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eda.py

@@ -7,10 +7,11 @@ import matplotlib.pyplot as plt
 def app():
     st.title('Exploratory Data Analysis')
 
-    df = pd.read_csv('deployment/eda_data.csv')
-    st.write('Dataset Preview')
+    df = pd.read_csv('eda_data.csv')
+    st.subheader('Dataset Preview')
     st.write(df)
 
+    st.subheader('Data Analysis Questions')
     st.write('How is the percentage of default payment as education level increases?')
     vis_1(df)
 

prediction.py

@@ -2,6 +2,67 @@
 import streamlit as st
 import numpy as np
 import pandas as pd
+import joblib
 
 def app():
-    st.title('Prediction for Default Payment on the Next Month')
+    st.title('Prediction for Default Payment on the Next Month')
+
+    df = pd.read_csv('eda_data.csv')
+    st.subheader('Dataset Preview')
+    st.write(df)
+
+    st.subheader('Input Data')
+    input = user_input(df)
+
+    st.subheader('User Input')
+    st.write(input)
+
+    load_model = joblib.load("model.pkl")
+
+    prediction = load_model.predict(input)
+
+    if prediction == 1:
+        prediction = 'Payment Defaulted (1)'
+    else:
+        prediction = 'Payment Not Defaulted (0)'
+
+    st.subheader('Prediction Result:')
+    st.write('Based on user input, the model predicted: ')
+    st.write(prediction)
+
+def user_input(df):
+    limit_balance = st.number_input('limit_balance', value=0.0)
+    education_level = st.selectbox('education_level', df['education_level'].unique())
+    pay_1 = st.selectbox('pay_1', [i for i in range(-1, 13)])
+    pay_2 = st.selectbox('pay_2', [i for i in range(-1, 13)])
+    pay_3 = st.selectbox('pay_3', [i for i in range(-1, 13)])
+    pay_4 = st.selectbox('pay_4', [i for i in range(-1, 13)])
+    pay_5 = st.selectbox('pay_5', [i for i in range(-1, 13)])
+    pay_6 = st.selectbox('pay_6', [i for i in range(-1, 13)])
+    pay_amt_1 = st.number_input('pay_amt_1', value=0.0)
+    pay_amt_2 = st.number_input('pay_amt_2', value=0.0)
+    pay_amt_3 = st.number_input('pay_amt_3', value=0.0)
+    pay_amt_4 = st.number_input('pay_amt_4', value=0.0)
+    pay_amt_5 = st.number_input('pay_amt_5', value=0.0)
+    pay_amt_6 = st.number_input('pay_amt_6', value=0.0)
+
+    data = {
+        'limit_balance' : limit_balance,
+        'education_level' : education_level,
+        'pay_1' : pay_1,
+        'pay_2' : pay_2,
+        'pay_3': pay_3,
+        'pay_4' : pay_4,
+        'pay_5' : pay_5,
+        'pay_6' : pay_6,
+        'pay_amt_1' : pay_amt_1,
+        'pay_amt_2' : pay_amt_2,
+        'pay_amt_3' : pay_amt_3,
+        'pay_amt_4' : pay_amt_4,
+        'pay_amt_5' : pay_amt_5,
+        'pay_amt_6' : pay_amt_6
+    }
+    features = pd.DataFrame(data, index=[0])
+    return features
+
+