Update app.py

app.py

@@ -13,14 +13,11 @@ uploaded_file = st.file_uploader("Upload your dataset (CSV format)", type="csv")
 
 if uploaded_file is not None:
     # Load the dataset
-    df = pd.read_csv(uploaded_file)
-
-    st.write("### Uploaded Dataset")
-    st.write(df)
+    df = pd.read_csv(uploaded_file, index_col=0)
 
     # Dynamically calculate the mean ignoring NaN values
     df['Average_score'] = df[['Boss_score', 'Colleague_score', 'Colleague_other_score',
-                              'Report_score', 'Customer_score', 'All_raters_Score']].mean(axis=1, skipna=True)
+                              'Report_score', 'Customer_score']].mean(axis=1, skipna=True)
 
     # Round the calculated average score to 2 decimal places
     df['Average_score'] = df['Average_score'].round(1)
@@ -69,7 +66,8 @@ if uploaded_file is not None:
     y_prob = gnb.predict_proba(X)
     confidence_scores = y_prob.max(axis=1)
     df['Confidence_score'] = confidence_scores
-
+    df =df.drop('All_raters_Score', axis = 1)
+    
     st.write("### Processed Dataset")
     st.write(df)