aesthetic changes 3

pages/3_Saved_Scenarios.py

@@ -211,10 +211,10 @@ def summary_df_to_worksheet(df, ws):
             ws.cell(row=i, column=j + 1, value=header[i - 1]).font = Font(bold=True, color='00000000')
             ws.cell(row=i,column=j+1).fill = heading_fill
             # ws.cell.border = border_style
-        if  col > 1 and (col - 6)%5==0:    
-            ws.merge_cells(start_row=1, end_row=1, start_column = col-3, end_column=col)
-            ws.cell(row=1,column=col).alignment = Alignment(horizontal='center')
-            # ws.cell.border = border_style
+        # if  col > 1 and (col - 6)%5==0:    
+        #     ws.merge_cells(start_row=1, end_row=1, start_column = col-3, end_column=col)
+        #     ws.cell(row=1,column=col).alignment = Alignment(horizontal='center')
+        #     # ws.cell.border = border_style
     # Apply borders to all cells, including empty cells
     for row in ws.iter_rows():
         for cell in row:

response_curves_model_quality_base.py

@@ -12,7 +12,7 @@ df= pd.read_csv('response_curves_input_file.csv')
 df.dropna(inplace=True)
 df['Date'] = pd.to_datetime(df['Date'])
 df.reset_index(inplace=True)
-
+import random
 channel_cols = [
  'Broadcast TV',
  'Cable TV',
@@ -93,7 +93,7 @@ def data_output(channel,X,y,y_fit_inv,x_ext_data,y_fit_inv_ext):
     plot_df = pd.DataFrame()
    
     plot_df[f'{channel}_Spends'] = X
-
+    plot_df[f'{channel}_Prospects'] = y
     plot_df['Date'] = df['Date']
     plot_df['MAT'] = df['MAT']
     
@@ -114,6 +114,7 @@ def data_output(channel,X,y,y_fit_inv,x_ext_data,y_fit_inv_ext):
 #     print(x_ext_data)
     ext_df = pd.DataFrame()
     ext_df[f'{channel}_Spends'] = x_ext_data
+    ext_df[f'{channel}_Prospects'] = y_fit_inv_v2_ext
     ext_df[fit_col] = y_fit_inv_v2_ext
     
     ext_df['Date'] =  [
@@ -124,7 +125,7 @@ def data_output(channel,X,y,y_fit_inv,x_ext_data,y_fit_inv_ext):
 
     ext_df['MAT'] = ["ext","ext","ext"]
     
-    print(ext_df)
+    print(ext_df.columns)
     plot_df= plot_df.append(ext_df)
     return plot_df
 

summary_df.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bb50f23e164ddf0cae9b81a28e47f97561d83e444b951bcf2e8192d70eadc7ce
+oid sha256:ef1d30472601a41557559d3fe1b39fe0a08bfa581a66af23a210e9dc459b750c
 size 1822