aesthetic changes 1

Model_Result_Overview.py

@@ -29,6 +29,7 @@ st.set_page_config(layout='wide')
 load_local_css('styles.css')
 set_header()
 
+st.title("Model Result Overview")
 
 def get_random_effects(media_data, panel_col, mdf):
     random_eff_df = pd.DataFrame(columns=[panel_col, "random_effect"])
@@ -107,19 +108,22 @@ if auth_status:
         a=1
     
     # st.header("")
-    st.markdown("<h5 style='font-weight: normal;'>MMM Readout for Selected Period</h5>", unsafe_allow_html=True)
+    # st.markdown("<h5 style='font-weight: normal;'>MMM Readout for Selected Period</h5>", unsafe_allow_html=True)
     #### Input Select Start and End Date  
     
     # Create two columns for start date and end date input
     col1, col2 = st.columns(2)
-                                                                
+
+    # now = datetime.now()
+    # us_format = now.strftime("%m/%d/%Y")
+                                                                    
     with col1:
         default_date = datetime(2024, 1, 28)
         start_date = st.date_input("Start Date: ",value=default_date)
         
     with col2:
         default_date = datetime(2024, 2, 24)
-        end_date = st.date_input("End Date: ",value=default_date)
+        end_date = st.date_input("End Date: ",value = default_date)
     
     # col1, col2 = st.columns(2)
     # with col1:
@@ -141,7 +145,26 @@ if auth_status:
     with col1:
         selected_option = st.selectbox('Select a comparison', options)
     with col2:
-        st.write("")
+        st.markdown("""</br>""",unsafe_allow_html=True)
+        if selected_option == "Month on Month" :
+
+            st.markdown(
+                f"""
+                <div style="padding: 5px; border-radius: 5px; background-color: #FFFFE0; width: fit-content; display: inline-block;">
+                    <strong> Comparision of current month spends to previous month spends</strong>
+                </div>
+                """,
+                unsafe_allow_html=True
+            )
+        else :
+            st.markdown(
+                f"""
+                <div style="padding: 5px; border-radius: 5px; background-color: #FFFFE0; width: fit-content; display: inline-block;">
+                    <strong> Comparision of current month spends to the same month in previous year</strong>
+                </div>
+                """,
+                unsafe_allow_html=True
+            )
         # Waterfall chart
     fig = sf.waterfall(start_date,end_date,selected_option)
     st.plotly_chart(fig,use_container_width=True)
@@ -152,6 +175,7 @@ if auth_status:
 
     ## Channel Contribution Bar Chart
     st.plotly_chart(sf.channel_contribution(start_date,end_date),use_container_width=True)
+    st.plotly_chart(sf.chanel_spends(start_date,end_date),use_container_width=True)
     # Format first three rows in percentage format
     # styled_df = sf.shares_table_func(shares_df)
     # # styled_df = styled_df.round(0).astype(int)
@@ -162,8 +186,8 @@ if auth_status:
 
         # st.table(styled_df)
     st.dataframe(sf.shares_table_func(shares_df),use_container_width=True)
-
-    st.dataframe(sf.eff_table_func(shares_df),use_container_width=True)
+    
+    st.dataframe(sf.eff_table_func(shares_df).style.format({"TOTAL SPEND": "{:,.0f}", "TOTAL SUPPORT": "{:,.0f}", "TOTAL CONTRIBUTION": "{:,.0f}"}),use_container_width=True)
 
         ### CPP CHART
     st.plotly_chart(sf.cpp(start_date,end_date),use_container_width=True)

Streamlit_functions.py

@@ -142,7 +142,7 @@ def pie_charts(start_date,end_date):
                         # title = "Distribution of Contributions"
                         ), 1, 2)
     fig.update_layout(
-        title="Distribution of Spends and Contributions"
+        title="Distribution Of Spends And Contributions"
     )
 
     return fig
@@ -167,7 +167,7 @@ def pie_spend(start_date,end_date):
 
     # Customize the layout
     fig.update_layout(
-        title="Distribution of Spends"
+        title="Distribution Of Spends"
     )
 
