Update app.py

app.py

@@ -23,10 +23,6 @@ logged_model = 'runs:/a45156c210f149b2abbfe15e5b824cc4/model'
 # Load model as a PyFuncModel.
 loaded_model = mlflow.pyfunc.load_model(logged_model)
 
-@st.cache_data
-def convert_df(df):
-   return df.to_csv(index=False).encode('utf-8')
-
 def run():
    # init
    st.set_page_config(page_title="Loan Default Prediction App")
@@ -36,13 +32,13 @@ def run():
    if uploaded_file is not None:
       # do prediction
       data = pd.read_csv(uploaded_file)
-      prediction = loaded_model.predict(data.iloc[:, :-1])
+      prediction = loaded_model.predict(data)
 
       # show the result
       st.write(prediction)
 
       # download the result
-      # csv = convert_df(prediction)
+      # csv = prediction.to_csv(index=False).encode('utf-8')
       # if st.download_button('Download Prediction', csv, 'prediction.csv'):
       #    st.write('Thanks for downloading!')