import streamlit as st import pandas as pd import joblib def app(): st.title("Transaction Data Input") st.write("Choose to upload a CSV file or manually input transaction data.") # Load pre-trained model with open('model.pkl', 'rb') as file_1: model = joblib.load(file_1) # Option to choose upload or manual input option = st.radio("Select input method:", ("Upload CSV", "Manual Input")) if option == "Upload CSV": # Option to upload a CSV file file_upload = st.file_uploader("Upload CSV", type=["csv"]) if file_upload is not None: data = pd.read_csv(file_upload) st.write("Uploaded Data Preview:") st.write(data.head()) if st.button("Submit CSV"): # Predict using the uploaded CSV data predictions = model.predict(data) data['prediction'] = predictions data['prediction'] = data['prediction'].map({1: 'Fraud Transactions', 0: 'Not Fraud Transactions'}) st.write("Predictions:") st.write(data[['type','nameOrig', 'nameDest', 'prediction']]) elif option == "Manual Input": st.write("Manually input data:") # Manual input of data step = st.number_input("Step", min_value=0) type = st.selectbox("Type", ["TRANSFER", "PAYMENT", "DEBIT", "CASH_OUT", "CASH_IN"]) amount = st.number_input("Amount", min_value=0.0) nameOrig = st.text_input("Origin Account Name") oldbalanceOrg = st.number_input("Old Balance (Origin)", min_value=0.0) newbalanceOrig = st.number_input("New Balance (Origin)", min_value=0.0) nameDest = st.text_input("Destination Account Name") oldbalanceDest = st.number_input("Old Balance (Destination)", min_value=0.0) newbalanceDest = st.number_input("New Balance (Destination)", min_value=0.0) isFlaggedFraud = st.selectbox("Is Flagged Fraud?", [0, 1]) if st.button("Submit"): # Create a DataFrame from manual input manual_data = pd.DataFrame({ "step": [step], "type": [type], "amount": [amount], "nameOrig": [nameOrig], "oldbalanceOrg": [oldbalanceOrg], "newbalanceOrig": [newbalanceOrig], "nameDest": [nameDest], "oldbalanceDest": [oldbalanceDest], "newbalanceDest": [newbalanceDest], "isFlaggedFraud": [isFlaggedFraud] }) st.write("Manual Input Data:") st.write(manual_data) # Predict using the manually input data manual_predictions = model.predict(manual_data) manual_data['prediction'] = manual_predictions manual_data['prediction'] = manual_data['prediction'].map({1: 'Fraud Transactions', 0: 'Not Fraud Transactions'}) st.write("Predictions:") st.write(manual_data[['type','nameOrig', 'nameDest', 'prediction']]) if __name__ == "__main__": app()