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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 = """
<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)
# 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() |