Update app.py

app.py

@@ -1,33 +1,33 @@
-import pandas as pd,numpy as np
-import pickle
-import streamlit as st
-
-st.title("User Behavior Using Mobile Prediction")
-
-Device Model = st.text_input("Enter Device_Model_type")
-App Usage Time (min/day)= st.number_input("Enter house size")
-location = st.text_input("Enter the location")
-city = st.text_input("Enter the city")
-numBathrooms = st.number_input("Enter the number of bathrooms")
-SecurityDeposit = st.number_input("Enter the deposit amount")
-Status = st.text_input("Enter the status of house")
-
-model_2 = pickle.load(open(r"C:\Users\nadip\Music\MACHINE LEARNING\ML Project\rfr.pkl","rb")) #pickle file path
-
-if st.button("Submit"):
-    result = model_2.predict([[house_type,house_size,location,city,numBathrooms,SecurityDeposit,Status]])
-    st.write(f"The predicted price of the rental house is {result}")
-    
-    
-# age = st.number_input("Enter age",min_value=0,max_value=1000,step=1,format="%d" )
-# gender = st.radio("Enter gender",['Male','Female'])
-# chestpain = st.selectbox("chestpain",['non-anginal_pain', 'typical_angina', 'atypical_angina','asymptomatic'])
-# restingBP =  st.number_input("Enter BP",min_value=0,max_value=1000,step=1,format="%d")
-# serum_cholesterol = st.number_input("Enter serum_cholesterol",min_value=0,max_value=10000,step=1,format="%d")
-# fasting_blood_sugar = st.radio("Enter fasting_blood_sugar",['yes','no'])
-# restingrelectro= st.selectbox("Enter resting_electro",['ST-T_wave_abnormality', 'normal', 'left_ventricular_hypertrophy'])
-# maxheartrate = st.number_input("Enter max_heart_rate",min_value=0,max_value=1000,step=1,format="%d")
-# exerciseangia =  st.radio("Enter exercise_angia",['yes','no'])
-# oldpeak= st.number_input("Enter oldpeak")
-# slope = st.selectbox("Enter slope",['downsloping', 'upsloping', 'flat'])
+import pandas as pd,numpy as np
+import pickle
+import streamlit as st
+
+st.title("User Behavior Using Mobile Prediction")
+
+Device_Model = st.text_input("Enter Device_Model_type")
+App_Usage_Time (min/day)= st.number_input("Enter house size")
+location = st.text_input("Enter the location")
+city = st.text_input("Enter the city")
+numBathrooms = st.number_input("Enter the number of bathrooms")
+SecurityDeposit = st.number_input("Enter the deposit amount")
+Status = st.text_input("Enter the status of house")
+
+# model_2 = pickle.load(open(r"Mobile_data_user_behavior/rfc.pkl","rb")) #pickle file path
+
+# if st.button("Submit"):
+#     result = model_2.predict([[house_type,house_size,location,city,numBathrooms,SecurityDeposit,Status]])
+#     st.write(f"The predicted price of the rental house is {result}")
+    
+    
+# age = st.number_input("Enter age",min_value=0,max_value=1000,step=1,format="%d" )
+# gender = st.radio("Enter gender",['Male','Female'])
+# chestpain = st.selectbox("chestpain",['non-anginal_pain', 'typical_angina', 'atypical_angina','asymptomatic'])
+# restingBP =  st.number_input("Enter BP",min_value=0,max_value=1000,step=1,format="%d")
+# serum_cholesterol = st.number_input("Enter serum_cholesterol",min_value=0,max_value=10000,step=1,format="%d")
+# fasting_blood_sugar = st.radio("Enter fasting_blood_sugar",['yes','no'])
+# restingrelectro= st.selectbox("Enter resting_electro",['ST-T_wave_abnormality', 'normal', 'left_ventricular_hypertrophy'])
+# maxheartrate = st.number_input("Enter max_heart_rate",min_value=0,max_value=1000,step=1,format="%d")
+# exerciseangia =  st.radio("Enter exercise_angia",['yes','no'])
+# oldpeak= st.number_input("Enter oldpeak")
+# slope = st.selectbox("Enter slope",['downsloping', 'upsloping', 'flat'])
 # noofmajorvessels = st.selectbox("enter number of major vessels",['Three', 'One', 'Zero', 'Two'])