     # Show the figure
@@ -194,7 +194,7 @@ def pie_contributions(start_date,end_date):
     # fig.add_annotation(showarrow=False)
     # Customize the layout
     fig.update_layout(
-        title="Distribution of Contributions",
+        title="Distribution Of Contributions",
         # margin=dict(t=0, b=0, l=0, r=0)
     )
     
@@ -268,8 +268,8 @@ def waterfall(start_date,end_date,btn_chart):
             x=[labels[i]],
             y=[cumulative[i+1] - cumulative[i]],
             base=[cumulative[i]],
-            text=[f"{abs(values[i])}"],
-            textposition='outside',
+            text=[f"{abs(values[i]):,}"],
+            textposition='auto',
             hovertemplate=hover_text,
             marker=dict(color=color),
             showlegend=False
@@ -281,7 +281,7 @@ def waterfall(start_date,end_date,btn_chart):
     # Updating layout for black background and gray gridlines
     if btn_chart == "Month on Month":
         fig.update_layout(
-            title=f"Change in MMM Estimated Prospect Contribution <br>{start_date_prev.strftime('%Y-%m-%d')} to {end_date_prev.strftime('%Y-%m-%d')} vs. {start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')}"
+            title=f"Change In MMM Estimated Prospect Contribution <br>{start_date_prev.strftime('%m-%d-%Y')} to {end_date_prev.strftime('%m-%d-%Y')} vs. {start_date.strftime('%m-%d-%Y')} to {end_date.strftime('%m-%d-%Y')}"
             ,showlegend=False,
             # plot_bgcolor='black',
             # paper_bgcolor='black',
@@ -295,13 +295,20 @@ def waterfall(start_date,end_date,btn_chart):
                 showgrid=True,
                 gridcolor='gray',  # Setting y-axis gridline color to gray
                 zeroline=False,  # Hiding the y-axis zero line
-                range=[18000, max(cumulative)+1000]  # Setting the y-axis range from 19k to slightly above the maximum value
+                # range=[18000, max(max(cumulative), max(values)) + 1000] # Setting the y-axis range from 19k to slightly above the maximum value
             )
-        
-        )
+            )
+        # fig.update_xaxes(
+        #         tickmode="array",
+        #         # categoryorder="total ascending",
+        #         tickvals=[f"{abs(values[i])}"],
+        #         ticktext=[f"{abs(values[i])}"],
+        #         ticklabelposition="outside",
+        #         tickfont=dict(color="white"),
+        # )
     else :
         fig.update_layout(
-            title=f"Change in MMM Estimated Prospect Contribution <br>{start_date_prev.strftime('%Y-%m-%d')} to {end_date_prev.strftime('%Y-%m-%d')} vs. {start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')}"
+            title=f"Change In MMM Estimated Prospect Contribution <br>{start_date_prev.strftime('%m-%d-%Y')} to {end_date_prev.strftime('%m-%d-%Y')} vs. {start_date.strftime('%m-%d-%Y')} to {end_date.strftime('%m-%d-%Y')}"
             ,showlegend=False,
             # plot_bgcolor='black',
             # paper_bgcolor='black',
@@ -315,7 +322,7 @@ def waterfall(start_date,end_date,btn_chart):
                 showgrid=True,
                 gridcolor='gray',  # Setting y-axis gridline color to gray
                 zeroline=False,  # Hiding the y-axis zero line
-                range=[10000, max(cumulative)+1000]  # Setting the y-axis range from 19k to slightly above the maximum value
+                # range=[10000, max(cumulative)+1000]  # Setting the y-axis range from 19k to slightly above the maximum value
             )
         
         )
@@ -418,13 +425,13 @@ def channel_contribution(start_date,end_date):
         x=channel_df['channels'],
         y=round(channel_df['contributions']),
         marker=dict(color='rgb(74, 136, 217)'),  # Blue color for all bars
-        text=round(channel_df['contributions']),
+        text=(channel_df['contributions']).astype(int).apply(lambda x: f"{x:,}"),
         textposition='outside'
     )])
 
