AI代码解释 """Find the minimum of three values."""number1=int(input('Enter first integer: '))number2=int(input('Enter second integer: '))number3=int(input('Enter third integer: '))minimum=number1ifnumber2<minimum:minimum=number2ifnumber3<minimum:minimum=number3print('Minimum value is',...
下面这种写法叫做链式赋值,先把20赋值给b,再把b赋值给a,相当于a=20、b=20。这种语法虽然是合法的,但是一般不建议使用,尽量一行代码就只包含一个操作。 a=b=20 1. 下面这种写法叫做多元赋值,相当于把10赋值给a,20赋值给b。这种赋值方式可以完成两个变量的交换。 a,b=10,20#交换变量a,b=b,aprint(a,b)...
range(65, 85))), 'values': np.random.uniform(size=20) })# 排序取值ordered_df = df.sort_values(by='values')my_range = range(1, len(df.index)+1)# 创建图表plt.stem(ordered_df['values'])plt.xticks(my_range, ordered_df['group'])# 显示plt....
[range(int(len(amplitude)/2))] # Exclude sampling frequency tpCount = len(amplitude) values = np.arange(int(tpCount/2)) timePeriod = tpCount/samplingFrequency frequencies = values/timePeriod # Frequency domain representation axis[3].set_title('Fourier transform depicting the frequency components...
x = (i for i in range(10)) Iterator Iterator is like range(11), compare to list = [0,1,...,10] all data is stored in memory. Iterator only generates values from looping through the object. # to get iterator from range function ...
Unit Root Test Thenullhypothesisofthe Augmented Dickey-Fuller is that there is a unit root,withthe alternative that there is no unit root.That is to say the bigger the p-value the more reason we assert that there is a unit root''' def testStationarity(ts): dftest = adfuller(ts) # ...
dataset=createDataSet() centroids, cluster= kmeans(dataset, 2)print('质心为:%s'%centroids)print('集群为:%s'%cluster)foriinrange(len(dataset)): plt.scatter(dataset[i][0],dataset[i][1], marker ='o',color ='green', s = 40 ,label ='原始点')#记号形状 颜色 点的大小 设置标签forjin...
importpandasaspd# 从列表创建分类Seriescategories=pd.Series(['a','b','c','a','b'],dtype='category')print("基本分类数据:\n",categories) 1. 2. 3. 4. 5. 输出: 基本分类数据: 0 a 1 b 2 c 3 a 4 b dtype: category Categories (3, object): ['a', 'b', 'c'] ...
Convert a number or string to an integer, or return 0 if no arguments are given. If x is floating point, the conversion truncates towards zero. If x is outside the integer range, the function returns a long instead. If x is not a number or if base is given, then x must be a ...
p = plt.plot(df1[:i].index, df1[:i].values)#note it only returns the dataset, up to the point i foriinrange(0,4): p[i].set_color(color[i])#set the colour of each curveimport matplotlib.animation as ani animator = ani.FuncAnimation(fig, buildmebarchart, interval =100) ...