Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import plotly.express as px
+
+st.set_page_config(page_title="Fatigue Dashboard", layout="wide")
+
+# Load Data
+df = pd.read_excel("manual fatique.xlsx")
+
+# Normalize timestamp
+timestamp_col = [col for col in df.columns if "GMT" in col or "timestamp" in col.lower()][0]
+df["Timestamp"] = pd.to_datetime(df[timestamp_col])
+
+st.title("⛑️ Fatigue Monitoring Dashboard")
+
+# Sidebar Filters
+shift_filter = st.sidebar.multiselect("Filter Shift", df['Shift'].unique())
+unit_filter = st.sidebar.multiselect("Filter Unit", df['Fleet Number'].unique())
+
+filtered = df.copy()
+if shift_filter:
+    filtered = filtered[filtered['Shift'].isin(shift_filter)]
+if unit_filter:
+    filtered = filtered[filtered['Fleet Number'].isin(unit_filter)]
+
+# KPI Metrics
+col1, col2 = st.columns(2)
+col1.metric("Total Fatigue Alerts", len(filtered))
+col2.metric("Unique Operators", filtered['Operator Name'].nunique())
+
+# Trend per day
+trend = filtered.groupby(filtered["Timestamp"].dt.date).size().reset_index(name="Count")
+fig = px.line(trend, x="Timestamp", y="Count", title="📈 Trend Fatigue Alerts Per Hari")
+st.plotly_chart(fig, use_container_width=True)
+
+# Shift comparison
+fig2 = px.bar(filtered, x="Shift", title="⚠️ Distribusi Alert per Shift", color="Shift")
+st.plotly_chart(fig2, use_container_width=True)
+
+# Top Units
+unit = filtered.groupby("Fleet Number").size().reset_index(name="Count").sort_values("Count", ascending=False)
+fig3 = px.bar(unit.head(10), x="Fleet Number", y="Count", title="🚛 Top 10 Unit dengan Alert Tertinggi")
+st.plotly_chart(fig3, use_container_width=True)
+
+# Heatmap jam kejadian
+filtered['Hour'] = filtered['Timestamp'].dt.hour
+hourly = filtered.groupby('Hour').size().reset_index(name="Count")
+fig4 = px.bar(hourly, x='Hour', y='Count', title="🕒 Peak Hour Fatigue Alerts")
+st.plotly_chart(fig4, use_container_width=True)
+
+st.caption("Created for Safety Improvement & Predictive Behavior Monitoring")