[f"{v:.1f}" for v in data_sorted["weekly_avg"]],
-                textposition="outside",
-                hovertemplate=(
-                    "<b>%{x}</b><br>" +
-                    "Weekly Avg: %{y:.2f}<br>" +
-                    "Trend Slope: %{customdata[0]:+.3f}<br>" +
-                    "Total Events: %{customdata[1]}<br>" +
-                    "Weeks Active: %{customdata[2]}<br>" +
-                    "<extra></extra>"
-                ),
-                customdata=np.stack([data_sorted["slope"], data_sorted["total_events"], data_sorted["n_weeks"]], axis=-1)
+# ===============================================================
+# PLOT FUNCTION — UPDATED: color for slope=0 is now #FFD700
+# ===============================================================
+def plot_chart(data, title):
+    if data.empty:
+        fig = go.Figure()
+        fig.add_annotation(
+            text="No Data",
+            x=0.5, y=0.5,
+            showarrow=False,
+            font_size=16
+        )
+        fig.update_layout(height=350, title=dict(text=title, x=0.5))
+        return fig
+
+    data_sorted = data.sort_values('weekly_avg', ascending=False)
+
+    def get_color(slope):
+        if slope == 0:
+            return "#FFD700"  # ✅ Kuning untuk One Time Event
+        elif slope > 0:
+            if slope < 0.5:
+                return "#ffcdd2"
+            elif slope < 1.0:
+                return "#ef9a9a"
+            elif slope < 1.5:
+                return "#e57373"
+            else:
+                return "#d32f2f"
+        else:  # slope < 0
+            if slope > -0.5:
+                return "#c8e6c9"
+            elif slope > -1.0:
+                return "#a5d6a7"
+            elif slope > -1.5:
+                return "#81c784"
+            else:
+                return "#388e3c"
+
+    colors = [get_color(s) for s in data_sorted["slope"]]
+
+    bar_trace = go.Bar(
+        x=data_sorted[col_operator].astype(str),
+        y=data_sorted["weekly_avg"],
+        marker=dict(
+            color=colors,
+            line=dict(width=2, color="rgba(0,0,0,0.2)")
+        ),
+        text=[f"{v:.1f}" for v in data_sorted["weekly_avg"]],
+        textposition="outside",
+        hovertemplate=(
+            "<b>%{x}</b><br>" +
+            "Weekly Avg: %{y:.2f}<br>" +
+            "Trend Slope: %{customdata[0]:+.3f}<br>" +
+            "Total Events: %{customdata[1]}<br>" +
+            "Weeks Active: %{customdata[2]}<br>" +
+            "<extra></extra>"
+        ),
+        customdata=np.stack([data_sorted["slope"], data_sorted["total_events"], data_sorted["n_weeks"]], axis=-1)
+    )
+
+    fig = go.Figure(bar_trace)
+    fig.update_layout(
+        title=dict(text=f"<b>{title}</b>", x=0.5),
+        height=450,
+        margin=dict(l=50, r=20, t=60, b=120),
+        xaxis_title="<b>Operator Name</b>",
+        yaxis_title="<b>Weekly Avg Events</b>",
+        font=dict(family="Segoe UI", size=12),
+        bargap=0.3,
+        plot_bgcolor="rgba(0,0,0,0)",
+        paper_bgcolor="rgba(0,0,0,0)",
+        xaxis=dict(tickangle=45)
+    )
+    return fig
+
+
+# ==========================
+# INSIGHT DISPLAY SECTION
+# ==========================
+col_insight1, col_insight2 = st.columns(2)
+
+with col_insight1:
+    if not top_ob.empty:
+        st.markdown("### OB HAULER Hazard Analysis")
+        ob_worsening = len(top_ob[top_ob['slope'] > 0])
+        ob_improving = len(top_ob[top_ob['slope'] < 0])
+        ob_one_time = len(top_ob[top_ob['slope'] == 0])
+        ob_avg_risk = top_ob['weekly_avg'].mean()
+        ob_max_risk = top_ob['weekly_avg'].max()
+
+        # Always show 3 insights
+        ob_insights = [
+            f"{ob_worsening} out of 10 top hazard operators are showing <span class='trend-up'>worsening</span> trends.",
+            f"{ob_one_time} operators are classified as <b>One Time Event</b> (single-week activity).",
+            f"Average hazard: {ob_avg_risk:.2f} events/week (max: {ob_max_risk:.2f})."
+        ]
+        for insight in ob_insights:
+            st.markdown(
+                f"""
+                <div class="ai-insight-box">
+                    <div class="ai-insight-title">Hazard Summary</div>
+                    <p>{insight}</p>
+                </div>
+                """,
+                unsafe_allow_html=True
             )
+    else:
+        st.info("No OB HAULER data for analysis.")
