update

utils/portary_div_exposure.py

@@ -364,13 +364,13 @@ def from_id_get_tag(card_id_dict):
 
 
 def save_data_to_csv(user_portrait_dict,word_count_exposure):
-    all_data = []
+    all_data = [("user_portrait","tag_type","user_portrait_count","diary_exposure","answer_exposure","tractate_exposure")]
     for tag in user_portrait_dict:
         data_type = ""
         data_count = ""
-        diary_exposure = 0
-        answer_exposure = 0
-        tractate_exposure = 0
+        diary_exposure = ('diary', 0)
+        answer_exposure = ('answer', 0)
+        tractate_exposure = ('tractate', 0)
         user_portrait = user_portrait_dict.get(tag)
         if user_portrait:
             data_type, data_count = user_portrait
@@ -380,16 +380,16 @@ def save_data_to_csv(user_portrait_dict,word_count_exposure):
             answer_exposure = word_count_exposure["answer"].get(tag)
         if word_count_exposure["tractate"].get(tag):
             tractate_exposure = word_count_exposure["tractate"].get(tag)
-        all_data.append((data_type,data_count,diary_exposure,answer_exposure,tractate_exposure))
-        print(all_data[-1])
+        all_data.append((data_type,data_count,diary_exposure[1],answer_exposure[1],tractate_exposure[1]))
+        print(tag,all_data[-1])
 
 
-    # data = pd.DataFrame(all_data)
-    # s = datetime.datetime.now()
-    # ss = str(s)[0:19].replace(' ', '-').replace(':', '-')
-    # data.to_csv('%s%sall_s2.csv' % (d, monthly_doc_type_name), encoding='gb18030',
-    #             # columns=columns
-    #             )
+    data = pd.DataFrame(all_data)
+    s = datetime.datetime.now()
+    ss = str(s)[0:19].replace(' ', '-').replace(':', '-')
+    data.to_csv('data.csv', encoding='gb18030',
+                # columns=columns
+                )
 
 def parse_data():
     demands_num = {}