2024年10月28日
摘要：
`import pylab as plt import numpy as np ax=plt.axes(projection='3d') X = np.arange(-6, 6, 0.25) Y = np.arange(-6, 6, 0.25) X, Y = np.meshgrid(X, Y) Z 阅读全文
摘要：
`import pylab as plt import numpy as np x=np.linspace(-4,4,100); x,y=np.meshgrid(x,x) z=50*np.sin(x+y); ax=plt.axes(projection='3d') ax.plot_surface(x 阅读全文
摘要：
`import pylab as plt import numpy as np ax=plt.axes(projection='3d') #设置三维图形模式 z=np.linspace(-50, 50, 1000) x=z2*np.sin(z); y=z2*np.cos(z) plt.plot(x, 阅读全文
摘要：
`import pylab as plt import numpy as np plt.rc('text', usetex=True) #调用tex字库 y1=np.random.randint(2, 5, 6); y1=y1/sum(y1); plt.subplot(2, 2, 1); str=[ 阅读全文
摘要：
`import pandas as pd import pylab as plt plt.rc('font',family='SimHei') #用来正常显示中文标签 plt.rc('font',size=16) #设置显示字体大小 a=pd.read_excel("data2_52.xlsx",h 阅读全文
摘要：
`import pandas as pd import pylab as plt plt.rc('font',family='SimHei') #用来正常显示中文标签 plt.rc('font',size=16) #设置显示字体大小 a=pd.read_excel("data2_52.xlsx", 阅读全文
摘要：
`import numpy as np import sympy as sp a = np.identity(4) #单位矩阵的另一种写法 b = np.rot90(a) c = sp.Matrix(b) print('特征值为：', c.eigenvals()) print('特征向量为：\n', 阅读全文
摘要：
`import sympy as sp sp.var('x1,x2') s=sp.solve([x12+x22-1,x1-x2],[x1,x2]) print(s) print("学号：3005")` 阅读全文
摘要：
`import sympy as sp a, b, c, x=sp.symbols('a,b,c,x') x0=sp.solve(ax**2+bx+c, x) print(x0) print("学号：3005")` 阅读全文
摘要：
`from scipy.sparse.linalg import eigs import numpy as np a = np.array([[1, 2, 3], [2, 1, 3], [3, 3, 6]], dtype=float) #必须加float,否则出错 b, c = np.linalg. 阅读全文
摘要：
`from scipy.optimize import least_squares import numpy as np a=np.loadtxt('data2_47.txt') x0=a[0]; y0=a[1]; d=a[2] fx=lambda x: np.sqrt((x0-x[0])2+(y0 阅读全文
摘要：
`from scipy.integrate import quad def fun42(x, a, b): return ax**2+bx I1 = quad(fun42, 0, 1, args=(2, 1)) I2 = quad(fun42, 0, 1, args=(2, 10)) print(I 阅读全文
摘要：
`from scipy.optimize import fsolve, root fx = lambda x: [x[0]2+x[1]2-1, x[0]-x[1]] s1 = fsolve(fx, [1, 1]) s2 = root(fx, [1, 1]) print(s1,'\n',' '); p 阅读全文
摘要：
`from scipy.optimize import fsolve, root fx = lambda x: x980-5.01*x979+7.398x**978 -3.388x977-x3+5.01x**2-7.398x+3.388 x1 = fsolve(fx, 1.5, maxfev=400 阅读全文
摘要：
`import numpy as np a=np.random.rand(6,8) #生成6×8的[0,1)上均匀分布的随机数矩阵 np.savetxt("data2_43_1.txt", a) #存成以制表符分隔的文本文件 np.savetxt("data2_43_2.csv", a, delim 阅读全文
摘要：
`import pandas as pd import numpy as np a = pd.DataFrame(np.random.randint(1,6,(5,3)), index=['a', 'b', 'c', 'd', 'e'], columns=['one', 'two', 'three' 阅读全文
摘要：
`import pandas as pd import numpy as np d=pd.DataFrame(np.random.randint(1,6,(10,4)), columns=list("ABCD")) d1=d[:4] #获取前4行数据 d2=d[4:] #获取第5行以后的数据 dd= 阅读全文
摘要：
`with open('data2_2.txt') as fp: L1=[]; L2=[]; for line in fp: L1.append(len(line)) L2.append(len(line.strip())) #去掉换行符 data = [str(num)+'\t' for num 阅读全文
摘要：
`import pandas as pd a=pd.read_csv("data2_38_2.csv", usecols=range(1,5)) b=pd.read_excel("data2_38_3.xlsx", "Sheet2", usecols=range(1,5)) print("学号：30 阅读全文
摘要：
2.38.1 `import pandas as pd import numpy as np dates=pd.date_range(start='20191101', end='20191124', freq='D') a1=pd.DataFrame(np.random.randn(24,4), 阅读全文