import numpy as np
import pandas as pd
import pickle
import streamlit as st
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.preprocessing import LabelEncoder
import datetime
data=pd.read_excel('Data_Train.xlsx')
data.drop(['Route','Duration'],axis=1)
data['Total_Stops'].map({'non-stop':0, '2 stops':2, '1 stop':3, '3 stops':3,'4 stops':4})
label=LabelEncoder()
data['Airline']=label.fit_transform(data['Airline'])
data['Source']=label.fit_transform(data['Source'])
data['Destination']=label.fit_transform(data['Destination'])
data['Additional_Info']=label.fit_transform(data['Additional_Info'])
data['Total_Stops']=label.fit_transform(data['Total_Stops'])
x=data.drop(['Price','Route','Duration'],axis=1)
y=data['Price']
model=RandomForestRegressor()
model.fit(x,y)
def main():
st.title("Flight-Price-Prediction")
st.write(" *--Built using StreamLit--* ")
st.subheader("Select Source")
source = st.selectbox(" " , ['Bangalore', 'Mumbai','Delhi','Kolkata',"Chennai"])
if source == "Bangalore":
source_inp = 0
elif source == "Chennai":
source_inp = 1
elif source == "Delhi":
source_inp = 2
elif source == "Kolkata":
source_inp = 3
elif source == "Mumbai":
source_inp = 4
st.write("Source -- " , source)
#destination
st.subheader("Select Destination")
dest = st.selectbox("" , ['Bangalore', 'Cochin', 'Hyderabad',"New Delhi",'Delhi','Kolkata'])
if dest == "Bangalore":
dest_inp = 0
elif dest == "Cochin":
dest_inp = 1
elif dest == "Delhi":
dest_inp = 2
elif dest == "Hyderabad":
dest_inp = 3
elif dest == "Kolkata":
dest_inp = 4
elif dest == "New Delhi":
dest_inp = 5
st.write("Destination -- ",dest)
#airline
st.subheader("Select Airline")
airline = st.selectbox(" " , ["Air India","GoAir","IndiGo","Jet Airways","Multiple carriers","SpiceJet",
"Vistara","Air Asia"])
if airline == "Jet Airways":
air_inp = 0
elif airline == "IndiGo":
air_inp = 1
elif airline == "Air India":
air_inp = 2
elif airline == "Multiple carriers":
air_inp = 3
elif airline == "SpiceJet":
air_inp = 4
elif airline == "Vistara":
air_inp = 5
elif airline == "Air Asia":
air_inp = 6
elif airline == "GoAir":
air_inp = 7
st.write("Airline -- " , airline)
addition_info=st.selectbox(" ",['No info', 'In-flight meal not included',
'No check-in baggage included', '1 Short layover', 'No Info',
'1 Long layover', 'Change airports', 'Business class',
'Red-eye flight', '2 Long layover'])
if addition_info== 'No info':
addition_info=8
elif addition_info== 'In-flight meal not included':
addition_info=7
elif addition_info== 'No check-in baggage included':
addition_info=6
elif addition_info== '1 Short layover':
addition_info=5
elif addition_info== '1 Long layover':
addition_info=4
elif addition_info== 'Change airports':
addition_info=3
elif addition_info== 'Business class':
addition_info=2
elif addition_info== 'Red-eye flight':
addition_info=1
elif addition_info== '2 Long layover':
addition_info=0
Date_of_Journey=st.date_input('Enter your journy',datetime.date(2019,1,1))
Dep_Time=st.time_input("Enter Dep_time")
Arrival_Time=st.time_input("Enter Arrival_Time")
st.subheader("Select Stops")
stop = st.selectbox(" " , [0,1,2,3,4])
st.write("Stops -- ", stop)
if st.button("PREDICT"):
result= model.predict([[air_inp , source_inp , dest_inp ,stop ,Date_of_Journey , Dep_Time , Arrival_Time ]])
st.success("The flight price is {}".format(result))
if __name__ == "__main__":
main()
please find the error i got in the above code
I would guess your error is at Date_of_Journey, as predictive models generally don’t take dates directly as inputs. But without the input data or model, it’s hard to say.
Best,
Randy