使用位运算符 & 来判断一个数的最后一位是否为 0，如果是，则该数为偶数；否则，该数为奇数。使用数学方法 import mathdef check_odd_even(num):if int(num/2) == num/2:return"偶数"else:return"奇数"while 1: data = int(input("请输入一个数: ")) print("判断结果为：", check_odd_eve...
Checkifa numericvalue(int,float,etc.)is effectively zero.Args:-num:The numeric value to check.-tolerance:The tolerance levelforfloating-point comparisons.Returns:-bool:Trueifnum is effectively zero,False otherwise."""ifisinstance(num,int):# Integer checkreturnnum==0elifisinstance(num,float):# Fl...
l = [1, 2, 'hello', 'world'] # 列表中同时含有int和string类型的元素 l [1, 2, 'hello', 'world'] tup = ('jason', 22) # 元组中同时含有int和string类型的元素 tup ('jason', 22) 其次,我们必须掌握它们的区别。 列表是动态的,长度大小不固定,可以随意地增加、删减或者改变元素(mutable)。
# prepare dataX = series.valuesX = X.astype('float32')train_size = int(len(X) * 0.50)train, test = X[0:train_size], X[train_size:]接下来，我们可以时间步长遍历测试数据集。训练数据集存储在一个Python的list对象中，因为我们需要在每次迭代中很容易的附加一些观察值，Numpy数组连接...
ha = args.hash_algorithmprint("File hashing enabled with {} algorithm".format(ha))ifnotargs.log:print("Log file not defined. Will write to stdout") 当组合成一个脚本并在命令行中使用-h参数执行时,上述代码将提供以下输出: 如此所示,-h标志显示了脚本帮助信息,由argparse自动生成,以及--hash-algorit...
if__name__ =='__main__': parser = argparse.ArgumentParser( description=__description__, epilog="Developed by {} on {}".format(", ".join(__authors__), __date__) ) parser.add_argument('EVIDENCE_FILE',help="Path to evidence file") ...
# Check if camera opened successfully ifnotcap.isOpened(): print("Unable to open camera") exit() # Initialize Mediapipe Hands object withmp_hands.Hands(static_image_mode=False, max_num_hands=2, min_detection_confidence=0.5)ashands:
12),(3, 15),(5, 20),]print(sorted(some_tuples, key=lambda t: t[0] + t[1]))但bisect_left不支持：index = bisect_left(some_tuples, (4, 17), key=lambda t: t[0] + t[1]) #报错# Expectation: index = 3# Reality: "TypeError: '<' not supported between instances of 'int'...
defcheck_johansen(df): '''df是包含两个序列的dataframe''' #进行Johansen协整检验 johansen_test=coint_johansen(df.values,det_order=0,k_ar_diff=1) #判断是否存在协整关系 ifjohansen_test.lr1[0]>johansen_test.cvt[0,1]:#5%显著性水平 returnTrue else: returnFalse statsmodels库的coint函数返回三个...
def change_dtypes(col_int, col_float, df): ''' AIM -> Changing dtypes to save memory INPUT -> List of column names (int, float), df OUTPUT -> updated df with smaller memory --- ''' df[col_int] = df[col_int].astype('int32') df[col_float] = df[...