# 需要导入模块: from pynlpl.statistics import FrequencyList [as 别名]# 或者: from pynlpl.statistics.FrequencyList importcount[as 别名]classSimpleLanguageModel:"""This is a simple unsmoothed language model. This class can both hold and compute the model."""def__init__(self, n=2, casesensi...
以下是一个扩展的示例,支持从用户输入读取数据: fromcollectionsimportCounter# 从用户输入获取数据user_input=input("请输入一组整数(用空格分隔):")data=list(map(int,user_input.split()))# 统计频率frequency=Counter(data)# 输出结果fornumber,countinfrequency.items():print(f"整数{number}出现的频率为:{co...
def count_word_frequency(text): # 初始化一个空字典来存储单词频率 word_frequency = {} # 将文本转换为小写并分割成单词列表 words = text.lower().split() # 遍历单词列表并计算频率 for word in words: # 去除标点符号 word = word.strip(".,?!-") # 如果单词已存在于字典中,则增加其频率;否则...
def spell_correction(sentence_list):max_edit_distance_dictionary= 3 prefix_length = 4 spellchecker = SymSpell(max_edit_distance_dictionary, prefix_length) dictionary_path = pkg_resources.resource_filename( "symspellpy", "frequency_dictionary_en_82_765.txt") bigram_path = pkg_reso...
text = text.lower() char_count = Counter(text) 如果你想要一个更详细的分析,你可以将结果保存到一个字典中,以便稍后进行更深入的分析或可视化。例如: frequency_dict = dict(char_count) 以上就是使用Python进行字符频率统计的基本步骤。你可以根据你的具体需求对这个程序进行修改和扩展。相关...
word, store the split word in a list as the first element inside a tuple. Store the frequency count of the word as an integer as the second element of the tuple. Create a tuple for every word in this fashion and store the tuples in a list called 'corpus', then return ...
In the numpy module, the unique() function gives the flexibility to find the frequency of each element of the list. import numpy as np List_numbers = [2, 4, 7, 8, 12, 4, 6, 7, 8, 91, 8] print(np.unique(List_numbers, return_counts=True)) The np.unique() function is used...
deffrequency(itemList):'返回列表中项的频率'counters={}#初始化计数器字典foriteminitemList:ifitemincounters:#item计数器已经存在counters[item]+=1#计数器加1else:#创建item计数器counters[item]=1#计数器初始化为1returncounters ★元组类型可以作为字典的键 ...
word_frequency_df = df.groupby(0).size().sort_values(ascending=False) word_frequency_df 最后将词频统计的结果保存为文件 # 将词频统计进行保存 word_frequency_df.to_excel('词频统计结果.xlsx') # 保存为excel文件 # word_frequency_df.to_csv('词频统计结果.xlsx') # 保存为csv文件 方法2:使用colle...
if(len(set(list)) == 1): #如果列表去重之后,只有一个元素,则这个元素就是这组数据的众数 return list[0] else:#列表去重之后有2个及以上元素 for i in list_set: # 遍历每一个list_set的元素,得到该元素何其对应的个数list.count(i) frequency_dict[i] = list.count(i) # 创建dict; new_dict...