     # Updating layout for better visualization
     fig.update_layout(
-        title=f"Media Contribution <br> {cur_data['Date'].min().strftime('%Y-%m-%d')} to {cur_data['Date'].max().strftime('%Y-%m-%d')}",
+        title=f"Media Contribution <br> {cur_data['Date'].min().strftime('%m-%d-%Y')} to {cur_data['Date'].max().strftime('%m-%d-%Y')}",
         # plot_bgcolor='black',
         # paper_bgcolor='black',
         # font=dict(color='white'),  # Changing font color to white for better contrast
@@ -442,6 +449,54 @@ def channel_contribution(start_date,end_date):
     )
 
     return fig
+
+def chanel_spends(start_date,end_date):
+
+    # if pd.isnull(start_date) == True :
+    #     start_date = datetime(2024, 1, 28)
+    # if pd.isnull(end_date) == True :
+    #     end_date = datetime(2024, 2, 24)
+ 
+    start_date = pd.to_datetime(start_date)
+    end_date = pd.to_datetime(end_date)
+
+    cur_data = df[(df['Date'] >= start_date) & (df['Date'] <= end_date)]
+
+    channel_df = pd.DataFrame(cur_data[spend_cols].sum()).reset_index()
+    channel_df.columns = ["channels","spends"]
+    channel_df["channels"] = channels
+
+    # Creating the bar chart
+    fig = go.Figure(data=[go.Bar(
+        x=channel_df['channels'],
+        y=round(channel_df['spends']),
+        marker=dict(color='rgb(74, 136, 217)'),  # Blue color for all bars
+        text=channel_df['spends'].apply(numerize),
+        # text = (channel_df['spends']).astype(int).apply(lambda x: f"{x:,}"),
+        textposition='outside'
+    )])
+
+    # Updating layout for better visualization
+    fig.update_layout(
+        title=f"Media Spends <br> {cur_data['Date'].min().strftime('%m-%d-%Y')} to {cur_data['Date'].max().strftime('%m-%d-%Y')}",
+        # plot_bgcolor='black',
+        # paper_bgcolor='black',
+        # font=dict(color='white'),  # Changing font color to white for better contrast
+        xaxis=dict(
+            showgrid=False,
+            gridcolor='gray',  # Setting x-axis gridline color to gray
+            zeroline=False,  # Hiding the x-axis zero line
+        ),
+        yaxis=dict(
+            title="Spends ($)",
+            showgrid=True,
+            gridcolor='gray',  # Setting y-axis gridline color to gray
+            zeroline=False,  # Hiding the y-axis zero line
+        )
+    )
+
+    return fig
+
 def shares_table_func(shares_df):
 
     # if pd.isnull(start_date) == True :
@@ -488,7 +543,7 @@ def eff_table_func(shares_df):
     media_df.index = media_df["MEDIA"]
     media_df.drop(columns = ["MEDIA"],inplace = True)
     for c in ["TOTAL SPEND","TOTAL SUPPORT","TOTAL CONTRIBUTION"]:
-        media_df[c] = media_df[c].astype(int).astype(str)
+        media_df[c] = media_df[c].astype(int)
     for c in ["SPEND SHARE","SUPPORT SHARE","CONTRIBUTION SHARE"]:
         media_df[c] = media_df[c].astype(int)
         media_df[c] = media_df[c].astype(str)+'%'
@@ -535,7 +590,7 @@ def cpp(start_date,end_date):
 
     # Update layout for better visualization
     fig.update_layout(
-        title=f"CPP distribution  <br>{cur_data['Date'].min().strftime('%Y-%m-%d')} to {cur_data['Date'].max().strftime('%Y-%m-%d')}"
+        title=f"CPP Distribution  <br>{cur_data['Date'].min().strftime('%m-%d-%Y')} to {cur_data['Date'].max().strftime('%m-%d-%Y')}"
         ,
         # plot_bgcolor='black',
         # paper_bgcolor='black',
@@ -572,8 +627,8 @@ def base_decomp():
 
     # Update layout for better visualization
     fig.update_layout(
-        title=f"Base decomposition"
-        # <br>{cur_data['Date'].min().strftime('%Y-%m-%d')} to {cur_data['Date'].max().strftime('%Y-%m-%d')}"
+        title=f"Base Decomposition"
+        # <br>{cur_data['Date'].min().strftime('%m-%d-%Y')} to {cur_data['Date'].max().strftime('%m-%d-%Y')}"
         ,
         # plot_bgcolor='black',
         # paper_bgcolor='black',
@@ -664,7 +719,7 @@ def media_decomp():
 
