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