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"""
Milestone 2
Nama: Devin Yaung Lee
Batch: HCK-009
// eda.py //
program ini menjadi base model EDA interface.
"""
import streamlit as st
import pandas as pd
import pickle
import streamlit as st
import pandas as pd
import pickle
def run():
st.title("Predict the Shipping On Time")
with open('model.pkl', 'rb') as file:
full_process = pickle.load(file)
# Collecting user input
warehouse_block = st.selectbox('Warehouse Block', ['A', 'B', 'C', 'D', 'E'])
mode_of_shipment = st.selectbox('Mode of Shipment', ['Flight', 'Ship', 'Road'])
customer_care_calls = st.selectbox('Customer Care Calls', [1, 2, 3, 4, 5, 6, 7])
customer_rating = st.selectbox('Customer Rating', [1, 2, 3, 4, 5])
cost_of_the_product = st.number_input('Cost of the Product (in USD)', min_value=0)
prior_purchases = st.selectbox('Prior Purchases', [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
product_importance = st.selectbox('Product Importance', ['low', 'medium', 'high'])
gender = st.selectbox('Gender', ['F', 'M'])
discount_offered = st.number_input('Discount Offered (in %)', min_value=0)
weight_in_gms = st.number_input('Weight (in grams)', min_value=0)
# Creating a DataFrame with the user input
data_inf = pd.DataFrame({
'warehouse_block': [warehouse_block],
'mode_of_shipment': [mode_of_shipment],
'customer_care_calls': [customer_care_calls],
'customer_rating': [customer_rating],
'cost_of_the_product': [cost_of_the_product],
'prior_purchases': [prior_purchases],
'product_importance': [product_importance],
'gender': [gender],
'discount_offered': [discount_offered],
'weight_in_gms': [weight_in_gms]
})
st.write('Review your input:')
st.table(data_inf)
if st.button('Predict'):
# Make prediction
prediction = full_process.predict(data_inf)
if prediction == 0:
st.success("The model predicts the shipment will not be on time!")
else:
st.success("The model predicts the shipment will be on time!")
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