Upload app.py

app.py

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+import streamlit as st
+import pandas as pd
+import pickle
+
+st.title("predict Phone Proces")
+
+#import 
+svr1 = 'svr.pkl'
+sv = pickle.load(open(svr1, 'rb'))
+
+st.write('Insert feature to predict')
+Name = st.slider(label='Name', min_value=0, max_value=200, value=42, step=1)
+Ratings = st.selectbox(label='anemia', options=['0', '1'])
+Prices = st.slider(label='Prices', min_value=0, max_value=1000, value=420, step=1)
+Ram  = st.selectbox(label='Ram (GB)', options=['0', '1'])
+Rom = st.slider(label='Rom(GB)', min_value=0, max_value=200, value=42, step=1)
+ScreenSize = st.selectbox(label='Screen Size(Inches)', options=['0', '1'])
+FirstCam = st.slider(label='First Cam (MP)', min_value=100000.0, max_value=999999.0, value=420000.0, step=0.01)
+SecondCam = st.slider(label='Second Cam  (MP)', min_value=0.0, max_value=99.9, value=42.0, step=0.1)
+ThirdCam = st.slider(label='Third Cam  (MP)', min_value=0, max_value=999, value=42, step=1)
+FourthCam = st.selectbox(label='Fourth Cam  (MP)', options=['0', '1'])
+FrontCam = st.selectbox(label='Front Cam  (MP)', options=['0', '1'])
+Battery= st.slider(label='Batery  (mAh)', min_value=0, max_value=999, value=42, step=1)
+
+
+
+# color = st.number_input(label='Colour', min_value=240, max_value=255, value=245, step=1)
+
+# convert into dataframe
+
+data = pd.DataFrame({'Name': [Name],
+                'Ratings': [Ratings],
+                'Prices': [Prices],
+                'Ram ':[Ram],
+                'Rom': [Rom],
+                'ScreenSize': [ScreenSize],
+                'FirstCam ': [FirstCam],
+                'SecondCam': [SecondCam],
+                'ThirdCam': [ThirdCam],
+                'FourthCam': [FourthCam],
+                'FrontCam': [FrontCam],
+                'Battery': [Battery]})
+
+# model predict
+Phone_price = svr1.predict(data).tolist()[0]
+
+# interpretation
+st.write('Predition Result: ')
+if Phone_price == 0:
+    st.text('Mahal Jon')
+else:
+    st.text('Sikat')