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import joblib import pandas as pd import streamlit as st |
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model = joblib.load("daimondx.joblib") unique_values = joblib.load("unique_values (1).joblib") |
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unique_cut = unique_values["cut"] unique_color = unique_values["color"] unique_clarity = unique_values["clarity"] |
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def main(): st.title("Diamond Prices") |
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with st.form("questionaire"): |
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carat = st.slider("Carat",min_value=0.00,max_value=5.00) |
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cut = st.selectbox("Cut", options=unique_cut) |
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color = st.selectbox("Color", options=unique_color) |
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clarity = st.selectbox("Clarity", options=unique_clarity) |
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depth = st.slider("Depth",min_value=0.00,max_value=100.00) |
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table = st.slider("table",min_value=0.00,max_value=100.00) |
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x = st.slider("length(mm)",min_value=0.01,max_value=10.00) |
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y = st.slider("width(mm)",min_value=0.01,max_value=10.00) |
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z = st.slider("depth(mm)",min_value=0.01,max_value=10.00) |
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clicked = st.form_submit_button("Predict Price") |
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if clicked: |
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result=model.predict(pd.DataFrame({"carat": [carat], |
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"cut": [cut], |
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"color": [color], |
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"clarity": [clarity], |
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"depth":[depth], |
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"table": [table], |
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"size": [size], |
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"length(mm)":[x], |
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"width(mm)":[y], |
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"depth(mm)":[z]})) |
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st.success("Your predicted income is"+result) |
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if name == "main": main() |
