Update app.py

app.py

@@ -1527,203 +1527,76 @@ def plot_chart(data, title):
     )
     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.")
-
-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# ===============================================================
-# 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
+        # CHARTS
+        # ===============================================================
+        col1, col2 = st.columns(2)
+        with col1:
+            st.plotly_chart(plot_chart(top_ob, "OB HAULER Operators (Hazard Gradient)"), use_container_width=True)
+        with col2:
+            st.plotly_chart(plot_chart(top_coal, "HAULING COAL Operators (Hazard Gradient)"), use_container_width=True)
 
-    data_sorted = data.sort_values('weekly_avg', ascending=False)
+        # ===============================================================
+        # AI INSIGHTS — tetap dalam bahasa Inggris, tanpa emoticon
+        # ===============================================================
+        col_insight1, col_insight2 = st.columns(2)
 
-    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"
+        with col_insight1:
+            if not top_ob.empty:
+                st.markdown("### OB HAULER 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()
+                ob_insights = []
+                if ob_worsening > ob_improving:
+                    ob_insights.append(f"{ob_worsening} out of 10 top risk operators are showing <span class='trend-up'>worsening</span> trends.")
+                else:
+                    ob_insights.append(f"{ob_improving} out of 10 top risk operators are showing <span class='trend-down'>improvement</span>.")
+                if ob_one_time > 0:
+                    ob_insights.append(f"{ob_one_time} operators are classified as <b>One Time Event</b> (single-week activity).")
+                ob_insights.append(f"Average risk: {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">Risk Summary</div>
+                        <p>{insight}</p>
+                    </div>
+                    """, unsafe_allow_html=True)
             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
+                st.info("No OB HAULER data for analysis.")
 
+        with col_insight2:
+            if not top_coal.empty:
+                st.markdown("### HAULING COAL 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 = []
+                if coal_worsening > coal_improving:
+                    coal_insights.append(f"{coal_worsening} out of 10 top risk operators are showing <span class='trend-up'>worsening</span> trends.")
+                else:
+                    coal_insights.append(f"{coal_improving} out of 10 top risk operators are showing <span class='trend-down'>improvement</span>.")
+                if coal_one_time > 0:
+                    coal_insights.append(f"{coal_one_time} operators are classified as <b>One Time Event</b> (single-week activity).")
+                coal_insights.append(f"Average risk: {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">Risk Summary</div>
+                        <p>{insight}</p>
+                    </div>
+                    """, unsafe_allow_html=True)
+            else:
+                st.info("No HAULING COAL data for analysis.")
 
-# ==========================
-# 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.")
-
-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
         # ===============================================================
         col_rec1, col_rec2 = st.columns(2)
 
@@ -1801,7 +1674,6 @@ with col_insight2:
         st.exception(e)  # optionally show full traceback during dev
 
 
-
 # =================== OBJECTIVE 6: Automated Insights & AI Recommendations =====================
 st.subheader("OBJECTIVE 6: Instant Insights & Recommendations")