6],[7,8]], dtype=np.float64) # Elementwise sum; both produce the array print(x + y) print(np.add(x, y)) # Elementwise difference; both produce the array print(x - y) print(np.subtract(x, y)) # Elementwise product; both produce the array print(x * y) print...
implement a difference function, which subtracts one list from another and returns the result. It should remove all values from lista, which are present in listb. defarray_diff(a, b):return [xfor xin aif xnotin b] Take 2 stringss1ands2including only letters fromatoz. Return a newsorted...
self.update(kwds)defsubtract(*args, **kwds):#删除'''Like dict.update() but subtracts counts instead of replacing them. Counts can be reduced below zero. Both the inputs and outputs are allowed to contain zero and negative counts. Source can be an iterable, a dictionary, or another Coun...
复制 # extract data (X_train, y_train), (X_test, y_test) = cifar10.load_data() #split train into train and validation sets X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.15, stratify=np.array (y_train), random_state=42) # perform one h...
156 157 Source can be an iterable, a dictionary, or another Counter instance. 158 159 >>> c = Counter('which') 160 >>> c.subtract('witch') # subtract elements from another iterable 161 >>> c.subtract(Counter('watch')) # subtract elements from another counter 162 >>> c['h'] #...
Sometimes we need to examine whether any or all elements of an array fulfill some logical condition. 有时我们需要检查数组的任何或所有元素是否满足某种逻辑条件。 Let’s generate a small one d array and check two things. 让我们生成一个小的一维数组并检查两件事。 First, if any of the entries ...
# main.py def calculate(operation, a, b): if operation == 'add': return a + b elif operation == 'subtract': return a - b # 其他操作... def main(): a = int(input("Enter first number: ")) b = int(input("Enter second number: ")) operation = input("Enter operation (add/...
both produce the array # [[-4.0 -4.0] # [-4.0 -4.0]] print x - y print np.subtract(x, y) # Elementwise product; both produce the array # [[ 5.0 12.0] # [21.0 32.0]] print x * y print np.multiply(x, y) # Elementwise division; both produce the array # [[ 0.2 0.33333333...
subtract sum swapaxes swaplevel tail take to_clipboard to_csv to_dict to_excel to_feather to_gbq to_hdf to_html to_json to_latex to_markdown to_numpy to_parquet to_period to_pickle to_records to_sql to_stata to_string to_timestamp to_xarray to_xml transform transpose truediv truncate ...
-= Subtracts the right operand from the left operand and stores the result in the left operand x -= y x = x - y *= Multiplies the right operand with the left operand and stores the result in the left operand x *= y x = x * y /= Divides the left operand by the right operand...