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app.py

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+import streamlit as st
+import pandas as pd
+import plotly.graph_objects as go
+
+# Load the Excel file
+file_path = 'Dhaka Metro Rail Fare 2.XLSX'  # Ensure the correct file path
+df = pd.read_excel(file_path)
+
+# Ensure necessary columns are present
+required_columns = ['Origin', 'Destination', 'Fare (৳)']
+if not all(col in df.columns for col in required_columns):
+    st.write("Please ensure the file contains 'Origin', 'Destination', and 'Fare' columns.")
+else:
+    # Add coordinates for each station (example coordinates for illustration)
+    coordinates = {
+        "Uttara North": (23.869066, 90.367445),
+        "Uttara Center": (23.860118, 90.365106),
+        "Uttara South": (23.845934, 90.363175),
+        "Pallabi": (23.82619516961383, 90.36481554252525),
+        "Mirpur 11": (23.819438208310213, 90.36528532902963),
+        "Mirpur 10": (23.808582994847285, 90.36821595330717),
+        "Kazipara": (23.800017952100532, 90.37178261495391),
+        "Shewrapara": (23.79070140857881, 90.37564622631841),
+        "Agargaon": (23.778385546736345, 90.3800557456356),
+        "Bijoy Sarani": (23.766638127271825, 90.38307537134754),
+        "Farmgate": (23.75923604938459, 90.38694218434738),
+        "Kawran Bazar": (23.751392319539104, 90.39275707447003),
+        "Shahbagh": (23.740324209546923, 90.39600784811131),
+        "Dhaka University": (23.732091083122114, 90.39659408796354),
+        "Bangladesh Secretariat": (23.73004754106779, 90.40764881366906),
+        "Motijheel": (23.72816566933198, 90.41923497972823),
+        "Kamalapur": (23.732367758919807, 90.42547378971085)
+    }
+
+    # Add latitude and longitude for origin and destination based on the coordinates dictionary
+    df['Origin_Lat'] = df['Origin'].map(lambda x: coordinates.get(x, (None, None))[0])
+    df['Origin_Lon'] = df['Origin'].map(lambda x: coordinates.get(x, (None, None))[1])
+    df['Destination_Lat'] = df['Destination'].map(lambda x: coordinates.get(x, (None, None))[0])
+    df['Destination_Lon'] = df['Destination'].map(lambda x: coordinates.get(x, (None, None))[1])
+
+    # Filter rows with missing coordinates
+    df.dropna(subset=['Origin_Lat', 'Origin_Lon', 'Destination_Lat', 'Destination_Lon'], inplace=True)
+
+    # Streamlit UI setup
+    st.title("Dhaka Metro Rail Fare Checker 🚇")
+    st.write("Below is the fare chart for Dhaka Metro Rail 💶:")
+
+    # Instruction sidebar
+    st.sidebar.title("Instructions")
+    st.sidebar.write("""
+    **Welcome to the Dhaka Metro Rail Fare Checker!**
+   
+    *How to use:*
+    1. Select your **Location station** from the dropdown menu.
+    2. Select your **destination(s)** from the list. You can select multiple destinations.
+    3. The fare from your location to the selected destination(s) will be displayed below.
+    4. You can also see the stations marked on a map.
+    
+    **Note:** The map highlights your location in green and destinations in blue.
+    
+    If you face any issues or need further assistance, feel free to [Contact Support on WhatsApp](https://wa.me/+8801719296601).
+    """)
+
+    # Define the default "Select Journey from" message
+    default_origin = "Select Journey from"
+
+    # Dropdown for selecting origin (with "Select Journey from" as a default placeholder)
+    origin = st.selectbox(
+        "Select your Location:", 
+        [default_origin] + df['Origin'].unique().tolist(),  # Add the "Select Journey from" option at the top
+        index=0  # Ensure the first option is selected by default
+    )
+
+    # Initialize session state for destination selection if not already set
+    if 'destination_select' not in st.session_state:
+        st.session_state.destination_select = []
+
+    # Multiselect for destinations (pass the default from session state)
+    destinations = st.multiselect(
+        "Select your destination(s):", 
+        df['Destination'].unique(), 
+        default=st.session_state.destination_select
+    )
+
+    # Update session state based on the selected destinations
+    st.session_state.destination_select = destinations
+
+    # If the user hasn't selected a valid origin yet, don't proceed
+    if origin == default_origin:
+        st.write("Please select a valid origin station to proceed.")
+    elif origin and destinations:
+        # Filter the dataframe based on user selection
+        fare_data = df[(df['Origin'] == origin) & (df['Destination'].isin(destinations))]
+
+        # Display the fare data
+        if not fare_data.empty:
+            for index, row in fare_data.iterrows():
+                st.write(f"Fare from {origin} to {row['Destination']} is: {row['Fare (৳)']}৳")
+        else:
+            st.write("No fare data available for the selected origin and destinations.")
+    else:
+        st.write("Please select both an origin and at least one destination.")
+
+    # Plotting the map using Plotly
+    fig = go.Figure()
+
+    # Add markers for each unique station
+    unique_stations = pd.concat([df[['Origin', 'Origin_Lat', 'Origin_Lon']].rename(columns={'Origin': 'Station', 'Origin_Lat': 'Lat', 'Origin_Lon': 'Lon'}), 
+                                 df[['Destination', 'Destination_Lat', 'Destination_Lon']].rename(columns={'Destination': 'Station', 'Destination_Lat': 'Lat', 'Destination_Lon': 'Lon'})]).drop_duplicates()
+
+    # Add a map marker for each station
+    for i, row in unique_stations.iterrows():
+        if row['Station'] == origin:
+            # Mark the origin as green
+            fig.add_trace(go.Scattermapbox(
+                mode="markers+text",
+                lon=[row['Lon']],
+                lat=[row['Lat']],
+                marker={'size': 12, 'color': 'green'},
+                text=row['Station'],
+                textposition="top center",
+                name=row['Station'],
+                customdata=[row['Station']]  # customdata is now a list
+            ))
+        elif row['Station'] in destinations:
+            # Mark the destination as blue
+            fig.add_trace(go.Scattermapbox(
+                mode="markers+text",
+                lon=[row['Lon']],
+                lat=[row['Lat']],
+                marker={'size': 12, 'color': 'blue'},
+                text=row['Station'],
+                textposition="top center",
+                name=row['Station'],
+                customdata=[row['Station']]  # customdata is now a list
+            ))
+        else:
+            # Mark all other stations as red
+            fig.add_trace(go.Scattermapbox(
+                mode="markers+text",
+                lon=[row['Lon']],
+                lat=[row['Lat']],
+                marker={'size': 12, 'color': 'red'},
+                text=row['Station'],
+                textposition="top center",
+                name=row['Station'],
+                customdata=[row['Station']]  # customdata is now a list
+            ))
+
+    # Map layout
+    fig.update_layout(
+        mapbox=dict(
+            style="open-street-map",
+            center=go.layout.mapbox.Center(lat=23.780, lon=90.400),  # Center on Dhaka
+            zoom=11
+        ),
+        margin={"r":0,"t":0,"l":0,"b":0},
+        showlegend=False,
+        title="Dhaka Metro Rail Location Map"
+    )
+
+    # Show plot in Streamlit
+    st.plotly_chart(fig)