Merge branch 'customer_retention' into 'master'

Customer Retention

See merge request !16

User/forms.py

@@ -52,3 +52,7 @@ class MyForm3(forms.Form):
 
  class MyFormNew(forms.Form):
      inputdate = forms.DateField(widget=DateInput)
+
+#Customer Frequency
+class MyForm(forms.Form):
+ customerid  = forms.IntegerField(label='Enter Customer ID' )

User/urls.py

@@ -16,5 +16,6 @@ urlpatterns = [
     path('Forecasting/', responseapp_views.Forecasting),
     path('Result/', responseapp_views.Forecasting),
     path('Customer_Data/', responseapp_views.Customer_Data),
+    path('Customer_Frequency/', responseapp_views.Customer_Frequency),
     path('', admin.site.urls),
 ]
\ No newline at end of file

User/views.py

@@ -27,13 +27,14 @@ from statsmodels.tsa.stattools import adfuller
 from statsmodels.tsa.arima.model import ARIMA
 from pandas.tseries.offsets import DateOffset
 
+import warnings
+warnings.filterwarnings("ignore")
+
 # Start  CompanyHome
 def Homepage(request):
     return render(request, 'Admin/Homepage.html');
 # End  CompanyHome
 
-
-
 # Employee_Efficency
 def Employee_Data(request):
     data1 = pd.read_csv('Data/WorkHistory.csv')
@@ -214,6 +215,131 @@ def Customer_Data(request):
     context = {'d': arr}
     return render(request, 'Admin/Customer_Data.html',context);
 
