Spaces:
Runtime error
Runtime error
File size: 1,533 Bytes
b123c5f 30ac382 b123c5f 9f5208e b123c5f 30ac382 b123c5f ea733c0 394db98 30ac382 90100f1 7017db6 b123c5f d854e6e e1f8d69 30ac382 d854e6e 566c988 73c52a6 b123c5f fb49a86 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 |
# -*- coding: utf-8 -*-
"""app.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1qmihuhzrIfWvaZodn-sxbyPBqKTF6Zqz
"""
import joblib
import pandas as pd
import streamlit as st
model = joblib.load('model.joblib')
unique_values = joblib.load('unique.joblib')
unique_LANDUSE_TYPE = unique_values["LANDUSE_TYPE"]
unique_USER = unique_values["USER"]
unique_Month = unique_values["Month"]
unique_vendor = unique_values["VENDOR"]
def main():
st.title("Water usage in town predict")
with st.form("questionaire"):
Land_use = st.selectbox("Land use",options = unique_LANDUSE_TYPE)
User = st.selectbox("User",options = unique_USER)
Month = st.selectbox("Month",options = unique_Month)
vendor = st.selectbox("Vendor",options = unique_vendor)
pipe_diam = st.number_input("pipe diameter(meter):",min_value=0.5, max_value=10.0, step=0.5)
clicked = st.form_submit_button("start predict ")
if clicked:
result=model.predict(pd.DataFrame({"LANDUSE_TYPE": [Land_use],
"USER": [User],
"Month": [Month],
"VENDOR": [vendor],
"PIPE DIAM": [pipe_diam]}))
str_result = str(result).strip("[]")
st.success("Water usage predict value:"+str_result+"cubic meters")
if __name__ == '__main__':
main() |