| import streamlit as st |
| from utils import PrepProcesor, columns |
|
|
| import numpy as np |
| import pandas as pd |
| import joblib |
|
|
| model = joblib.load('xgbpipe.joblib') |
| st.title('Will you survive if you were among Titanic passengers or not :ship:') |
| |
| passengerid = st.text_input("Input Passenger ID", '8585') |
| pclass = st.selectbox("Choose class", [1,2,3]) |
| name = st.text_input("Input Passenger Name", 'Soheil Tehranipour') |
| sex = st.select_slider("Choose sex", ['male','female']) |
| age = st.slider("Choose age",0,100) |
| sibsp = st.slider("Choose siblings",0,10) |
| parch = st.slider("Choose parch",0,10) |
| ticket = st.text_input("Input Ticket Number", "8585") |
| fare = st.number_input("Input Fare Price", 0,1000) |
| cabin = st.text_input("Input Cabin", "C52") |
| embarked = st.select_slider("Did they Embark?", ['S','C','Q']) |
|
|
| def predict(): |
| row = np.array([passengerid,pclass,name,sex,age,sibsp,parch,ticket,fare,cabin,embarked]) |
| X = pd.DataFrame([row], columns = columns) |
| prediction = model.predict(X) |
| if prediction[0] == 1: |
| st.success('Passenger Survived :thumbsup:') |
| else: |
| st.error('Passenger did not Survive :thumbsdown:') |
|
|
| trigger = st.button('Predict', on_click=predict) |
|
|
|
|
