|
import joblib import pandas as pd import streamlit as st |
|
|
|
model = joblib.load("daimondjubjub.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 = 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]})) |
|
|
|
st.success("Your predicted income is"+result) |
|
if name == "main": main() |