     # Updating layout for better visualization
     fig.update_layout(
-        title=f"Media decomposition",# <br>{cur_data['Date'].min().strftime('%Y-%m-%d')} to {cur_data['Date'].max().strftime('%Y-%m-%d')}",
+        title=f"Media Decomposition",# <br>{cur_data['Date'].min().strftime('%m-%d-%Y')} to {cur_data['Date'].max().strftime('%m-%d-%Y')}",
         # plot_bgcolor='black',
         # paper_bgcolor='black',
         # font=dict(color='white'),  # Changing font color to white for better contrast
@@ -753,12 +808,14 @@ def elasticity(media_df):
         x=media_df['coeff'],
         y=media_df['category'],
         orientation='h',  # Setting the orientation to horizontal
-        marker_color='rgba(75, 136, 257, 1)'  # Color for the bars
+        marker_color='rgba(75, 136, 257, 1)',  
+        text= media_df['coeff'].round(2),
+        textposition="outside"
     ))
 
     # Updating layout for better visualization
     fig.update_layout(
-        title="Media and Baseline Elasticity",
+        title="Media And Baseline Elasticity",
         xaxis=dict(
             title="Elasticity (coefficient)",
             showgrid=True,
@@ -790,7 +847,9 @@ def half_life(media_df):
         x=media_df[media_df['half_life'].isnull()==False]['half_life'],
         y=media_df[media_df['half_life'].isnull()==False]['category'],
         orientation='h',  # Setting the orientation to horizontal
-        marker_color='rgba(75, 136, 257, 1)'  # Color for the bars
+        marker_color='rgba(75, 136, 257, 1)',  
+        text= media_df['coeff'].round(2),
+        textposition="outside"
     ))
 
     # Updating layout for better visualization
@@ -856,8 +915,15 @@ def model_metrics_table_func():
                                  calculate_bic(df["Y"], df["Y_hat"])])
     model_metrics_df.index = ["R-squared","Adjusted R-squared","MAPE","AIC","BIC"]
     model_metrics_df = model_metrics_df.transpose()
-    model_metrics_df.index = ['']
-    return model_metrics_df.round(2)
+    # model_metrics_df.index = model_metrics_df["R-squared"]
+    # model_metrics_df = model_metrics_df.drop(columns=["R-squared"])
+    model_metrics_df2 = pd.DataFrame(model_metrics_df.values,columns=["R-squared","Adjusted R-squared","MAPE","AIC","BIC"] )
+    model_metrics_df2 = model_metrics_df2.round(2)
+    model_metrics_df2["AIC"] = model_metrics_df2["AIC"].round(0)
+    model_metrics_df2["BIC"] = model_metrics_df2["BIC"].round(0)
+    model_metrics_df2.index = [" "]
+    # model_metrics_df2 = model_metrics_df2.reset_index(drop = True)
+    return model_metrics_df2
 
 
 def scenario_spend_forecasting(delta_df,start_date,end_date):

pages/1_Model_Quality.py

@@ -10,7 +10,7 @@ st.set_page_config(
 
 
 st.header("Model Quality")
-st.write("MMM Model Quality")
+# st.write("MMM Model Quality")
 
 st.plotly_chart(sf.mmm_model_quality(),use_container_width=True)
     
@@ -18,7 +18,7 @@ media_df = sf.media_data()
     # Create two columns for start date and end date input
 col1, col2 = st.columns(2)
 
