Add commentaries

convert.py

@@ -299,6 +299,7 @@ def parse_xlsx_file(data_filepath : Path):
                     new_date = datetime(*xlrd.xldate_as_tuple(date, workbook.datemode)).strftime("%Y-%m-%d")
                     list_date.append(new_date)
             else: 
+                # Create the series by parsing elements of each column
                 for element in range(0, len(worksheet.col_values(index))):
                     if element == 0: 
                         code_serie = worksheet.col_values(index)[element]
@@ -331,12 +332,15 @@ def parse_xlsx_file_total(data_filepath : Path):
             if index == 0:
                 for element in range(1, len(worksheet.col_values(index))):
                     date = worksheet.col_values(index)[element]
+                    # If date is in month, convert date and append it to list_date_months
                     if type(date) == float:
                         new_date = datetime(*xlrd.xldate_as_tuple(date, workbook.datemode)).strftime("%Y-%m-%d")
                         list_date_months.append(new_date)
+                    # If date is in quarter just append it to list_date_quarters
                     elif type(date) == str:
                         list_date_quarters.append(date)
             else: 
+                # Create the series by parsing elements of each column
                 for element in range(0, len(worksheet.col_values(index))):
                     if element == 0: 
                         code_serie = worksheet.col_values(index)[element]
@@ -353,11 +357,13 @@ def parse_xlsx_file_total(data_filepath : Path):
     for s in series.items():
         if s[0] not in new_series.keys():
             new_series[s[0]] = list()
+        # For monthly information
         if len(s[1]) >= 430:
             new_list_months = list(zip(list_date_months, s[1]))
             for element in new_list_months:
                 new_series[s[0]].append(element)
             new_series[s[0]].insert(0, ("PERIOD", "VALUE"))
+        # For quarter information
         else:
             new_list_quarters = list(zip(list_date_quarters, s[1]))
             for element in new_list_quarters:
@@ -382,12 +388,15 @@ def parse_xlsx_file_industry_sa_total(data_filepath : Path):
             if index == 0:
                 for element in range(1, len(worksheet.col_values(index))):
                     date = worksheet.col_values(index)[element]
+                    # If date is in month, convert date and append it to list_date_months
                     if type(date) == float:
                         new_date = datetime(*xlrd.xldate_as_tuple(date, workbook.datemode)).strftime("%Y-%m-%d")
                         list_date_months.append(new_date)
+                    # If date is in quarter just append it to list_date_quarters
                     elif type(date) == str:
                         list_date_quarters.append(date)
             else: 
+                # Create the series by parsing elements of each column
                 for element in range(0, len(worksheet.col_values(index))):
                     if element == 0: 
                         code_serie = worksheet.col_values(index)[element]
@@ -404,12 +413,14 @@ def parse_xlsx_file_industry_sa_total(data_filepath : Path):
     for s in series.items():
         if s[0] not in new_series.keys():
             new_series[s[0]] = list()
+        # For monthly information
         if len(s[1]) >= 430:
             new_list_months = list(zip(list_date_months, s[1]))
             for element in new_list_months:
                 new_series[s[0]].append(element)
             new_series[s[0]].insert(0, ("PERIOD", "VALUE"))
         else:
+            # For quarter information
             new_list_quarters = list(zip(list_date_quarters, s[1]))
             for element in new_list_quarters:
                 new_series[s[0]].append(element)