René's URL Explorer Experiment

Title: import streamlit as st import pandas as pd from sklearn.linear_model import LinearRegression st.set_page_config(page_title="Mainpuri Property AI", layout="centered") st.title("🏡 Mainpuri Property Rate Prediction AI") # ---- Dummy data ---- data = { "size": [1000, 1500, 2000, 1200, 1800], "road_width": [20, 30, 40, 25, 35], "price": [2000000, 3500000, 5000000, 2500000, 4000000] } df = pd.DataFrame(data) X = df[["size", "road_width"]] y = df["price"] model = LinearRegression() model.fit(X, y) st.subheader("Enter Property Details") size = st.number_input("Land Size (sq ft)", min_value=100, max_value=10000, value=1200) road_width = st.number_input("Road Width (ft)", min_value=10, max_value=100, value=25) if st.button("Predict Price"): predicted_price = model.predict([[size, road_width]])[0] st.success(f"Predicted Property Price: ₹{predicted_price:,.0f}") · Issue #3 · codewithdev/codewithdev · GitHub

Open Graph Title: import streamlit as st import pandas as pd from sklearn.linear_model import LinearRegression st.set_page_config(page_title="Mainpuri Property AI", layout="centered") st.title("🏡 Mainpuri Property Rate Prediction AI") # ---- Dummy data ---- data = { "size": [1000, 1500, 2000, 1200, 1800], "road_width": [20, 30, 40, 25, 35], "price": [2000000, 3500000, 5000000, 2500000, 4000000] } df = pd.DataFrame(data) X = df[["size", "road_width"]] y = df["price"] model = LinearRegression() model.fit(X, y) st.subheader("Enter Property Details") size = st.number_input("Land Size (sq ft)", min_value=100, max_value=10000, value=1200) road_width = st.number_input("Road Width (ft)", min_value=10, max_value=100, value=25) if st.button("Predict Price"): predicted_price = model.predict([[size, road_width]])[0] st.success(f"Predicted Property Price: ₹{predicted_price:,.0f}") · Issue #3 · codewithdev/codewithdev

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Opengraph URL: https://github.com/codewithdev/codewithdev/issues/3

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