import streamlit as st import numpy as np import pandas as pd import joblib model = joblib.load('Churn_PredCls.joblib') gender = st.selectbox("Choose sex", ['Male', 'Female']) SeniorCitizen = st.sidebar.selectbox("SeniorCitizen", ['Yes', 'No']) Partner = st.sidebar.selectbox("Does he/she have partner?", ['No', 'Yes']) Dependents = st.sidebar.selectbox("Dependents", ['Yes', 'No']) tenure = st.slider("Choose tenure", 0, 100) PhoneService = st.sidebar.selectbox("PhoneService", ['No', 'Yes']) MultipleLines = st.sidebar.selectbox("MultipleLines", ['Yes', 'No']) InternetService = st.selectbox("InternetService", ['Fiber optic', 'DSL', 'No']) OnlineSecurity = st.sidebar.selectbox("OnlineSecurity", ['No', 'Yes']) OnlineBackup = st.sidebar.selectbox("OnlineBackup", ['Yes', 'No']) DeviceProtection = st.sidebar.selectbox("DeviceProtection", ['No', 'Yes']) TechSupport = st.sidebar.selectbox("TechSupport", ['Yes', 'No']) StreamingTV = st.sidebar.selectbox("StreamingTV", ['No', 'Yes']) StreamingMovies = st.sidebar.selectbox("StreamingMovies", ['Yes', 'No']) Contract = st.selectbox("Contract", ['Two year', 'One year', 'Month-to-month']) PaperlessBilling = st.sidebar.selectbox("PaperlessBilling", ['No', 'Yes']) PaymentMethod = st.selectbox("PaymentMethod", ['Credit card (automatic)', 'Electronic check', 'Mailed check', 'Bank transfer (automatic)']) MonthlyCharges = st.slider("MonthlyCharges", 0, 1000) TotalCharges = st.slider("TotalCharges", 0, 10000) columns = ['gender', 'SeniorCitizen', 'Partner', 'Dependents', 'tenure', 'PhoneService', 'MultipleLines', 'InternetService', 'OnlineSecurity', 'OnlineBackup', 'DeviceProtection', 'TechSupport', 'StreamingTV', 'StreamingMovies', 'Contract', 'PaperlessBilling', 'PaymentMethod', 'MonthlyCharges', 'TotalCharges'] rows = [gender, SeniorCitizen, Partner, Dependents, tenure, PhoneService, MultipleLines, InternetService, OnlineSecurity, OnlineBackup, DeviceProtection, TechSupport, StreamingTV, StreamingMovies, Contract, PaperlessBilling, PaymentMethod, MonthlyCharges, TotalCharges] def predict(): row = np.array(rows) X = pd.DataFrame([row], columns = columns) prediction = model.predict(X) if prediction[0] == 1: st.success('She/He will remain among the customers :thumbsup:') else: st.error('She/He will not remain among the customers :thumbsup:') trigger = st.button('Predict', on_click=predict)