Update app.py

app.py

@@ -3,9 +3,9 @@ import pandas as pd
 import altair as alt
 
 st.set_page_config(page_title="Shipment Monitoring Dashboard", layout="wide")
-st.title("🚚 Shipment Monitoring Dashboard")
+st.title("\ud83d\ude9a Shipment Monitoring Dashboard")
 
-uploaded_file = st.file_uploader("Upload the Excel file", type=["xlsx"])
+uploaded_file = st.file_uploader("Upload your Excel file", type=["xlsx"])
 
 if uploaded_file:
     df = pd.read_excel(uploaded_file, sheet_name=0)
@@ -29,6 +29,7 @@ if uploaded_file:
             return "Ship Out"
 
     df['Shipment Status'] = df.apply(determine_status, axis=1)
+    df['ETA'] = pd.to_datetime(df['ETA'])
 
     # Filter for Injection Gateway
     injection_gateways = df['Injection Gateway'].dropna().unique().tolist()
@@ -36,43 +37,53 @@ if uploaded_file:
     if selected_gateway != "All":
         df = df[df['Injection Gateway'] == selected_gateway]
 
-    # Shipment status summary
-    st.subheader("📊 Shipment Status Distribution")
-    status_counts = df['Shipment Status'].value_counts().reset_index()
+    # Filter by ETA date range
+    st.subheader("\ud83d\udd0e Filter by ETA Date Range")
+    min_date, max_date = df['ETA'].min(), df['ETA'].max()
+    start_date, end_date = st.date_input("Select ETA date range:", [min_date, max_date], min_value=min_date, max_value=max_date)
+    df = df[(df['ETA'] >= pd.to_datetime(start_date)) & (df['ETA'] <= pd.to_datetime(end_date))]
+
+    # Shipment status distribution with interactive selection
+    st.subheader("\ud83d\udcca Shipment Status Distribution")
+    status_order = ["Pending", "WH-IN", "Cargo Ready", "Ship Out"]
+    status_counts = df['Shipment Status'].value_counts().reindex(status_order).reset_index()
     status_counts.columns = ['Shipment Status', 'Count']
+    status_counts = status_counts.dropna()
+
+    # Altair selection for interactivity
+    selection = alt.selection_single(fields=['Shipment Status'], bind='legend', name='Select', init={'Shipment Status': 'Pending'})
+
     chart = alt.Chart(status_counts).mark_bar().encode(
-        x='Shipment Status',
+        x=alt.X('Shipment Status', sort=status_order),
         y='Count',
         color='Shipment Status',
-        tooltip=['Shipment Status', 'Count']
-    )
+        tooltip=['Shipment Status', 'Count'],
+        opacity=alt.condition(selection, alt.value(1), alt.value(0.4))
+    ).add_params(selection).properties(height=300)
+
     st.altair_chart(chart, use_container_width=True)
 
+    selected_status = selection.init['Shipment Status'] if selection else "Pending"
+
     # Volume by ETA
-    st.subheader("📅 Shipment Volume by ETA")
-    df['ETA'] = pd.to_datetime(df['ETA'])
+    st.subheader("\ud83d\udcc5 Shipment Volume by ETA")
     volume_by_eta = df.groupby('ETA').agg({
         'MAWB': 'count',
         'Cartons': 'sum',
-        'Packages': 'sum',
-        'Weights': 'sum'
     }).reset_index().rename(columns={'MAWB': 'Shipment Count'})
 
     st.dataframe(volume_by_eta, use_container_width=True)
 
-    line_chart = alt.Chart(volume_by_eta).transform_fold(
-        ['Shipment Count', 'Cartons', 'Packages', 'Weights'],
-        as_=['Metric', 'Value']
-    ).mark_line(point=True).encode(
+    line_chart = alt.Chart(volume_by_eta).mark_line(point=True).encode(
         x='ETA:T',
-        y='Value:Q',
-        color='Metric:N',
-        tooltip=['ETA:T', 'Metric:N', 'Value:Q']
+        y='Cartons:Q',
+        tooltip=['ETA:T', 'Shipment Count:Q', 'Cartons:Q']
     ).properties(height=400)
 
     st.altair_chart(line_chart, use_container_width=True)
 
-    # Table view sorted by ETA
-    st.subheader("🔍 Shipment Detail View by ETA")
-    sorted_df = df[['MAWB', 'ETA', 'ATA', 'Shipment Status', 'Cartons', 'Last Mile Carrier']].sort_values(by='ETA')
+    # Table view sorted by ETA and filtered by selected status
+    st.subheader("\ud83d\udd0d Shipment Detail View by ETA")
+    filtered_df = df[df['Shipment Status'] == selected_status]
+    sorted_df = filtered_df[['MAWB', 'ETA', 'ATA', 'Shipment Status', 'Cartons', 'Last Mile Carrier']].sort_values(by='ETA')
     st.dataframe(sorted_df, use_container_width=True)