| import joblib import pandas as pd import streamlit as st | |
| model = joblib.load("daimond.joblib") unique_values = joblib.load("unique_values.joblib") | |
| unique_cut = unique_values["cut"] unique_color = unique_values["color"] unique_clarity = unique_values["clarity"] | |
| def main(): st.title("Diamond Prices") | |
| with st.form("questionaire"): | |
| carat = st.slider("Carat",min_value=0.00,max_value=5.00) | |
| cut = st.selectbox("Cut", options=unique_cut) | |
| color = st.selectbox("Color", options=unique_color) | |
| clarity = st.selectbox("Clarity", options=unique_clarity) | |
| depth = st.slider("Depth",min_value=0.00,max_value=100.00) | |
| table = st.slider("table",min_value=0.00,max_value=100.00) | |
| x = st.slider("length(mm)",min_value=0.01,max_value=10.00) | |
| y = st.slider("width(mm)",min_value=0.01,max_value=10.00) | |
| z = st.slider("depth(mm)",min_value=0.01,max_value=10.00) | |
| # clicked==True only when the button is clicked | |
| clicked = st.form_submit_button("Predict Price") | |
| if clicked: | |
| result=model.predict(pd.DataFrame({"carat": [carat], | |
| "cut": [cut], | |
| "color": [color], | |
| "clarity": [clarity], | |
| "depth":[depth], | |
| "table": [table], | |
| "size": [size], | |
| "length(mm)":[x], | |
| "width(mm)":[y], | |
| "depth(mm)":[z]})) | |
| # Show prediction | |
| st.success("Your predicted income is"+result) | |
| if name == "main": main() |