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import streamlit as st
import pandas as pd
import joblib
# Load your trained model
model = joblib.load('models\model1.pkl')
# Function to predict sales
def predict_sales(input_data):
# Make predictions using the loaded model
sales_prediction = model.predict(input_data)
return sales_prediction
# Streamlit app
def main():
st.title('Sales Prediction App')
# Input widgets
PromoInterval = st.selectbox("Promo Interval", ['No Promotion', 'Jan,Apr,Jul,Oct', 'Feb,May,Aug,Nov', 'Mar,Jun,Sept,Dec'])
# -----------------------------------------------------------------------------------------------
StoreType = st.radio("StoreType", ["Small Shop", "Medium Store", "Large Store", "Hypermarket"])
Assortment = st.radio("Assortment", ["basic", "extra", "extended"])
# Encode StateHoliday as 1 for 'Yes' and 0 for 'No' --------------------------------------
StateHoliday = st.radio("State Holiday", ["Yes", "No"])
StateHoliday = 1 if StateHoliday == "Yes" else 0
SchoolHoliday = st.radio("School Holiday", ["Yes", "No"])
SchoolHoliday = 1 if SchoolHoliday == "Yes" else 0
Promo = st.radio("Promotion", ["store is participating", "store is not participating"])
Promo = 1 if Promo == "store is participating" else 0
# ----------------------------------------------------------------------------------------
Store = st.slider("Store", 1, 1115)
Customers = st.slider("Customers", 0, 7388)
CompetitionDistance = st.slider("Competition Distance", 20, 75860)
CompetitionOpenSinceMonth = st.slider("Competition Open Since Month", 1, 12)
CompetitionOpenSinceYear = st.slider("Competition Open Since Year", 1998, 2015)
# ----------------------------------------------------------------------------------------
# Store user inputs
input_data = pd.DataFrame({
'PromoInterval': [PromoInterval],
'StoreType': [StoreType],
'Assortment': [Assortment],
'StateHoliday': [StateHoliday],
'Store': [Store],
'Customers': [Customers],
'Promo': [Promo],
'SchoolHoliday': [SchoolHoliday],
'CompetitionDistance': [CompetitionDistance],
'CompetitionOpenSinceMonth': [CompetitionOpenSinceMonth],
'CompetitionOpenSinceYear': [CompetitionOpenSinceYear]
})
# Display input data
st.subheader('Input Data:')
st.write(input_data)
# Predict sales
# if st.button('Predict Sales'):
# prediction = predict_sales(input_data)
# st.write('Predicted Sales:', prediction)
if st.button('Predict Sales'):
prediction = predict_sales(input_data)[0]
formatted_prediction = "{:.2f}".format(prediction) # Format prediction to display two decimal points
st.write('Predicted Sales:', formatted_prediction)
if __name__ == '__main__':
main()
# Record at index 795018:
# PromoInterval Jan,Apr,Jul,Oct
# StoreType Small Shop
# Assortment basic
# StateHoliday 0
# Store 650
# Customers 636
# Promo 1
# SchoolHoliday 0
# CompetitionDistance 1420
# CompetitionOpenSinceMonth 10
# CompetitionOpenSinceYear 2012
# Sales 6322
# Name: 795018, dtype: object |