 
-            fig = go.Figure(bar_trace)
-            fig.update_layout(
-                title=dict(text=f"<b>{title}</b>", x=0.5),
-                height=450,
-                margin=dict(l=50, r=20, t=60, b=120),
-                xaxis_title="<b>Operator Name</b>",
-                yaxis_title="<b>Weekly Avg Events</b>",
-                font=dict(family="Segoe UI", size=12),
-                bargap=0.3,
-                plot_bgcolor="rgba(0,0,0,0)",
-                paper_bgcolor="rgba(0,0,0,0)",
-                xaxis=dict(tickangle=45)
+with col_insight2:
+    if not top_coal.empty:
+        st.markdown("### HAULING COAL Hazard Analysis")
+        coal_worsening = len(top_coal[top_coal['slope'] > 0])
+        coal_improving = len(top_coal[top_coal['slope'] < 0])
+        coal_one_time = len(top_coal[top_coal['slope'] == 0])
+        coal_avg_risk = top_coal['weekly_avg'].mean()
+        coal_max_risk = top_coal['weekly_avg'].max()
+
+        coal_insights = [
+            f"{coal_worsening} out of 10 top hazard operators are showing <span class='trend-up'>worsening</span> trends.",
+            f"{coal_one_time} operators are classified as <b>One Time Event</b> (single-week activity).",
+            f"Average hazard: {coal_avg_risk:.2f} events/week (max: {coal_max_risk:.2f})."
+        ]
+        for insight in coal_insights:
+            st.markdown(
+                f"""
+                <div class="ai-insight-box">
+                    <div class="ai-insight-title">Hazard Summary</div>
+                    <p>{insight}</p>
+                </div>
+                """,
+                unsafe_allow_html=True
             )
-            return fig
-            col_insight1, col_insight2 = st.columns(2)
-            with col_insight1:
-                if not top_ob.empty:
-                    st.markdown("### OB HAULER Hazard Analysis")
-                    ob_worsening = len(top_ob[top_ob['slope'] > 0])
-                    ob_improving = len(top_ob[top_ob['slope'] < 0])
-                    ob_one_time = len(top_ob[top_ob['slope'] == 0])
-                    ob_avg_risk = top_ob['weekly_avg'].mean()
-                    ob_max_risk = top_ob['weekly_avg'].max()
-
-        # Buat list 3 poin yang selalu ada, tanpa kondisional untuk jumlah poin
-            ob_insights = [
+    else:
+        st.info("No HAULING COAL data for analysis.")
+        # ===============================================================
+        # RECOMMENDATIONS# ===============================================================
+# PLOT FUNCTION — UPDATED: color for slope=0 is now #FFD700
+# ===============================================================
+def plot_chart(data, title):
+    if data.empty:
+        fig = go.Figure()
+        fig.add_annotation(
+            text="No Data",
+            x=0.5, y=0.5,
+            showarrow=False,
+            font_size=16
+        )
+        fig.update_layout(height=350, title=dict(text=title, x=0.5))
+        return fig
+
+    data_sorted = data.sort_values('weekly_avg', ascending=False)
+
+    def get_color(slope):
+        if slope == 0:
+            return "#FFD700"  # ✅ Kuning untuk One Time Event
+        elif slope > 0:
+            if slope < 0.5:
+                return "#ffcdd2"
+            elif slope < 1.0:
+                return "#ef9a9a"
+            elif slope < 1.5:
+                return "#e57373"
+            else:
+                return "#d32f2f"
+        else:  # slope < 0
+            if slope > -0.5:
+                return "#c8e6c9"
+            elif slope > -1.0:
+                return "#a5d6a7"
+            elif slope > -1.5:
+                return "#81c784"
+            else:
+                return "#388e3c"
+
+    colors = [get_color(s) for s in data_sorted["slope"]]
+
+    bar_trace = go.Bar(
+        x=data_sorted[col_operator].astype(str),
+        y=data_sorted["weekly_avg"],
+        marker=dict(
+            color=colors,
+            line=dict(width=2, color="rgba(0,0,0,0.2)")
+        ),
+        text=[f"{v:.1f}" for v in data_sorted["weekly_avg"]],
+        textposition="outside",
+        hovertemplate=(
+            "<b>%{x}</b><br>" +
+            "Weekly Avg: %{y:.2f}<br>" +
+            "Trend Slope: %{customdata[0]:+.3f}<br>" +
+            "Total Events: %{customdata[1]}<br>" +
+            "Weeks Active: %{customdata[2]}<br>" +
+            "<extra></extra>"
+        ),
+        customdata=np.stack([data_sorted["slope"], data_sorted["total_events"], data_sorted["n_weeks"]], axis=-1)
+    )
+
+    fig = go.Figure(bar_trace)
+    fig.update_layout(
