Update app.py

app.py

@@ -191,6 +191,7 @@ def col_to_ints(df,columns_to_convert):
   return df
 
 def fill_missing_quarters(df, lob, acc, transaction):
+    filled = []
     print('accident',acc,'transaction',transaction)
     columns_to_convert = [acc,transaction]  # Only affect acc and transaction
 
@@ -201,9 +202,10 @@ def fill_missing_quarters(df, lob, acc, transaction):
     
     quarters = []
     start_year = 2017
+    end_year = 2022
     # df_temp = df.copy(deep=True)
     # df_temp = df_temp.dropna()
-    end_year = min(int(df[acc].max()[:4]), 2025)
+    end_year = min(int(df[acc].max()[:4]), 2022)
     print("the end year", end_year)
     print("safe and sound")
     for year in range(start_year, end_year+1):
@@ -227,7 +229,10 @@ def fill_missing_quarters(df, lob, acc, transaction):
                     l_missing_df[col] = 0.1
 
         if len(l_quarters) > 0 :
-            print(l,'was filled with the dates',l_quarters)
+            filled_warn = str(l)+' was filled with the dates '+str(l_quarters)
+            print(filled_warn)
+            filled.append(filled_warn)
+            
         l_missing_df[lob] = l
         missing_quarters.append(l_missing_df)
     
@@ -250,13 +255,14 @@ def fill_missing_quarters(df, lob, acc, transaction):
     # Print the filled quarters or a message if there are no missing quarters
     filled_quarters = filled_df[acc].unique()
     #filtered_quarters = [q for q in filled_quarters if q[:4] in [str(year1) for year1 in range(start_year, end_year + 1)]]
-    if False:#len(filtered_quarters) == 0:
-        print("No missing quarters between 2017-2022")
+    if len(filtered_quarters) == 0:
+        print("No missing quarters between 2017-"+str(end_year))
+        filled.append("No missing quarters between 2017-"+str(end_year))
     else:
         pass#print(filtered_quarters)
 
     #filled_df = filled_df[[acc, transaction] + [col for col in filled_df.columns if col not in [acc, transaction]]]
-    return filled_df
+    return filled_df,filled
 
 def drop_missing_rows(df, columns):
     #import sys
@@ -311,7 +317,7 @@ def filter_claims(df):
   print("Sum of Null beginning: ",df.isnull().sum())
   print("Sum of Null beginning 2: ",(df == '').sum())
   print(df.dtypes)
-
+  filled_warn = []
   global warnings
   warnings = []
   columns = []
@@ -334,7 +340,7 @@ def filter_claims(df):
   #temp.to_csv("gayassshit1.csv")
   #df.to_csv("before_filling.csv")
   #print("\n"*10,columns[0],min_col,max_col,"\n"*10)
-  df = fill_missing_quarters(df,columns[0],min_col,max_col)
+  df, filled_warn = fill_missing_quarters(df,columns[0],min_col,max_col)
   #df.to_csv("after_filling.csv")
   #print(columns[0],min_col,max_col)
   #temp = fill_missing_quarters(temp,columns[0],min_col,max_col)
@@ -371,12 +377,13 @@ def filter_claims(df):
   
   df = df.replace('nan',0)
   df = df.fillna({col: 0 for col in df.columns if col not in sublist})
-  return df,columns,temp
+  return df,columns,temp,filled_warn
 
 def filter_premiums(df):
   global warnings
   warnings = []
   columns = []
+  filled_warn = []
   # Find lob
   columns.append(get_lob(df))
   is_found(columns,"lob")
@@ -384,7 +391,7 @@ def filter_premiums(df):
     return None,None
   # Find quarter bracket
   columns.append(get_quarter_bracket(df))
-  df = fill_missing_quarters(df,columns[0],columns[-1],columns[-1])
+  df,filled_warn = fill_missing_quarters(df,columns[0],columns[-1],columns[-1])
   is_found(columns,"quarter")
   # Find premium earned
   columns.append(get_earned(df))
@@ -395,7 +402,7 @@ def filter_premiums(df):
   # Warn
   for i,w in enumerate(warnings):
     print(str(i+1)+'-',w)
-  return df,columns
+  return df,columns,filled_warn
 
 css_code='body{background-image:url("https://picsum.photos/seed/picsum/200/300");}'
 
@@ -469,6 +476,7 @@ def process(files,button):
                 # return zip_files([files.name]),'Success'+passe
             temp = None
             columns = []
+            filled_warn = []
             replacens = dict()
             print("Processing:", name)
             
@@ -484,7 +492,7 @@ def process(files,button):
 
             if "summ" in name:
                 print("Summary:")
-                df,columns = filter_premiums(df)
+                df,columns,filled_warn = filter_premiums(df)
                 if columns == None:
                     print(name,'has no LOB column')
                     print("--"*50)
@@ -493,7 +501,7 @@ def process(files,button):
                 altnames = get_alts('summ')
             else:
                 print("Claims:")
-                df,columns,temp = filter_claims(df)
+                df,columns,temp,filled_warn = filter_claims(df)
                 if columns == None:
                     print(name,'has no LOB column')
                     print("--"*50)
@@ -532,6 +540,7 @@ def process(files,button):
             sheet_data[name] = {
                 "Before columns": [old_olds],
                 "After columns": [columns, '00FF00'],
+                'Filled quarters':[filled_warn]
                 #"Warnings": [sheetwarnings]
             }