Update app.py

app.py

@@ -1,58 +1,58 @@
-import streamlit as st 
-import  joblib
-from datetime import date
-import numpy as np
-
-
-html_temp = """
-    <div style="background-color:tomato;padding:10px">
-    <h2 style="color:white;text-align:center;">Streamlit AIR Pollution Prediciton  ML App </h2>
-    </div>
-    """
-st.markdown(html_temp, unsafe_allow_html=True)
-
-image_url="https://wallpapercave.com/wp/wp6100544.jpg"
-
-st.image(image_url, caption="Image from URL", use_column_width=True)
-
-# Name
-name=st.selectbox("Select Name" ,options=['Emissions',"Pollution","Asthma-Related","Hospitalizations"])
-name_index=['Emissions',"Pollution","Asthma-Related","Hospitalizations"]
-name_value= name_index.index(name)
-
-# Measure
-measure=st.selectbox("Select Measure ",options=["Density","Miles","Rates","Concentration"])
-measure_index=["Density","Miles","Rates","Concentration"]
-measure_value =measure_index.index(measure)
-
-# Geo_Type_Name
-Geo_Type_Name=st.selectbox('Select Geo_Type_Name',options=["UHF42",'UHF34','Borough','CD','Citywi'])
-Geo_Type_Name_index=["UHF42",'UHF34','Borough','CD','Citywi']
-Geo_Type_Name_value =Geo_Type_Name_index.index(Geo_Type_Name)
-
-# Geo_Place_Name
-Geo_Place_Name=st.selectbox('Select Geo_Place_Name',options=['Queens','Unknown','Brooklyn','Bronx','Manhattan','Staten Island=5'])
-Geo_Place_Name_index=['Queens','Unknown','Brooklyn','Bronx','Manhattan','Staten Island=5']
-Geo_Place_Name_value=Geo_Place_Name_index.index(Geo_Place_Name)
-
-#time_period
-time_period=st.selectbox('select Time Period',options=['Other','Annual Average','Summer','Winter'])
-time_period_index=['Other','Annual Average','Summer','Winter']
-time_period_value=time_period_index.index(time_period)
-
-# Data_Values
-Data_values=st.slider("Enter The Data Values",min_value=0,max_value=424,value=1)
-
-# model
-model=joblib.load('Air_pollution_prediction_rf_model.joblib')
-
-
-if st.button("submit"):
-    output=model.predict([[name_value,measure_value,Geo_Type_Name_value,Geo_Place_Name_value,time_period_value,Data_values]])
-    
-    if output==0:
-        st.text_area('',' Air Pollution is Moderate')
-    elif output==1:
-        st.text_area('',' Air Pollution is Good')
-    elif output==2:
-        st.text_area('',"Air Pollution is Bad")
+import streamlit as st 
+import  joblib
+from datetime import date
+import numpy as np
+
+
+html_temp = """
+    <div style="background-color:tomato;padding:10px">
+    <h2 style="color:white;text-align:center;">Streamlit AIR Pollution Prediciton  ML App </h2>
+    </div>
+    """
+st.markdown(html_temp, unsafe_allow_html=True)
+
+image_url="https://wallpapercave.com/wp/wp6100544.jpg"
+
+st.image(image_url, use_container_width=True)
+
+# Name
+name=st.selectbox("Select Name" ,options=['Emissions',"Pollution","Asthma-Related","Hospitalizations"])
+name_index=['Emissions',"Pollution","Asthma-Related","Hospitalizations"]
+name_value= name_index.index(name)
+
+# Measure
+measure=st.selectbox("Select Measure ",options=["Density","Miles","Rates","Concentration"])
+measure_index=["Density","Miles","Rates","Concentration"]
+measure_value =measure_index.index(measure)
+
+# Geo_Type_Name
+Geo_Type_Name=st.selectbox('Select Geo_Type_Name',options=["UHF42",'UHF34','Borough','CD','Citywi'])
+Geo_Type_Name_index=["UHF42",'UHF34','Borough','CD','Citywi']
+Geo_Type_Name_value =Geo_Type_Name_index.index(Geo_Type_Name)
+
+# Geo_Place_Name
+Geo_Place_Name=st.selectbox('Select Geo_Place_Name',options=['Queens','Unknown','Brooklyn','Bronx','Manhattan','Staten Island=5'])
+Geo_Place_Name_index=['Queens','Unknown','Brooklyn','Bronx','Manhattan','Staten Island=5']
+Geo_Place_Name_value=Geo_Place_Name_index.index(Geo_Place_Name)
+
+#time_period
+time_period=st.selectbox('select Time Period',options=['Other','Annual Average','Summer','Winter'])
+time_period_index=['Other','Annual Average','Summer','Winter']
+time_period_value=time_period_index.index(time_period)
+
+# Data_Values
+Data_values=st.slider("Enter The Data Values",min_value=0,max_value=424,value=1)
+
+# model
+model=joblib.load('Air_pollution_prediction_rf_model.joblib')
+
+
+if st.button("submit"):
+    output=model.predict([[name_value,measure_value,Geo_Type_Name_value,Geo_Place_Name_value,time_period_value,Data_values]])
+    
+    if output==0:
+        st.text_area('',' Air Pollution is Moderate')
+    elif output==1:
+        st.text_area('',' Air Pollution is Good')
+    elif output==2:
+        st.text_area('',"Air Pollution is Bad")