Python 从词频创建ARFF

我有一些代码，可以给我一个单词列表，以及它们在文本中出现的频率，我希望它能让代码自动将前10个单词转换成ARFF

@关系字频率

@属性字串 @属性频率数字

排名前10位的数据及其频率

我正在努力解决如何用我当前的代码实现这一点

import re
import nltk

# Quran subset
filename = 'subsetQuran.txt'

# create list of lower case words
word_list = re.split('\s+', file(filename).read().lower())
print 'Words in text:', len(word_list)

word_list2 = [w.strip() for w in word_list if w.strip() not in nltk.corpus.stopwords.words('english')]



# create dictionary of word:frequency pairs
freq_dic = {}
# punctuation and numbers to be removed
punctuation = re.compile(r'[-.?!,":;()|0-9]') 
for word in word_list2:
    # remove punctuation marks
    word = punctuation.sub("", word)
    # form dictionary
    try: 
        freq_dic[word] += 1
    except: 
        freq_dic[word] = 1


print '-'*30

print "sorted by highest frequency first:"
# create list of (val, key) tuple pairs
freq_list2 = [(val, key) for key, val in freq_dic.items()]
# sort by val or frequency
freq_list2.sort(reverse=True)
freq_list3 = list(freq_list2)
# display result
for freq, word in freq_list2:
    print word, freq
f = open("wordfreq.txt", "w")
f.write( str(freq_list3) )
f.close()

---

任何帮助都是感激的，这样做的方式真的是折磨我的大脑

我希望你不介意稍微重写一下：

import re
import nltk
from collections import defaultdict

# Quran subset
filename = 'subsetQuran.txt'

# create list of lower case words
word_list = open(filename).read().lower().split()
print 'Words in text:', len(word_list)

# remove stopwords
word_list = [w for w in word_list if w not in nltk.corpus.stopwords.words('english')]

# create dictionary of word:frequency pairs
freq_dic = defaultdict(int)

# punctuation and numbers to be removed
punctuation = re.compile(r'[-.?!,":;()|0-9]') 
for word in word_list:
    # remove punctuation marks
    word = punctuation.sub("", word)
    # increment count for word
    freq_dic[word] += 1

print '-' * 30

print "sorted by highest frequency first:"
# create list of (frequency, word) tuple pairs
freq_list = [(freq, word) for word, freq in freq_dic.items()]

# sort by descending frequency
freq_list.sort(reverse=True)

# display result
for freq, word in freq_list:
    print word, freq

# write ARFF file for 10 most common words
f = open("wordfreq.txt", "w")
f.write("@RELATION wordfrequencies\n")
f.write("@ATTRIBUTE word string\n")
f.write("@ATTRIBUTE frequency numeric\n")
f.write("@DATA\n")
for freq, word in freq_list[ : 10]:
    f.write("'%s',%d\n" % (word, freq))
f.close()

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不确定这是否有帮助，但它可能会告诉你如何为所有单词制作一个arff，然后将其编辑为只取前10名？