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例题2.38代码 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
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例题2.37代码 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), i 阅读全文
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例题2.36代码 import numpy as np a = np.eye(4) b = np.rot90(a) c, d = np.linalg.eig(b) print('特征值为：', c) print('特征向量为：\n', d) 阅读全文
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例题2.35代码 import numpy as np a = np.array([[3, 1], [1, 2], [1, 1]]) b = np.array([9, 8, 6]) x = np.linalg.pinv(a) @ b print(np.round(x, 4)) 阅读全文
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例题2.34代码 `` import numpy as np a = np.array([[3, 1], [1, 2]]) b = np.array([9, 8]) x1 = np.linalg.inv(a) @ b #第一种解法 上面语句中@表示矩阵乘法 x2 = np.linalg.solve( 阅读全文
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例题2.33代码 import numpy as np a = np.array([[0, 3, 4], [1, 6, 4]]) b = np.linalg.norm(a, axis=1) #求行向量2范数 c = np.linalg.norm(a, axis=0) #求列向量2范数 d = np. 阅读全文
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例题2.32代码 import numpy as np a = np.ones(4) b = np.arange(2, 10, 2) c = a @ b #a作为行向量,b作为列向量 d = np.arange(16).reshape(4,4) f = a @ d #a作为行向量 g = d @ a 阅读全文
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例题2.31代码 import numpy as np a = np.array([[0, 3, 4], [1, 6, 4]]) b = np.array([[1, 2, 3], [2, 1, 4]]) c = a / b #两个矩阵对应元素相除 d = np.array([2, 3, 2]) e 阅读全文
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例题2.30代码 import numpy as np a = np.array([[0, 3, 4], [1, 6, 4]]) b = a.sum() c1 = sum(a) c2 = np.sum(a, axis = 0) c3 = np.sum(a, axis = 1, keepdims = 阅读全文
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例题2.29代码 import numpy as np a = np.arange(16).reshape(4, 4) b = np.vsplit(a, 2) print('行分割: \n', b[0], '\n', b[1]) c = np.hsplit(a, 4) print('列分割：: \n 阅读全文