Changelog:

L89-92 and L109-113 introduced symbols, types and ef. values for them
L138-140 set condition for symbol and type
L182-191 add symbols, types to dict_data

pymt940/CSV2MentorBrd.py

@@ -107,8 +107,12 @@ class PaymentsProcessorBrd:
         payments_df = payments_df.loc[(payments_df['Suma'] < 0)]
         # print(payments_df['Debit (suma)'])
         payments_df['Amount'] = payments_df['Suma'].map(abs)
-
+        payments_df['symbols'] = ''
+        payments_df['types'] = ''
+        payments_df.loc[payments_df['symbols'] == '', 'symbols'] = 401
+        payments_df.loc[payments_df['types'] == '', 'types'] = 'ALIMENTARE CREDIT'
         self._calculate_payment_attributes(payments_df, mentor_names=mentor_names, day_slice=day_slice)
+        return payments_df
 
     def process_income_data(self, day_slice=(0, 2)):
         df_dict = get_partners(self.partner_data)
@@ -124,8 +128,12 @@ class PaymentsProcessorBrd:
         income_df = income_df.loc[(income_df['Suma'] > 0)]
         # print(income_df['Credit (suma)'])
         income_df['Amount'] = income_df['Suma']
-
+        income_df['symbols'] = ''
+        income_df['types'] = ''
+        income_df.loc[income_df['symbols'] == '', 'symbols'] = 411.01
+        income_df.loc[income_df['types'] == '', 'types'] = 'ALIMENTARE CREDIT'
         self._calculate_payment_attributes(income_df, mentor_names, day_slice=day_slice)
+        return income_df
 
     def _calculate_payment_attributes(self, df, mentor_names, day_slice=(0, 2)):
         # df['Amount'] = df['Credit'].map(str).apply(dig_it).map(abs)
@@ -158,6 +166,8 @@ class PaymentsProcessorBrd:
         cl_names = []
         obs = []
         counts = []
+        symbols = []
+        types = []
 
         for day in days:
             values = df.loc[df['day'] == day, 'Amount'].tolist()
@@ -183,6 +193,16 @@ class PaymentsProcessorBrd:
             count_of_value = value_counts[day]
             counts.append(count_of_value)
         self.counts = counts
+
+        for day in days:
+            acc_symbol = df.loc[df['day'] == day, 'symbols'].tolist()
+            symbols.append(acc_symbol)
+        self.symbol_list = {k: v for k, v in zip(days, symbols)}
+
+        for day in days:
+            type_ = df.loc[df['day'] == day, 'types'].tolist()
+            types.append(type_)
+        self.type_list = {k: v for k, v in zip(days, types)}
         self.unique_count = unique_count
 
     def to_dict(self, kind: str, month_back: int, std_client: str, acc_symbol: int):
@@ -206,9 +226,10 @@ class PaymentsProcessorBrd:
                     'clients': self.names_dict,
                     'cods': self.fiscal_code_dict,
                     'amount': self.trans_dict,
-                    'cont': acc_symbol,
+                    'cont': self.symbol_list,
                     'std_client': std_client,
-                    'obs': self.obs_dict
+                    'obs': self.obs_dict,
+                    'represents': self.type_list
                     }
             return data
 

pymt940/CSV2MentorOtp.py

@@ -107,8 +107,12 @@ class PaymentsProcessorOtp:
         payments_df = payments_df.loc[(payments_df['Suma Debit'] != '') & (payments_df['Suma Debit'] != '0.00')]
         # print(payments_df['Suma Debit'])
         payments_df['Amount'] = payments_df['Suma Debit'].map(str).apply(dig_it).map(abs)
-
+        payments_df['symbols'] = ''
+        payments_df['types'] = ''
+        payments_df.loc[payments_df['symbols'] == '', 'symbols'] = 401
+        payments_df.loc[payments_df['types'] == '', 'types'] = 'ALIMENTARE CREDIT'
         self._calculate_payment_attributes(payments_df, mentor_names=mentor_names, day_slice=day_slice)
+        return payments_df
 
     def process_income_data(self, day_slice=(0, 2)):
         df_dict = get_partners(self.partner_data)
@@ -144,8 +148,12 @@ class PaymentsProcessorOtp:
         income_df = income_df.loc[(income_df['Suma Credit'] != '') & (income_df['Suma Credit'] != 0.00)]
         # print(income_df['Suma Credit'])
         income_df['Amount'] = income_df['Suma Credit'].map(str).apply(dig_it)
-
+        income_df['symbols'] = ''
+        income_df['types'] = ''
+        income_df.loc[income_df['symbols'] == '', 'symbols'] = 411.01
+        income_df.loc[income_df['types'] == '', 'types'] = 'ALIMENTARE CREDIT'
         self._calculate_payment_attributes(income_df, mentor_names, day_slice=day_slice)
+        return income_df
 
