add merge value

eda/smart_rank/tag3_update_user_portrait_offline.py

+import functools
+import operator
+from collections import Counter
+
 from tool import get_tag3_user_log
 
 
+def merge_values(d1, d2):
+    ini_dict = [d1, d2]
+    return dict(functools.reduce(operator.add, map(Counter, ini_dict)))
+
+
 def update_tag3_user_portrait(cl_id):
     user_df = get_tag3_user_log(cl_id)
     if not user_df.empty:
-        user_df["first_solutions"] = list(zip(user_df["first_solutions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
-        user_df["second_solutions"] = list(zip(user_df["second_solutions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
-        user_df["first_demands"] = list(zip(user_df["first_demands"].apply(lambda x: x.split(",")), user_df["tag_score"]))
-        user_df["second_demands"] = list(zip(user_df["second_demands"].apply(lambda x: x.split(",")), user_df["tag_score"]))
-        user_df["first_positions"] = list(zip(user_df["first_positions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
-        user_df["second_positions"] = list(zip(user_df["second_positions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+        user_df["first_solutions"] = list(
+            zip(user_df["first_solutions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+        user_df["second_solutions"] = list(
+            zip(user_df["second_solutions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+        user_df["first_demands"] = list(
+            zip(user_df["first_demands"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+        user_df["second_demands"] = list(
+            zip(user_df["second_demands"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+        user_df["first_positions"] = list(
+            zip(user_df["first_positions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
+        user_df["second_positions"] = list(
+            zip(user_df["second_positions"].apply(lambda x: x.split(",")), user_df["tag_score"]))
         user_df["projects"] = list(zip(user_df["projects"].apply(lambda x: x.split(",")), user_df["tag_score"]))
 
-        user_df["first_solutions_dict"] = user_df["first_solutions"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
-        user_df["second_solutions_dict"] = user_df["second_solutions"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
-        user_df["first_demands_dict"] = user_df["first_demands"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
-        user_df["second_demands_dict"] = user_df["second_demands"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
-        user_df["first_positions_dict"] = user_df["first_positions"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
-        user_df["second_positions_dict"] = user_df["second_positions"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
+        user_df["first_solutions_dict"] = user_df["first_solutions"].apply(
+            lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
+        user_df["second_solutions_dict"] = user_df["second_solutions"].apply(
+            lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
+        user_df["first_demands_dict"] = user_df["first_demands"].apply(
+            lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
+        user_df["second_demands_dict"] = user_df["second_demands"].apply(
+            lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
+        user_df["first_positions_dict"] = user_df["first_positions"].apply(
+            lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
+        user_df["second_positions_dict"] = user_df["second_positions"].apply(
+            lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
         user_df["projects_dict"] = user_df["projects"].apply(lambda x: dict(zip(x[0], [x[1]] * len(x[0]))))
 
         first_solutions_list = user_df["first_solutions_dict"].tolist()
         second_solutions_list = user_df["second_solutions_dict"].tolist()
-        first_demands_list = user_df["first_demands_list"].tolist()
+        first_demands_list = user_df["first_demands_dict"].tolist()
         second_demands_list = user_df["second_demands_dict"].tolist()
         first_positions_list = user_df["first_positions_dict"].tolist()
         second_positions_list = user_df["second_positions_dict"].tolist()
         projects_list = user_df["projects_dict"].tolist()
 
         print(first_solutions_list)
-        print(second_solutions_list)
-        print(first_demands_list)
-        print(second_demands_list)
-        print(first_positions_list)
-        print(second_positions_list)
-        print(projects_list)
+        print(merge_values(first_solutions_list), "\n")
+
+        print(second_solutions_list, "\n")
+        print(merge_values(second_solutions_list))
+
+        print(first_demands_list, "\n")
+        print(merge_values(first_demands_list))
 
 
 if __name__ == "__main__":