2.1 使用`random.sample()函数 Python的random模块中的sample()函数可以从给定的序列中随机选择指定数量的元素。这是一个非常实用的功能,下面是一个简单的示例。 importrandom# 定义一个包含元素的列表my_list=[1,2,3,4,5,6,7,8,9,10]# 随机选择3个元素random_selection=random.sample(my_list,3)print("...
最后一步是使用random.sample方法从list中随机选择10个元素。代码如下: random_selection=random.sample(elements,10)print(random_selection) 1. 2. 在这段代码中,random.sample方法会从elements这个list中随机选择10个元素,并将结果存储在random_selection中。最后,我们使用print语句将随机选择的10个元素打印出来。 3....
sample(self, population, k) method of random.Random instance Chooses k unique random elements from a population sequence. Returns a new list containing elements from the population while leaving the original population unchanged. The resulting list is in selection order so that all sub-slices will ...
return seq[int(self.random() * len(seq))] # raises IndexError if seq is empty def shuffle(self, x, random=None): """x, random=random.random -> shuffle list x in place; return None. Optional arg random is a 0-argument function returning a random float in [0.0, 1.0); by default...
6. shuffle(x, random=None) method of random.Random instance Shuffle list x in place, and return None. # 给列表随机排序,俗称“洗牌”函数>>> random.shuffle([1,2,3,4,5,6])>>> a = [1,2,3,4,5,6]>>> random.shuffle(a)>>> a[4, 6, 5, 2, 3, 1]>>> random.shuffle(a)>...
The list should contain a randomly selection of the values from a specified list, and there should be 10 times higher possibility to select "apple" than the other two: importrandom mylist = ["apple","banana","cherry"] print(random.choices(mylist,weights = [10,1,1], k =14)) ...
seed(54) arr = [random.randint(0,100) for _ in range(10)] print("原始数据:", arr) selection_sort(arr) print("选择排序结果:", arr) # 输出结果 原始数据: [17, 56, 71, 38, 61, 62, 48, 28, 57, 42] 选择排序结果: [17, 28, 38, 42, 48, 56, 57, 61, 62, 71] 动画...
Chooses k unique random elements from a population sequence. Returns a new list containing elements from the population while leaving the original population unchanged. The resulting list is in selection order so that all sub-slices will also be valid random ...
y = y.values.ravel() X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42, stratify=y) scaler = MinMaxScaler() X_train = scaler.fit_transform(X_train) X_test = scaler.transform(X_test) ...
jinlist_1:sht_3[int(i),int(j)].color=(255,25,0)f()list_1=[]foriinrange(30):forjin...