Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,21 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+import joblib
+import numpy as np
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
+with open("src/House_Linear","rb") as f:
+    model = joblib.load(f)
 
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
+st.title(":orange[House] in USA:house:")
 
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
+sqft_living = st.number_input("sqft_living: ",min_value=0.1,max_value=100000.0,step=1.0)
+sqft_lot = st.number_input("sqft_lot: ",min_value=0.1,max_value=1000000.0,step=1.0)
+floors = st.number_input("floors: ",min_value=0.1,max_value=10.0,step=1.0)
+Bedrooms = st.number_input("Bedrooms: ",min_value=1.0,max_value=5.0,step=1.0)
+Condition = st.number_input("Condition: ",min_value=1,max_value=5,step=1)
 
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
 
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+if st.button("Estimate"):
+    model_input = np.array([[sqft_living,sqft_lot,floors,Bedrooms,Condition]])
+    prediction = model.predict(model_input)
+    formatted_pred = round(prediction[0].item(),2)
+    st.write(f"House Analysis: {formatted_pred}")