+# Customer Frequency
+def Customer_Frequency(request):
+    if request.method == 'POST':
+        myForm = MyForm(request.POST)
+        if myForm.is_valid():
+
+            # Loading the data
+            df = pd.read_csv('Data/CustomerDataset.csv')
+
+            # Drop the missing data in `df`
+            df_data = df.dropna()
+
+            # Convert the date field, InvoiceDate to datetime object
+            df_data.InvoiceDate = pd.to_datetime(df_data.InvoiceDate)
+
+            ctm_bhvr_dt = df_data[(df_data.InvoiceDate < pd.Timestamp(2021, 10, 8))  # dataset End date
+                                  & (df_data.InvoiceDate >= pd.Timestamp(2021, 2, 12))].reset_index(
+                drop=True)  # dataset start date
+
+            ctm_next_quarter = df_data[(df_data.InvoiceDate < pd.Timestamp(2022, 4, 8))  # predict date Till
+                                       & (df_data.InvoiceDate >= pd.Timestamp(2021, 10, 8))].reset_index(
+                drop=True)  # dataset End date
+
+            # Get the distinct customers in the dataframe ctm_bhvr_dt
+            ctm_dt = pd.DataFrame(ctm_bhvr_dt['CustomerID'].unique())
+
+            # Rename the column to CustomerID.
+            ctm_dt.columns = ['CustomerID']
+
+            # Create a dataframe with CustomerID and customers first purchase
+            # date in the dataset ctm_next_quarter
+            ctm_1st_purchase_in_next_quarter = ctm_next_quarter.groupby('CustomerID').InvoiceDate.min().reset_index()
+            ctm_1st_purchase_in_next_quarter.columns = ['CustomerID', 'MinPurchaseDate']
+
+            # Create a dataframe with CustomerID and customers last purchase
+            # date in the dataset ctm_bhvr_dt
+            ctm_last_purchase_bhvr_dt = ctm_bhvr_dt.groupby('CustomerID').InvoiceDate.max().reset_index()
+            ctm_last_purchase_bhvr_dt.columns = ['CustomerID', 'MaxPurchaseDate']
+
+            # Merge two dataframes ctm_last_purchase_bhvr_dt and ctm_1st_purchase_in_next_quarter
+            ctm_purchase_dates = pd.merge(ctm_last_purchase_bhvr_dt, ctm_1st_purchase_in_next_quarter, on='CustomerID',
+                                          how='left')
+
+            # Get the difference in days from MinPurchaseDate and MaxPurchaseDate for each customer
+            ctm_purchase_dates['NextPurchaseDay'] = (
+                        ctm_purchase_dates['MinPurchaseDate'] - ctm_purchase_dates['MaxPurchaseDate']).dt.days
+
+            # Update the dataframe ctm_dt by merging it with the NextPurchaseDay column of the dataframe ctm_purchase_dates
+            ctm_dt = pd.merge(ctm_dt, ctm_purchase_dates[['CustomerID', 'NextPurchaseDay']], on='CustomerID',
+                              how='left')
+
+            ctm_dt = ctm_dt.fillna("Not Returning")
+
+            newloaded = ctm_dt.head()
+            print("-----------------Next Purchase Day-----------------")
+            # print(newloaded)
+
+            # Feature Engineering
+            # Recency
+            # Get the maximum purchase date of each customer and create a dataframe with it together with the customer's id.
+            ctm_max_purchase = ctm_bhvr_dt.groupby('CustomerID').InvoiceDate.max().reset_index()
+            ctm_max_purchase.columns = ['CustomerID', 'MaxPurchaseDate']
+
+            # Find the recency of each customer in days
+            ctm_max_purchase['Recency'] = (
+                        ctm_max_purchase['MaxPurchaseDate'].max() - ctm_max_purchase['MaxPurchaseDate']).dt.days
+
+            # Find the recency in days
+            ctm_max_purchase['Recency'] = (
+                        ctm_max_purchase['MaxPurchaseDate'].max() - ctm_max_purchase['MaxPurchaseDate']).dt.days
+
+            # Merge the dataframes ctm_dt and ctm_max_purchase[['CustomerID', 'Recency']] on the CustomerID column.
+            ctm_dt = pd.merge(ctm_dt, ctm_max_purchase[['CustomerID', 'Recency']], on='CustomerID')
+            Recency = ctm_dt.head()
+
+            # Frequency
+            # Get service booking counts for each user and create a dataframe with it
+            ctm_frequency = df_data.groupby('CustomerID').InvoiceDate.count().reset_index()
+            ctm_frequency.columns = ['CustomerID', 'Frequency']
+
+            # Update the dataframe ctm_dt by merging it with the dataframe ctm_frequency
+            ctm_dt = pd.merge(ctm_dt, ctm_frequency, on='CustomerID')
+            Frequency = ctm_dt.head()
+            print(Frequency)
+            # print(ctm_dt)
+            # Monetary Value/Revenue
+            # Create a new label, Revenue of each item bought
+
+
+            # customer value persontage
+
+
+        #     print(Frequency)
+
+            df2 = pd.read_csv('Data/CustomerDataset.csv')
+            ctm_dt = pd.merge(ctm_dt, df2, on='CustomerID')
+
+            # Merge the dataframe ctm_revenue with ctm_dt
+            # ctm_dt = pd.merge(ctm_dt, ctm_revenue, on='CustomerID')
+            # Monetary = ctm_dt.head()
+            # print(Monetary)
+
+            # Building Machine Learning Models
+
+
+            # get data of Entered Customer
+            customerid = myForm.cleaned_data['customerid']
+            dfz = ctm_dt[(ctm_dt["CustomerID"] == customerid)  ]
+            Frequency = dfz.head(1)
+
+            print(Frequency)
+
+            df = Frequency
+            # data = data.to_html()
+            json_records = df.reset_index().to_json(orient='records')
+            arr = []
+            arr = json.loads(json_records)
+            a = 2
+            form = MyForm()
+            context = { 'form': form, 'd': arr}
+            return render(request, 'Admin/Customer_Frequency.html', context)
+
+    else:
+        form = MyForm()
+    return render(request, 'Admin/Customer_Frequency.html', {'form': form});
 
 def AdminHome(request):
     return render(request,'Admin/AdminHome.html')