+        title=dict(text=f"<b>{title}</b>", x=0.5),
+        height=450,
+        margin=dict(l=50, r=20, t=60, b=120),
+        xaxis_title="<b>Operator Name</b>",
+        yaxis_title="<b>Weekly Avg Events</b>",
+        font=dict(family="Segoe UI", size=12),
+        bargap=0.3,
+        plot_bgcolor="rgba(0,0,0,0)",
+        paper_bgcolor="rgba(0,0,0,0)",
+        xaxis=dict(tickangle=45)
+    )
+    return fig
+
+
+# ==========================
+# INSIGHT DISPLAY SECTION
+# ==========================
+col_insight1, col_insight2 = st.columns(2)
+
+with col_insight1:
+    if not top_ob.empty:
+        st.markdown("### OB HAULER Hazard Analysis")
+        ob_worsening = len(top_ob[top_ob['slope'] > 0])
+        ob_improving = len(top_ob[top_ob['slope'] < 0])
+        ob_one_time = len(top_ob[top_ob['slope'] == 0])
+        ob_avg_risk = top_ob['weekly_avg'].mean()
+        ob_max_risk = top_ob['weekly_avg'].max()
+
+        # Always show 3 insights
+        ob_insights = [
             f"{ob_worsening} out of 10 top hazard operators are showing <span class='trend-up'>worsening</span> trends.",
             f"{ob_one_time} operators are classified as <b>One Time Event</b> (single-week activity).",
             f"Average hazard: {ob_avg_risk:.2f} events/week (max: {ob_max_risk:.2f})."
         ]
-            for insight in ob_insights:
-            st.markdown(f"""
-            <div class="ai-insight-box">
-                <div class="ai-insight-title">Hazard Summary</div>
-                <p>{insight}</p>
-            </div>
-            """, unsafe_allow_html=True)
+        for insight in ob_insights:
+            st.markdown(
+                f"""
+                <div class="ai-insight-box">
+                    <div class="ai-insight-title">Hazard Summary</div>
+                    <p>{insight}</p>
+                </div>
+                """,
+                unsafe_allow_html=True
+            )
     else:
         st.info("No OB HAULER data for analysis.")
-        with col_insight2:
-            if not top_coal.empty:
-                st.markdown("### HAULING COAL Hazard Analysis")
-                coal_worsening = len(top_coal[top_coal['slope'] > 0])
-                coal_improving = len(top_coal[top_coal['slope'] < 0])
-                coal_one_time = len(top_coal[top_coal['slope'] == 0])
-                coal_avg_risk = top_coal['weekly_avg'].mean()
-                coal_max_risk = top_coal['weekly_avg'].max()
-                coal_insights = [f"{coal_worsening} out of 10 top hazard operators are showing <span class='trend-up'>worsening</span> trends.",
-                                 f"{coal_one_time} operators are classified as <b>One Time Event</b> (single-week activity).",
-                                 f"Average hazard: {coal_avg_risk:.2f} events/week (max: {coal_max_risk:.2f})."]
-                for insight in coal_insights:
-                    st.markdown(f"""
-                    <div class="ai-insight-box">
-                <div class="ai-insight-title">Hazard Summary</div>
-                <p>{insight}</p>
-            </div>
-            """, unsafe_allow_html=True)
-                    else:
-                    st.info("No HAULING COAL data for analysis.")
-        # ===============================================================
-        # RECOMMENDATIONS
+
+with col_insight2:
+    if not top_coal.empty:
+        st.markdown("### HAULING COAL Hazard Analysis")
+        coal_worsening = len(top_coal[top_coal['slope'] > 0])
+        coal_improving = len(top_coal[top_coal['slope'] < 0])
+        coal_one_time = len(top_coal[top_coal['slope'] == 0])
+        coal_avg_risk = top_coal['weekly_avg'].mean()
+        coal_max_risk = top_coal['weekly_avg'].max()
+
+        coal_insights = [
+            f"{coal_worsening} out of 10 top hazard operators are showing <span class='trend-up'>worsening</span> trends.",
+            f"{coal_one_time} operators are classified as <b>One Time Event</b> (single-week activity).",
+            f"Average hazard: {coal_avg_risk:.2f} events/week (max: {coal_max_risk:.2f})."
+        ]
+        for insight in coal_insights:
+            st.markdown(
+                f"""
+                <div class="ai-insight-box">
+                    <div class="ai-insight-title">Hazard Summary</div>
+                    <p>{insight}</p>
+                </div>
+                """,
+                unsafe_allow_html=True
+            )
+    else:
+        st.info("No HAULING COAL data for analysis.")
         # ===============================================================
         col_rec1, col_rec2 = st.columns(2)