Delete app.py

app.py

@@ -1,68 +0,0 @@
-import streamlit as st
-import numpy as np
-import pickle
-
-pipe = pickle.load(open('pipe.pkl','rb'))
-df = pickle.load(open('df.pkl','rb'))
-
-st.title("Laptop Price Predictor")
-
-company = st.selectbox('Brand',df['Company'].unique())
-
-
-type = st.selectbox('Type',df['TypeName'].unique())
-
-
-ram = st.selectbox('RAM(in GB)',[2,4,8,12,16,24,32,64])
-
-
-weight = st.number_input('Weight of laptop')
-
-
-touchscreen = st.selectbox('Touchscreen',['No','Yes'])
-
-
-ips = st.selectbox('IPS',['No','Yes'])
-
-
-screen_size = st.number_input('Screen Size')
-
-
-resolution = st.selectbox('Screen Resolution',['1920x1080','1600x900','3840x2160','3200x1800','2560x1600','2560x1440','2304x1440','1366x768','2880x1800'])
-
-
-cpu = st.selectbox('CPU',df['Cpu brand'].unique())
-
-
-hdd = st.selectbox('HDD(in GB)',[0,128,256,512,1024,2048])
-
-
-ssd = st.selectbox('SSD(in GB)',[0,8,128,256,512,1024,2048])
-
-
-gpu = st.selectbox('GPU',df['Gpu Brand'].unique())
-
-
-os = st.selectbox('Os',df['os'].unique())
-
-
-if st.button('Predict Price'):
-    if touchscreen=='Yes':
-        touchscreen = 1
-    else:
-        touchscreen = 0
-
-    if ips =='Yes':
-        ips = 1
-    else:
-        ips = 0
-
-    X_res = int(resolution.split('x')[0])
-    Y_res = int(resolution.split('x')[1])
-
-    ppi = ((X_res**2) + (Y_res**2))**0.5/screen_size
-
-    query = np.array([company,type,ram,weight,touchscreen,ips,ppi,cpu,hdd,ssd,gpu,os])
-
-    query = query.reshape(1,12)
-    st.title("The Predicted Price: "+str(int(np.exp(pipe.predict(query)[0]))))