templates/Admin/Customer_Frequency.html

+{% extends 'Admin/Sidebar2.html' %}
+{% block content %}
+{% load widget_tweaks %}
+{%load static%}
+<head>
+        <!-- Font special for pages-->
+        <link href="https://fonts.googleapis.com/css?family=Open+Sans:300,300i,400,400i,600,600i,700,700i,800,800i" rel="stylesheet">
+
+        <!-- Main CSS-->
+
+        <link href="{% static "css/main.css" %}"rel="stylesheet" media="all">
+</head>
+<div class=" >
+    <div class="wrapper wrapper 0">
+
+        <div style="margin-left: 0px;" class="card card-5">
+
+            {% if messages %}
+<ul class="messages">
+    {% for message in messages %}
+    <li  {% if message.tags %} class=" {{ message.tags }} " {% endif %}> {{ message }} </li>
+    {% endfor %}
+</ul>
+{% endif %}
+
+            <div class="card-heading">
+                <h2 class="title mt-3" style="color: #02111f;"> PREDICT CUSTOMER RETENTION  </h2>
+            </div>
+
+       <div class="card-body">
+             <form action="/Admin/Customer_Frequency/" method="post">
+    {% csrf_token %}
+        <table class="table table-light">
+    {{form.as_table}}
+
+ </table>
+<input type="submit" value="PREDICT" class="btn btn--radius-2" style="background: #02111f;"/>
+
+
+</form>      <br><div class="text-right">
+  <input name="b_print" type="button" class="btn btn-print" onClick="printdiv('div_print');" value=" Print " style="background: #02111f;">
+ </div>
+                <br>
+
+
+            </div>
+
+       </div>
+   </div>
+         <div id="myDiv">
+                        <div id="div_print">
+                        <div class="card card-body printableArea">
+
+ <div role="alert"  >
+
+
+          <div class="container" style="overflow-x:auto;">
+
+                            <table class="table table-striped">
+
+                                <thead>
+                                    <tr>
+                                        <th> Customer ID </th>
+                                        <th> Customer Name </th>
+                                        <th> Vehicle Number </th>
+                                        <th> Vehicle Type </th>
+                                        <th> Next Return In </th>
+                                        <th> Return Frequency </th>
+
+                                    </tr>
+                                </thead>
+                                <tbody>
+                                    {% if d %}
+                                    {% for i in d %}
+                                    <tr>
+                                        <td> {{i.CustomerID}} </td>
+                                        <td> {{i.CustomerName}} </td>
+                                        <td> {{i.VehicleNo}} </td>
+                                        <td> {{i.VehicleType}} </td>
+                                        <td> {{i.NextPurchaseDay}} </td>
+                                        <td>{{i.Frequency}}</td>
+                                    </tr>
+                                    {% endfor %}
+                                    {% endif %}
+                                </tbody>
+                            </table>
+                        </div>
+
+</div>
+
+</div></div></div>
+
+
+
+     <script language="javascript">
+        function printdiv(printpage) {
+            var headstr = "<html><head><title></title></head><body>";
+            var footstr = "</body>";
+            var newstr = document.all.item(printpage).innerHTML;
+            var oldstr = document.body.innerHTML;
+            document.body.innerHTML = headstr + newstr + footstr;
+            window.print();
+            document.body.innerHTML = oldstr;
+            location.reload();
+            return false;
+        }
+    </script>
+
+    <div class="alert alert-primary fixed-bottom mb-0 text-center" style="background: #747578; border: none; color: white;" role="alert"  > © SERVPORT 2022   </div>
+
+</div>
+
+{% endblock content %}
+

templates/Admin/Sidebar2.html

@@ -187,7 +187,7 @@ body{
             <li><a style="text-decoration:none;" href="#"><i class="fas fa-eye"></i>  Highest Demand      </a>
             <li><a style="text-decoration:none;" href="/Admin/PurchaseHistory/"><i class="fas fa-cubes"></i>  Purchase History    </a>
             <li><a style="text-decoration:none;" href="/Admin/Customer_Data/"><i class="fas fa-user"></i>  Customer Data    </a>
-
+            <li><a style="text-decoration:none;" href="/Admin/Customer_Frequency/"><i class="fas fa-chart-bar"></i>  Customer Frequency   </a>
         </ul> 
 
     </div>