Update app.py

app.py

@@ -50,14 +50,14 @@ if uploaded_file is not None:
     summary['probability_alive'] = bgf.conditional_probability_alive(summary['frequency'], summary['recency'], summary['T'])
     #Predict future transaction for the next 300 days based on historical dataa
     t = 300
-    summary['pred_num_txn'] = round(bgf.conditional_expected_number_of_purchases_up_to_time(t, summary['frequency'], summary['recency'], summary['T']),2)
-    summary.sort_values(by='pred_num_txn', ascending=False).head(10).reset_index()
+    summary['Predicted No. of Transaction'] = round(bgf.conditional_expected_number_of_purchases_up_to_time(t, summary['frequency'], summary['recency'], summary['T']),2)
+    summary.sort_values(by='Predicted No. of Transaction', ascending=False).head(10).reset_index()
     #Hidden trends
-    ax = sns.countplot(x="pred_num_txn",data=summary)
-    plt.scatter(summary['probability_alive'],summary['pred_num_txn'])
+    ax = sns.countplot(x="Predicted No. of Transaction",data=summary)
+    plt.scatter(summary['probability_alive'],summary['Predicted No. of Transaction'])
     summary_correlation=summary.corr()
     summary1=summary
-    summary1['Active/Inactive']=summary1['pred_num_txn'].apply(lambda x:"ACTIVE" if x>=1 else "INACTIVE")
+    summary1['Active/Inactive']=summary1['Predicted No. of Transaction'].apply(lambda x:"ACTIVE" if x>=1 else "INACTIVE")
     selector=st.selectbox('Select User ID',summary1['CustomerID'],index=None,placeholder='Select Customer ID')
     summary2=summary1[['CustomerID','Active/Inactive']]
     if selector is not None:
@@ -65,9 +65,9 @@ if uploaded_file is not None:
         st.write('STATUS:',selected)
     trends= data_clv.groupby('CustomerID')['Quantity'].mean().reset_index()
     trends1= data_clv.groupby('CustomerID')['TotalSales'].mean().reset_index()
-    trends.at[0,'Quantity']=7.42
-    trends1.at[0,'TotalSales']=77.183
     summary1=summary1.merge(trends, how='left',on='CustomerID')
     summary1=summary1.merge(trends1, how='left',on='CustomerID')
+    summary1.drop('probability_alive',axis=1,inplace=True)
+    summary1.rename(columns={'Quantity':'Average Quantity','TotalSales':'Average Sales Value'})
     out=summary1.to_csv().encode('utf-8')
     st.download_button(label='DOWNLOAD RESULT',data=out, file_name='CLV_OUTPUT.csv',mime='text/csv')