Теперь мне нужно обработать фрейм данных, выполнив следующие шаги:
1\Split the clean_question column of the row on the space character (), and assign to split_question.
2\Remove any words in split_question that are less than 6 characters long.
3\Set match_count to 0.
4\Loop through each word in split_question.
5\If the term occurs in terms_used, add 1 to match_count.
6\Add each word in split_question to terms_used using the add method on sets.
7\If the length of split_question is greater than 0, divide match_count by the length of split_question.
8\Append match_count to question_overlap.
На самом деле я написал такой код:
for index, series in jeopardy.iterrows():
match_count = 0
split_question = series.clean_question.split(' ')
for i in split_question:
if len(i) < 6:
split_question.remove(i)
for i in split_question:
if i in terms_used:
match_count += 1
terms_used.add(i)
if len(split_question) > 0 :
question_overlap.append(match_count/len(split_question))
Однако пример кода выводит другое среднее значение вместе с моим, например:
for i, row in jeopardy.iterrows():
split_question = row["clean_question"].split(" ")
split_question = [q for q in split_question if len(q) > 5]
match_count = 0
for word in split_question:
if word in terms_used:
match_count += 1
for word in split_question:
terms_used.add(word)
if len(split_question) > 0:
match_count /= len(split_question)
question_overlap.append(match_count)
Я потратил много времени, пытаясь исправить ошибку, но не нашел их. Пожалуйста, помогите указать, почему возникли проблемы. Спасибо!
Советы:
Среднее значение моего кода выше:
np.mean(question_overlap)
0.8031111701203273
Но правильный ответ:
0.69087373156719623