Update app.py

app.py

@@ -1,49 +1,49 @@
 import pandas as pd
 import gradio as gr
 
-# Pivot between Model↔Texter schedules (7-day weekly format)
+# Pivot between Model↔Texter schedules (7-day weekly format), handling merged headers
 def convert_schedule(file_path, direction):
-    # 1. Load schedule: first column is index; use two header rows to capture proper day labels
-    df = pd.read_excel(file_path, header=[0,1], index_col=0)
-    # Combine multi-index headers: take the second row (actual day names)
-    # level 0 may contain merged group labels (e.g., timeslot), level 1 has actual dates/days
-    df.columns = df.columns.get_level_values(1).astype(str)
+    # 1. Try reading with two header rows for merged timeslot/day layouts
+    try:
+        df = pd.read_excel(file_path, header=[0,1], index_col=0)
+        # Extract the second-level headers (actual days)
+        second_level = df.columns.get_level_values(1).astype(str)
+        # If these are all unnamed, fallback
+        if all(lbl.startswith('Unnamed') for lbl in second_level):
+            raise ValueError
+        df.columns = second_level
+    except Exception:
+        # Fallback: single header row, simple day labels
+        df = pd.read_excel(file_path, header=0, index_col=0)
+        df.columns = df.columns.astype(str)
 
-    # Drop any 'Unnamed' or blank day columns
+    # 2. Drop any 'Unnamed' or blank header columns
     df = df.loc[:, ~df.columns.str.match(r'^Unnamed')]
 
-    # Determine the name of the index column after reset_index()()
-    index_name = df.index.name or 'index'
-
-    # 2. Setup melting parameters based on direction
+    # 3. Determine id/val columns
     if direction == 'A to B':
-        # A-format: models in index, texters in cells → output: texters as rows, models as cell values
-        id_col = 'Model'
-        val_col = 'Texter'
-        df_reset = df.reset_index().rename(columns={index_name: id_col})
+        id_col, val_col = 'Model', 'Texter'
     else:
-        # B-format: texters in index, models in cells → output: models as rows, texters as cell values
-        id_col = 'Texter'
-        val_col = 'Model'
-        df_reset = df.reset_index().rename(columns={index_name: id_col})
+        id_col, val_col = 'Texter', 'Model'
 
-    # 3. Melt into long form: [id_col, Day, val_col]
+    # 4. Melt into long format
+    df_reset = df.reset_index().rename(columns={df.index.name or df.columns.name or '': id_col})
     df_melt = df_reset.melt(id_vars=[id_col], var_name='Day', value_name=val_col)
-    # Drop empty assignments
     df_melt = df_melt.dropna(subset=[val_col])
 
-    # 4. Pivot back to wide: index=val_col, columns=Day, values=id_col
+    # 5. Pivot table: join duplicates with comma
     pivot = df_melt.pivot_table(
         index=val_col,
         columns='Day',
         values=id_col,
-        aggfunc='first'
+        aggfunc=lambda x: ', '.join(map(str, x))
     )
+    pivot = pivot.fillna('')
 
-    # 5. Reorder columns to match original days order and fill empties
+    # 6. Reorder columns to match original
     result = pivot.reindex(columns=df.columns.tolist(), fill_value='')
 
-    # Cleanup axis names for display
+    # Cleanup axis names
     result.index.name = None
     result.columns.name = None
     return result
@@ -59,10 +59,10 @@ iface = gr.Interface(
     title='7-Day Schedule Pivot',
     description=(
         'Upload a 7-column weekly schedule (Models vs Days), then flip between '  
-        'Models→Texters or Texters→Models. Maintains original days order.'
+        'Models→Texters or Texters→Models. Maintains original days order, even with merged headers.'
     ),
     allow_flagging='never'
 )
 
 if __name__ == '__main__':
-    iface.launch(server_name='0.0.0.0', server_port=7860)
+    iface.launch(server_name='0.0.0.0', server_port=7860)