可以通过split方法将字符串分割成单词列表,再使用count函数统计某个单词出现的次数: text = "This is a sample text with several words" words = text.split() count_is = words.count("is") print(f"'is'出现了{count_is}次") 这个例子中,单词“is”出现了1次。 3、统计元素频率 在列表操作中,常常...
print(counter["Python"]) # 输出: 2 这里,Counter类统计了每个单词出现的次数,我们可以方便地获取"Python"的出现次数。 使用字典 对于更复杂的统计需求,可以使用字典进行自定义统计: text = "Python is an amazing language. Python is popular." words = text.split() frequency = {} for word in words: ...
lst.append("")else: lst.append(word_i) new_string="".join(lst).split()returnnew_string src='/tmp/sample.txt'dic={} with open(src,'r') as f:#f.readlines()forlineinf: words_list=line.lower().split()forwordinwords_list:#str in listword = makekey(word)#return listforwordsinwo...
print("The file " + filename + " has about " + str(num_words) + " words.")filenames = ['alice.txt', 'siddhartha.txt', 'moby dick.txt', 'little_women.txt']for filename in filenames:count_words(filename) # 确保使用下划线调用函数 ```--- ### **关键修改说明** ### **1...
currentWORD=sentences[wordIDX]ifcurrentWORDnotinwordLIST: wordLIST.append(currentWORD) fid.close()print('==>> totalFrameNUM:', totalFrameNUM)print('==>> Max_sentence_NUM:', Max_sentence_NUM)print('==>> total word num:', len(wordLIST))print('==>> BBox NUM:', BBox_validateNUM)for...
python from collections import Counter words = ["apple", "banana", "apple", "orange", "banana", "apple"] word_counts = Counter(words) print(word_counts) # 输出: Counter({'apple': 3, 'banana': 2, 'orange': 1}) print(word_counts["apple"]) # 输出: 3 4. 自定义count函数 你...
words = text.split()这将把文本按照空格分割成一个单词列表。第三步：计数 现在，我们已经得到了单词列表，接下来就可以统计文本中每个单词出现的次数了。可以使用 Python 中的字典来保存单词和频率的对应关系。代码如下：word_count = {} for word in words:if word not in word_count:word_count[word] = ...
if k not in stop_words: print (k,v) 运行结果 以上,是利用python中自身的数据结构做的处理,下面利用python库做处理。 使用counter计算词频 1,导入相关的库,同样是需要去掉停用词的,并且去除前10的词语及对应的词频 from collections import Counter
javaRDD(); JavaRDD<String> words = lines.flatMap(s -> Arrays.asList(SPACE.split(s)).iterator()); JavaPairRDD<String, Integer> ones = words.mapToPair(s -> new Tuple2<>(s, 1)); JavaPairRDD<String, Integer> counts = ones.reduceByKey((i1, i2) -> i1 + i2); List<Tuple2...
word_counts = {word: words.count(word) for word in set(words)} print(word_counts) 在这个例子中,word_counts将是一个字典,包含每个单词及其出现的次数。例如: {'python': 3, 'is': 3, 'great': 1, 'dynamic': 1, 'easy': 1, 'to': 1, 'learn': 1} ...