Update app.py

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 import altair as alt
 
 st.set_page_config(page_title="Shipment Monitoring Dashboard", layout="wide")
-st.title("\ud83d\ude9a Shipment Monitoring Dashboard")
+st.title("Shipment Monitoring Dashboard")
 
 uploaded_file = st.file_uploader("Upload your Excel file", type=["xlsx"])
 
@@ -38,13 +38,13 @@ if uploaded_file:
         df = df[df['Injection Gateway'] == selected_gateway]
 
     # Filter by ETA date range
-    st.subheader("\ud83d\udd0e Filter by ETA Date Range")
+    st.subheader("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")
+    st.subheader("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']
@@ -66,7 +66,7 @@ if uploaded_file:
     selected_status = selection.init['Shipment Status'] if selection else "Pending"
 
     # Volume by ETA
-    st.subheader("\ud83d\udcc5 Shipment Volume by ETA")
+    st.subheader("Shipment Volume by ETA")
     volume_by_eta = df.groupby('ETA').agg({
         'MAWB': 'count',
         'Cartons': 'sum',
@@ -83,7 +83,7 @@ if uploaded_file:
     st.altair_chart(line_chart, use_container_width=True)
 
     # Table view sorted by ETA and filtered by selected status
-    st.subheader("\ud83d\udd0d Shipment Detail View by ETA")
+    st.subheader("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)