     def _calculate_payment_attributes(self, df, mentor_names, day_slice=(0, 2)):
         # df['Amount'] = df['Credit'].map(str).apply(dig_it).map(abs)
@@ -178,6 +186,8 @@ class PaymentsProcessorOtp:
         cl_names = []
         obs = []
         counts = []
+        symbols = []
+        types = []
 
         for day in days:
             values = df.loc[df['day'] == day, 'Amount'].tolist()
@@ -203,6 +213,16 @@ class PaymentsProcessorOtp:
             count_of_value = value_counts[day]
             counts.append(count_of_value)
         self.counts = counts
+
+        for day in days:
+            acc_symbol = df.loc[df['day'] == day, 'symbols'].tolist()
+            symbols.append(acc_symbol)
+        self.symbol_list = {k: v for k, v in zip(days, symbols)}
+
+        for day in days:
+            type_ = df.loc[df['day'] == day, 'types'].tolist()
+            types.append(type_)
+        self.type_list = {k: v for k, v in zip(days, types)}
         self.unique_count = unique_count
 
     def to_dict(self, kind: str, month_back: int, std_client: str, acc_symbol: int):
@@ -226,8 +246,9 @@ class PaymentsProcessorOtp:
                     'clients': self.names_dict,
                     'cods': self.fiscal_code_dict,
                     'amount': self.trans_dict,
-                    'cont': acc_symbol,
+                    'cont': self.symbol_list,
                     'std_client': std_client,
-                    'obs': self.obs_dict
+                    'obs': self.obs_dict,
+                    'represents': self.type_list
                     }
             return data

pymt940/CSV2MentorRncb.py

@@ -84,8 +84,12 @@ class PaymentsProcessorRncb:
         payments_df = payments_df.loc[(payments_df['Debit (suma)'] != '') & (payments_df['Debit (suma)'] != '0.00')]
         # print(payments_df['Debit (suma)'])
         payments_df['Amount'] = payments_df['Debit (suma)'].map(str).apply(dig_it)
-
+        payments_df['symbols'] = ''
+        payments_df['types'] = ''
+        payments_df.loc[payments_df['symbols'] == '', 'symbols'] = 401
+        payments_df.loc[payments_df['types'] == '', 'types'] = 'ALIMENTARE CREDIT'
         self._calculate_payment_attributes(payments_df, mentor_names=mentor_names, day_slice=day_slice)
+        return payments_df
 
     def process_income_data(self, day_slice=(0, 2)):
         df_dict = get_partners(self.partner_data)
@@ -101,8 +105,12 @@ class PaymentsProcessorRncb:
         income_df = income_df.loc[(income_df['Credit (suma)'] != '') & (income_df['Credit (suma)'] != '0.00')]
         # print(income_df['Credit (suma)'])
         income_df['Amount'] = income_df['Credit (suma)'].map(str).apply(dig_it)
-
+        income_df['symbols'] = ''
+        income_df['types'] = ''
+        income_df.loc[income_df['symbols'] == '', 'symbols'] = 411.01
+        income_df.loc[income_df['types'] == '', 'types'] = 'ALIMENTARE CREDIT'
         self._calculate_payment_attributes(income_df, mentor_names, day_slice=day_slice)
+        return income_df
 
     def _calculate_payment_attributes(self, df, mentor_names, day_slice=(0, 2)):
         # df['Amount'] = df['Credit'].map(str).apply(dig_it).map(abs)
@@ -135,6 +143,8 @@ class PaymentsProcessorRncb:
         cl_names = []
         obs = []
         counts = []
+        symbols = []
+        types = []
 
         for day in days:
             values = df.loc[df['day'] == day, 'Amount'].tolist()
@@ -160,6 +170,16 @@ class PaymentsProcessorRncb:
             count_of_value = value_counts[day]
             counts.append(count_of_value)
         self.counts = counts
+
+        for day in days:
+            acc_symbol = df.loc[df['day'] == day, 'symbols'].tolist()
+            symbols.append(acc_symbol)
+        self.symbol_list = {k: v for k, v in zip(days, symbols)}
+
+        for day in days:
+            type_ = df.loc[df['day'] == day, 'types'].tolist()
+            types.append(type_)
+        self.type_list = {k: v for k, v in zip(days, types)}
         self.unique_count = unique_count
 
     def to_dict(self, kind: str, month_back: int, std_client: str, acc_symbol: int):
@@ -183,8 +203,9 @@ class PaymentsProcessorRncb:
                     'clients': self.names_dict,
                     'cods': self.fiscal_code_dict,
                     'amount': self.trans_dict,
-                    'cont': acc_symbol,
+                    'cont': self.symbol_list,
                     'std_client': std_client,
-                    'obs': self.obs_dict
+                    'obs': self.obs_dict,
+                    'represents': self.type_list
                     }
             return data