-st.table(sf.model_metrics_table_func()) 
+st.dataframe(sf.model_metrics_table_func(),hide_index  = True,use_container_width=True) 
 
 with col1:
     st.plotly_chart(sf.elasticity(media_df))
@@ -48,10 +48,10 @@ options1 = [
 col1, col2 = st.columns(2)
      # Create a dropdown menu   
 with col1:
-    selected_option = st.selectbox('Select a media channel:', options)
-    selected_option2 = st.selectbox('Select a Chart Type', options1)
+    selected_option = st.selectbox('Select A Media Channel:', options)
+    selected_option2 = st.selectbox('Select A Chart Type', options1)
          # Display the selected option
-    st.plotly_chart(rc1.response_curves(selected_option,selected_option2))
+    
 with col2:
     st.write("")
-   
+st.plotly_chart(rc1.response_curves(selected_option,selected_option2))  

pages/3_Saved_Scenarios.py

@@ -20,6 +20,7 @@ st.set_page_config(layout='wide')
 load_local_css('styles.css')
 set_header()
 
+st.title("Saved Scenarios")
 # for k, v in st.session_state.items():
 #     if k not in ['logout', 'login','config'] and not k.startswith('FormSubmitter'):
 #         st.session_state[k] = v
@@ -87,7 +88,14 @@ def comparison_scenarios_df():
             _df = _df.set_index('Channel')
             summary_df_prospect = summary_df_prospect.merge(_df, left_index=True, right_index=True)
     st.session_state['disable_download_button'] = False
-    return summary_df_spend,summary_df_prospect
+
+    efficiency_df = pd.DataFrame(index = summary_df_prospect.index)
+
+    for c in summary_df_spend.columns:
+        efficiency_df[c] = (summary_df_prospect[c]/summary_df_prospect[c].sum())/(summary_df_spend[c]/summary_df_spend[c].sum())
+        efficiency_df[c] = efficiency_df[c].round(2)
+        
+    return summary_df_spend,summary_df_prospect,efficiency_df
 
 
 
@@ -107,7 +115,7 @@ def plot_comparison_chart(df,metric):
 
     # Create the layout
     layout = go.Layout(
-        title='Scenario comparison '+ metric,
+        title='Comparing '+ metric,
         xaxis_title="Channels",
         yaxis_title=metric,
         barmode='group'
@@ -119,12 +127,13 @@ def plot_comparison_chart(df,metric):
     return fig
 
 def create_comparison_plots():
-    comparison_scenarios_df()
-    spends_df, prospects_df = comparison_scenarios_df()
-
+    # comparison_scenarios_df()
+    spends_df, prospects_df, efficiency_df = comparison_scenarios_df()
+    # st.dataframe(spends_df)
     st.plotly_chart(plot_comparison_chart(spends_df,"Spends"),use_container_width=True)
     st.plotly_chart(plot_comparison_chart(prospects_df,"Contributions"),use_container_width=True)
-
+    st.plotly_chart(plot_comparison_chart(efficiency_df,"Efficiency"),use_container_width=True)
+    
 def create_scenario_summary(scenario_dict):
     summary_rows = []
     actual_total_spends = scenario_dict.get('actual_total_spends'), 
@@ -137,6 +146,7 @@ def create_scenario_summary(scenario_dict):
     # st.write(actual_total_sales[0])
     # st.write(modified_total_spends[0])
     for channel_dict in scenario_dict['channels']:
+        # st.write(channel_dict['name'])
         name_mod = channel_name_formating(channel_dict['name'])
         summary_rows.append([name_mod,
                              channel_dict.get('actual_total_spends') * channel_dict.get('conversion_rate'),
@@ -170,35 +180,78 @@ def create_scenario_summary(scenario_dict):
                         #  scenario_dict.get('modified_total_spends') / scenario_dict.get('modified_total_sales')
                         ])
     
-    columns_index = pd.MultiIndex.from_product([[''],['Channel']], names=["first", "second"])
-    columns_index = columns_index.append(pd.MultiIndex.from_product([['Spends','Prospects',"Efficiency"],['Actual','Simulated']], names=["first", "second"]))
+    adf = pd.DataFrame(summary_rows)
+    # st.write(adf.columns)
     
