| import joblib |
| import pandas as pd |
| import streamlit as st |
|
|
| model = joblib.load("daimondx.joblib") unique_values = joblib.load("unique_values (1).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() |
