下面是一个示例代码: defget_unique_elements(lst):unique_elements=[]forelementinlst:ifelementnotinunique_elements:unique_elements.append(element)returnunique_elements original_list=[1,2,3,2,1,4,5,4]unique_elements=get_unique_elements(original_list)print(unique_elements) 1. 2. 3. 4. 5. 6....
1. 遍历完成后,集合中的元素即为不重复的元素。最后,我们需要将集合转换为列表并返回。可以使用list()函数来实现: unique_list=list(unique_set)returnunique_list 1. 2. 下面是完整的代码示例: defget_unique_elements(your_list):unique_set=set()foriteminyour_list:ifitemnotinunique_set:unique_set.add(...
lst = [1, 2, 2, 3, 4, 4, 5]unique_lst = list(Counter(lst).elements())```这些方法各...
我们可以使用numpy的unique和bincount函数来找到出现次数最多的元素。下面是代码示例: import numpy as np def most_frequent_element(lst): unique_elements, counts = np.unique(lst, return_counts=True) most_frequent = unique_elements[np.argmax(counts)] return most_frequent 例子: lst = [1, 2, 3, ...
第一种方法：使用 set()set() 函数可以将列表转换为一个集合。集合（set）是一个无序的不重复元素...
方法2:使用一个列表推导式(list comprehension)从一个列表中删除重复值。 def remove_duplicates(original): unique = [] [unique.append(n) for n in original if n not in unique] return(unique) print(remove_duplicates([1, 2, 3, 1, 7])) ...
pythonunique_moments = list(set(moments))2.分割字符串 朋友圈中经常会出现包含多个标签或关键词的字符串，这时候我们可以使用Python的split()函数来将字符串分割成单个元素。pythontags = moment.find_element_by_class_name('weui-desktop-moment__tags').text.split()3.提取关键词 如果我们需要从一段文字中...
1. Creating a List To conjure a list into being: # A list of mystical elements elements = ['Earth', 'Air', 'Fire', 'Water'] 2. Appending to a List To append a new element to the end of a list: elements.append('Aether') 3. Inserting into a List To insert an element at a ...
>>> c = Counter('abcdeabcdabcaba')#count elements from a string| | >>> c.most_common(3)#three most common elements| [('a', 5), ('b', 4), ('c', 3)]| >>> sorted(c)#list all unique elements| ['a','b','c','d','e']| >>>''.join(sorted(c.elements()))#list ...
clear() # reset all counts list(c) # list unique elements set(c) # convert to a set dict(c) # convert to a regular dictionary c.items() # convert to a list of (elem, cnt) pairs Counter(dict(list_of_pairs)) # convert from a list of (elem, cnt) pairs c.most_common()[:-...