-    return  pd.DataFrame(summary_rows, columns=columns_index)
+    adf.columns = ["1","2","3","4","5","6","7"]
+    adf.index = adf["1"].to_list() #["1","2","3","4","5","6","7","8","9","10","11","12","13","14"]
+    adf.drop(columns= ["1"],inplace= True)
+    # columns_index = pd.MultiIndex.from_product([[''],['Channel']], names=["",""])
+    # columns_index = columns_index.append(pd.MultiIndex.from_product([['Spends','Prospects',"Efficiency"],['Actual','Simulated']], names=["",""]))
+    columns_index = pd.MultiIndex.from_product([['Spends','Prospects',"Efficiency"],['Actual','Simulated']], names=["",""])
+    adf.columns = columns_index
+    return  adf # pd.DataFrame(summary_rows, columns=columns_index)
     
 
    
 def summary_df_to_worksheet(df, ws):
-    heading_fill = PatternFill(fill_type='solid',start_color='FF11B6BD',end_color='FF11B6BD')
+    heading_fill = PatternFill(fill_type='solid',start_color='FFFFFFFF',end_color='FFFFFFFF')
+
+    # Define border style
+    border_style = Border(
+        left=Side(border_style='thin', color='00000000'),
+        right=Side(border_style='thin', color='00000000'),
+        top=Side(border_style='thin', color='00000000'),
+        bottom=Side(border_style='thin', color='00000000')
+    )
+    number_format = '0.00'  
     for j,header in enumerate(df.columns.values):
         col = j + 1
         for i in range(1,3):
-            ws.cell(row=i, column=j + 1, value=header[i - 1]).font = Font(bold=True, color='FFFFFFFF')
+            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
+    # Apply borders to all cells, including empty cells
+    for row in ws.iter_rows():
+        for cell in row:
+            cell.border = border_style
+
     for i,row in enumerate(df.itertuples()):
         for j,value in enumerate(row):
             if j == 0:
                 continue
-            elif (j-2)%4 == 0 or (j-3)%4 == 0:
-                ws.cell(row=i+3, column = j, value=value)
-                # .number_format = '$#,##0.0' 
+            # elif (j-2)%4 == 0 or (j-3)%4 == 0:
+            #     ws.cell(row=i+3, column = j, value=value)
+            #     # cell.border = border_style
+            #     # .number_format = '$#,##0.0' 
+            #     if isinstance(value, (int, float)):
+            #         cell.number_format = number_format
             else:
                 ws.cell(row=i+3, column = j, value=value)
+                # cell.border = border_style
+                if isinstance(value, (int, float)):
+                    cell.number_format = '$#,##0.0'
+                    # cell.number_format = number_format
+    # Auto-size columns
+    for col in ws.columns:
+        max_length = 15
+        column = col[0].column_letter
+        for cell in col:
+            try:
+                if len(str(cell.value)) > max_length:
+                    max_length = len(cell.value)
+            except:
+                pass
+        adjusted_width = (max_length + 2)
+        ws.column_dimensions[column].width = adjusted_width
    
 from openpyxl.utils import get_column_letter
 from openpyxl.styles import Font, PatternFill
+from openpyxl.styles import PatternFill, Font, Alignment, Border, Side
 import logging
 
 def scenario_df_to_worksheet(df, ws):
@@ -274,8 +327,8 @@ def download_scenarios():
         scenario_df = pd.DataFrame(_spends).T
         scenario_df.columns = column_names
         ## write to sheet
-        ws = wb.create_sheet(scenario_name)
-        scenario_df_to_worksheet(scenario_df, ws)    
+        # ws = wb.create_sheet(scenario_name)
+        # scenario_df_to_worksheet(scenario_df, ws)    
         summary_rows.append(['Total',
                         scenario_dict.get('modified_total_spends') ,
                         scenario_dict.get('modified_total_sales'),
@@ -305,8 +358,8 @@ def disable_download_button():
 def transform(x):
     if x.name == ("",'Channel'):
         return x
-    elif x.name[0] == 'ROI' or x.name[0] == 'MROI':
-        return x.apply(lambda y : y if isinstance(y,str) else decimal_formater(format_numbers(y,include_indicator=False,n_decimals=4),n_decimals=4))
+    elif x.name[0] == 'Efficiency' or x.name[0] == 'MROI':
+        return x.apply(lambda y : y if isinstance(y,str) else decimal_formater(format_numbers(y,include_indicator=False,n_decimals=2),n_decimals=2))
     else:
         return x.apply(lambda y : y if isinstance(y,str) else format_numbers(y))
 
