j aime le riz blanc ici

main.py

@@ -18,6 +18,7 @@ tweetNumber = 100
 for i, tweet in enumerate(sntwitter.TwitterSearchScraper(query=construct_query(terms, negativeTerms, filters, negativeFilters)).get_items()):
     if i > tweetNumber:
         break
+
     if (tweet.lang in languages):
         dict = {'date': convert_date_str(
             tweet.date), 'tweet': tweet.rawContent}
@@ -27,7 +28,7 @@ for i, tweet in enumerate(sntwitter.TwitterSearchScraper(query=construct_query(t
 
     print(i/tweetNumber*100, " %")
 
-print(calc_frequency(table))
+print(calc_frequency(table["date"]))
 table = table.drop_duplicates(subset=["tweet"]).sort_values(by=["tweet"])
 
 table.to_json("output/twitter_data.json", orient="split")

src/functions.py

@@ -24,10 +24,14 @@ def convert_date_str(date):
             "%m/%d/%Y, %H:%M:%S"))
 
 
-def time_to_num(time_str):
-    hh, mm, ss = map(int, time_str.split(':'))
+def time_to_num(date):
+    clean_date = date[12:]
+
+    hh, mm, ss = int(clean_date[:2]), int(
+        clean_date[3:5]), int(clean_date[6:8])
     return ss + 60*(mm+60*hh)
 
 
 def calc_frequency(table_tweets):
-    return (abs(time_to_num(table_tweets["date"][0])-time_to_num(table_tweets["date"][-1]))/len(table_tweets["date"]))
+    table_tweets_list = list(table_tweets)
+    return (len(table_tweets)/abs(time_to_num(table_tweets_list[0])-time_to_num(table_tweets_list[-1])))