Update app.py

app.py

@@ -141,15 +141,14 @@ def main():
 
     if uploaded_file is not None:
         try:
-            # Step 1: Read the Excel file into a DataFrame and automatically rename duplicate columns
-            df = pd.read_excel(uploaded_file, mangle_dupe_cols=True)
+            # Step 1: Read the Excel file into a DataFrame
+            df = pd.read_excel(uploaded_file)
 
-            # Step 2: Rename duplicate columns to make them more readable if needed
-            # Columns will already be unique, e.g., "Student Attendance [J]", "Student Attendance [J].1"
-            df.columns = [col.replace(".1", "_2").replace(".2", "_3") for col in df.columns]
+            # Step 2: Manually handle duplicate columns
+            df.columns = pd.io.parsers.base.make_unique(df.columns)
 
-            # Step 3: Replace student names with initials
-            df = replace_student_names_with_initials(df)
+            # Step 3: Rename duplicate columns to make them more readable
+            df.columns = [f"{col.split('.')[0]}_{i}" if '.' in col else col for i, col in enumerate(df.columns, 1)]
 
             # Step 4: Display the uploaded data
             st.subheader("Uploaded Data")
@@ -272,7 +271,9 @@ def plot_intervention_statistics(intervention_stats):
     st.pyplot(fig)
 
     return fig
+
     
+
 def compute_student_metrics(df):
     # Filter DataFrame for sessions where intervention happened
     intervention_df = df[df[INTERVENTION_COLUMN].str.strip().str.lower() == 'yes']
@@ -284,8 +285,12 @@ def compute_student_metrics(df):
     student_metrics = {}
 
     for col in student_columns:
-        # Extract student name or initials, removing any suffixes added for uniqueness
-        student_name = re.match(r'Student Attendance \[(.+?)\]', col).group(1)
+        try:
+            # Extract student name or initials, removing any suffixes added for uniqueness
+            student_name = re.match(r'Student Attendance \[(.+?)\]', col.split('_')[0]).group(1)
+        except AttributeError:
+            st.warning(f"Unexpected column name format: {col}. Skipping this column.")
+            continue
         # Get the attendance data for the student
         student_data = intervention_df[[col]].copy()