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RF_model.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b281e50fea47fdf98bca4232d4a90bb5f57b94fc33c9db869d45b6957c1bd969
+size 45133345

app.py

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+import streamlit as st
+import pandas as pd
+from joblib import dump, load
+
+# model
+Model= load('RF_model.joblib')
+
+# predict
+def predict_note_authentication(values):
+    ans=Model.predict([values])
+    return ans
+def main():
+    # st.title("Flight Fair Predictions")
+    html_temp = """
+    <div style="background-color:tomato;padding:10px">
+    <h2 style="color:white;text-align:center;">Streamlit Flight Fair Predictions ML App </h2>
+    </div>
+    """
+    st.markdown(html_temp, unsafe_allow_html=True)
+    
+    # Airline selection
+    Airline_options = ['Jet Airways', 'IndiGo', 'Air India', 'Multiple carriers', 
+                       'SpiceJet', 'Vistara', 'Air Asia', 'GoAir', 
+                       'Multiple carriers Premium economy', 'Jet Airways Business', 
+                       'Vistara Premium economy', 'Trujet']
+    Airline = st.selectbox('Airline', options=Airline_options)
+    Airline_dict = {'Jet Airways': 3849, 'IndiGo': 2053, 'Air India': 1751, 
+                    'Multiple carriers': 1196, 'SpiceJet': 818, 'Vistara': 479, 
+                    'Air Asia': 319, 'GoAir': 194, 'Multiple carriers Premium economy': 13, 
+                    'Jet Airways Business': 6, 'Vistara Premium economy': 3, 'Trujet': 1}
+    Airline_value = Airline_dict.get(Airline, 0)  # default to 0 if not found
+    
+    # Total Stops selection
+    Total_Stops_options = ['non-stop', '1 stop', '2 stops', '3 stops', '4 stops']
+    Total_Stops = st.selectbox('Total Stops', options=Total_Stops_options)
+    Total_Stops_dict = {'non-stop': 0, '1 stop': 1, '2 stops': 2, '3 stops': 3, '4 stops': 4}
+    Total_Stops_value = Total_Stops_dict.get(Total_Stops, 0)  # default to 0 if not found
+    
+    # Date_of_Journey
+    Date_of_Journey=st.date_input('Date_of_Journey')
+    Day_of_Journey=pd.to_datetime(Date_of_Journey).day
+    Month_of_Journey=pd.to_datetime(Date_of_Journey).month
+    
+    # Dep_Time
+    Dep_Time=st.text_input("Dep_Time (HH:MM)", "00:00")
+    # Convert Dep_Time to string in the format "HH:MM"
+    time_dep = pd.to_datetime(Dep_Time, format='mixed')
+    Dep_hour=time_dep.hour
+    Dep_min=time_dep.minute
+    
+    # Arrival_Time
+    Arrival_Time=st.text_input("Arrival Time (HH:MM)", "13:30")
+    time_arr = pd.to_datetime(Arrival_Time, format='mixed')
+    Arrival_hour=time_arr.hour
+    Arrival_min=time_arr.minute
+    
+    # Duration
+    departure_hour, departure_minute = map(int, Dep_Time.split(':'))
+    arrival_hour, arrival_minute = map(int, Arrival_Time.split(':'))
+    Duration_hour = arrival_hour - departure_hour   # Calculate the duration
+    Duration_minute = arrival_minute - departure_minute
+
+    if Duration_minute < 0:
+        Duration_hour -= 1
+        Duration_minute += 60
+        
+    Duration_in_min = Duration_hour*60 + Duration_minute
+    
+    # In-flight meal not included
+    In_flight_meal_not_included=st.selectbox('In-flight meal not included',options=['yes','no'])
+    if In_flight_meal_not_included=='yes':
+        In_flight_meal_not_included=1
+    else:
+        In_flight_meal_not_included=0
+        
+    # No check-in baggage included
+    No_check_in_baggage_included=st.selectbox('No check-in baggage included',options=['yes','no'])
+    if No_check_in_baggage_included=='yes':
+        No_check_in_baggage_included=1
+    else:
+        No_check_in_baggage_included=0
+    
+    # Source
+    Source=st.selectbox('Source',options=['Banglore','Chennai','Delhi','Kolkata','Mumbai'])
+    source_index = ['Banglore', 'Chennai', 'Delhi', 'Kolkata', 'Mumbai']
+    source_value = [1 if src == Source else 0 for src in source_index]
+    
+    # Destination
+    Destination=st.selectbox('Destination',options=['Banglore',
+                                                    'Cochin',
+                                                    'Delhi',
+                                                    'Hyderabad',
+                                                    'Kolkata'])
+    destination_index = ['Banglore', 'Cochin', 'Delhi', 'Hyderabad', 'Kolkata']
+    destination_value = [1 if dest == Destination else 0 for dest in destination_index]
+        
+    values=[Airline_value, Total_Stops_value, Day_of_Journey, Month_of_Journey,
+            Dep_hour, Dep_min, Arrival_hour, Arrival_min, Duration_in_min,
+            In_flight_meal_not_included, No_check_in_baggage_included]+source_value+destination_value
+    
+    if st.button("Predict"):
+        result=predict_note_authentication(values)
+        st.success(f'Expected Flight price is : {result}')
+    
+if __name__ == "__main__":
+    main()