import streamlit as st import pandas as pd from joblib import dump, load # model Model= load('RF_model.joblib') # predict def predict_fare(features): fare = Model.predict([features]) return fare def main(): # st.title("Flight Fair Predictions") html_temp = """

Streamlit Flight Fair Predictions ML App

""" st.markdown(html_temp, unsafe_allow_html=True) # 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] # 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 input_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_fare(input_values) st.success(f'Expected Flight Fare is : ₹ {result[0]}') st.write("") if __name__ == "__main__": main()