Upload 10_Optimized_Result_Analysis.py

pages/10_Optimized_Result_Analysis.py

@@ -14,7 +14,15 @@ import plotly.express as px
 import numpy as np
 import plotly.graph_objects as go
 import pandas as pd
+from plotly.subplots import make_subplots
 
+def format_number(x):
+    if x >= 1_000_000:
+        return f'{x / 1_000_000:.2f}M'
+    elif x >= 1_000:
+        return f'{x / 1_000:.2f}K'
+    else:
+        return f'{x:.2f}'
 
 def summary_plot(data, x, y, title, text_column, color, format_as_percent=False, format_as_decimal=False):
     fig = px.bar(data, x=x, y=y, orientation='h',
@@ -96,6 +104,7 @@ spends_data=pd.read_excel('Overview_data_test.xlsx')
 
 with open('summary_df.pkl', 'rb') as file:
   summary_df_sorted = pickle.load(file)
+  #st.write(summary_df_sorted)
 
 selected_scenario= st.selectbox('Select Saved Scenarios',['S1','S2']) 
 
@@ -334,31 +343,75 @@ with st.expander("Return Forecast by Media Channel"):
 
     summary_df_sorted=summary_df_sorted.merge(effectiveness_df,left_on="Channel_name",right_on='Channel')
 
-    # st.dataframe(summary_df_sorted.head(2))
-    summary_df_sorted['Efficiency']=summary_df_sorted['ResponseMetricValue']/summary_df_sorted['Optimized_spend']
-# # # st.dataframe(summary_df_sorted.head(2))
-# st.dataframe(summary_df_sorted.head(2))
+    #
+    summary_df_sorted['Efficiency'] = summary_df_sorted['ResponseMetricValue'] / summary_df_sorted['Optimized_spend']
+    summary_df_sorted=summary_df_sorted.sort_values(by='Optimized_spend',ascending=True)
+    #st.dataframe(summary_df_sorted)
+
+    channel_colors = px.colors.qualitative.Plotly
+
+    fig = make_subplots(rows=1, cols=3, subplot_titles=('Optimized Spends', 'Effectiveness', 'Efficiency'), horizontal_spacing=0.05)
+
+    for i, channel in enumerate(summary_df_sorted['Channel_name'].unique()):
+        channel_df = summary_df_sorted[summary_df_sorted['Channel_name'] == channel]
+        channel_color = channel_colors[i % len(channel_colors)]
+
+        fig.add_trace(go.Bar(x=channel_df['Optimized_spend'],
+                            y=channel_df['Channel_name'],
+                            text=channel_df['Optimized_spend'].apply(format_number),
+                            marker_color=channel_color,
+                            orientation='h'), row=1, col=1)
+
+        fig.add_trace(go.Bar(x=channel_df['ResponseMetricValue'],
+                            y=channel_df['Channel_name'],
+                            text=channel_df['ResponseMetricValue'].apply(format_number),
+                            marker_color=channel_color,
+                            orientation='h', showlegend=False), row=1, col=2)
+
+        fig.add_trace(go.Bar(x=channel_df['Efficiency'],
+                            y=channel_df['Channel_name'],
+                            text=channel_df['Efficiency'].apply(format_number),
+                            marker_color=channel_color,
+                            orientation='h', showlegend=False), row=1, col=3)
+
+    fig.update_layout(
+        height=600,
+        width=900,
+        title='Media Channel Performance',
+        showlegend=False
+    )
+
+    fig.update_yaxes(showticklabels=False ,row=1, col=2 )
+    fig.update_yaxes(showticklabels=False, row=1, col=3)
+
+    fig.update_xaxes(showticklabels=False, row=1, col=1)
+    fig.update_xaxes(showticklabels=False, row=1, col=2)
+    fig.update_xaxes(showticklabels=False, row=1, col=3)
+
+
+    st.plotly_chart(fig, use_container_width=True)
+
 
-    columns= st.columns(3)
-    with columns[0]:
-        fig=summary_plot(summary_df_sorted, x='Optimized_spend', y='Channel_name', title='', text_column='Optimized_spend',color='Channel_name')
-        st.plotly_chart(fig,use_container_width=True)  
-    with columns[1]: 
+
+    # columns= st.columns(3)
+    # with columns[0]:
+    #     fig=summary_plot(summary_df_sorted, x='Optimized_spend', y='Channel_name', title='', text_column='Optimized_spend',color='Channel_name')
+    #     st.plotly_chart(fig,use_container_width=True)  
+    # with columns[1]: 
         
-        # effectiveness=(selected_metric.groupby(by=['MediaChannelName'])['ResponseMetricValue'].sum()).values
-        # effectiveness_df=pd.DataFrame({'Channel':st.session_state['raw_data']['MediaChannelName'].unique(),"ResponseMetricValue":effectiveness})
-        # # effectiveness.reset_index(inplace=True)
-        # # st.dataframe(effectiveness.head())
-        fig=summary_plot(summary_df_sorted, x='ResponseMetricValue', y='Channel_name', title='Effectiveness', text_column='ResponseMetricValue',color='Channel_name')
-        st.plotly_chart(fig,use_container_width=True)  
-
-    with columns[2]:
-        fig=summary_plot(summary_df_sorted, x='Efficiency', y='Channel_name', title='Efficiency', text_column='Efficiency',color='Channel_name',format_as_decimal=True)
-        st.plotly_chart(fig,use_container_width=True)
-
-import plotly.express as px
-import plotly.graph_objects as go
-from plotly.subplots import make_subplots
+    #     # effectiveness=(selected_metric.groupby(by=['MediaChannelName'])['ResponseMetricValue'].sum()).values
+    #     # effectiveness_df=pd.DataFrame({'Channel':st.session_state['raw_data']['MediaChannelName'].unique(),"ResponseMetricValue":effectiveness})
+    #     # # effectiveness.reset_index(inplace=True)
+    #     # # st.dataframe(effectiveness.head())
+
+
+    #     fig=summary_plot(summary_df_sorted, x='ResponseMetricValue', y='Channel_name', title='Effectiveness', text_column='ResponseMetricValue',color='Channel_name')
+    #     st.plotly_chart(fig,use_container_width=True)  
+
+    # with columns[2]:
+    #     fig=summary_plot(summary_df_sorted, x='Efficiency', y='Channel_name', title='Efficiency', text_column='Efficiency',color='Channel_name',format_as_decimal=True)
+    #     st.plotly_chart(fig,use_container_width=True)
+
 
 # Create figure with subplots
 # fig = make_subplots(rows=1, cols=2)