@@ -376,28 +429,40 @@ if auth_status == True:
         column_1, column_2,column_3 = st.columns((6,1,1))
         with column_1:
             st.header(selected_scenario)
-        with column_2:
-            st.button('Delete scenarios', on_click=delete_scenario)
         with column_3:
-            st.button('Load Scenario', on_click=load_scenario)
+            st.button('Delete scenarios', on_click=delete_scenario)
+        # with column_3:
+            # st.button('Load Scenario', on_click=load_scenario)
         
         selected_scenario_details = saved_scenarios[selected_scenario]
         
         pd.set_option('display.max_colwidth', 100)
-            
-        st.markdown(create_scenario_summary(selected_scenario_details).transform(transform).style.set_table_styles(
-    [{
-        'selector': 'th',
-        'props': [('background-color', '#11B6BD')]
-    },
-        {
-        'selector' : 'tr:nth-child(even)',
-        'props' : [('background-color', '#11B6BD')]
-        }
-        ]).to_html(),unsafe_allow_html=True)
+        # st.table(create_scenario_summary(selected_scenario_details))
+        # st.table(create_scenario_summary(selected_scenario_details).transform(transform))
+        adf = create_scenario_summary(selected_scenario_details).transform(transform)
+        # adf1 = adf[('Spends', 'Actual'),
+        #     ( 'Spends', 'Simulated'),
+        #     ( 'Prospects','Actual'),
+        #     ( 'Prospects', 'Simulated')].transform(transform)
+        # adf2 = adf[('Efficiency',    'Actual'),
+        #     ('Efficiency', 'Simulated')].round(2)
+        # st.write(adf.columns)
+        # adf = adf.set_index([('',   'Channel')])#, inplace=True)
+        # st.table(adf)
+        st.markdown(adf.style.set_table_styles(
+        [
+        #     {
+        #     'selector': 'th',
+        #     'props': [('background-color', '#1167bd')]
+        # },
+            # {
+            # 'selector' : 'tr:nth-child(even)',
+            # 'props' : [('background-color', '#11B6BD')]
+            # }
+            ]).to_html(),unsafe_allow_html=True)
         st.markdown("<br><br>", unsafe_allow_html=True)
         
-        with st.expander('Scenario comparison'):
+    with st.expander('Scenario comparison'):
             st.header("Scenario comparison")
             if len(scenarios_to_compare)== 0:
                 st.write("")

response_curves_model_quality_base.py

@@ -220,6 +220,7 @@ def response_curves(channel,chart_typ):
 
     # Update layout with titles
     fig.update_layout(
+        width=700, height=500,
         title=channel+' Response Curve',
         xaxis_title='Weekly Spends',
         yaxis_title='Prospects'

summary_df.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5edd69af2383d62f1f66e884c5dea34ee767b63b7a7498cc84d56f532b0bc309
+oid sha256:7eec7e117e96a7d10019a7e5cc889c769bdc4ae798cb0271c9870ee71e805b95
 size 1822

utilities.py

@@ -957,7 +957,23 @@ def channel_name_formating(channel_name):
         name_mod = name_mod.replace("Imp", "Spend")
     elif name_mod.lower().endswith(" clicks"):
         name_mod = name_mod.replace("Clicks", "Spend")
-    return name_mod
+    # st.write(channel_name)
+    key_dict = my_dict = {
+        "DisplayProspecting" :"Display Prospecting",
+        "CableTV" :"Cable TV",
+        "SocialProspecting": "Social Prospecting",
+        "Connected&OTTTV"  :"Connected & OTTTV",
+        "SocialRetargeting" : "Social Retargeting",
+        "DigitalPartners" :"Digital Partners",
+        "Audio" :"Audio",
+        "BroadcastTV": "Broadcast TV",
+        "SearchNon-brand": "Search Non-brand",
+        "Email" :"Email" ,
+        "SearchBrand": "Search Brand",
+        "DisplayRetargeting" :  "Display Retargeting" ,
+        "\xa0Video":"Video"
+    }
+    return key_dict[channel_name]
 
 
 def send_email(email, message):