11 2024 档案
摘要：import pandas as pd import matplotlib.pyplot as plt import scipy.stats as stats 读取 Excel 文件中的数据 data = pd.read_excel('9.3.xlsx') # 将 'your_file.xlsx'
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摘要：import pandas as pd import scipy.stats as stats data = pd.read_excel('9.2.xlsx') data_values = data.values.flatten().tolist() statistic, p_value = sta
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摘要：loan_amount = 600000 - 200000 月利率 monthly_interest_rate = 0.0036 贷款期限（月） loan_term_months = 30 * 12 每月还款额 = 贷款本金×月利率×(1 + 月利率)^n÷((1 + 月利率)^n - 1)，其中
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摘要：import numpy as np import matplotlib.pyplot as plt a = 1 - 0.2*(1/12) m = 1.109 * 10**5 w3 = 17.86 w4 = 22.99 X = [] Z = [] for k in np.arange(0, 0.87
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摘要：import numpy as np import matplotlib.pyplot as plt from scipy.integrate import solve_ivp plt.rcParams['text.usetex'] = False def model(t, y): f, df_dm
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摘要：import numpy as np from scipy.integrate import solve_ivp import matplotlib.pyplot as plt def differential_equations(t, z): x, y = z dx_dt = -x ** 3 -
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摘要：import numpy as np from scipy.interpolate import interp1d from scipy.integrate import quad import matplotlib.pyplot as plt g = lambda x: (3 * x ** 2 +
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摘要：import numpy as np from scipy.optimize import curve_fit, leastsq, least_squares import matplotlib.pyplot as plt def g(x, a, b): return 10 * a / (10 *
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摘要：import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import griddata def f(x, y): return (x2 - 2*x) * np.exp(-x2 - y**2 - x*y) x_
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摘要：import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import interp1d, CubicSpline T = np.array([700, 720, 740, 760, 780]) V = np.
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