使用 numpy 按行连接不同大小的数组

Question

我设法使用 np.concatenate 按行加入了两个相同大小（即相同数量的列）的 csv 数据集。

combined = np.concatenate((price1,price2))

如何使用 numpy 按行连接两个不同大小的 csv 数据集（它们包含通用标题，但其中一个数据集有一个附加列）？

数据集 1 的标题：a、b、c、d、e、f、g、h、i、k

dataset2 的标题：a、b、c、d、e、f、g、h、i、j（分析不需要的附加列）、k

非常感谢。

Answer 1

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Answer 2

您可以使用np.delete删除多余的列然后使用np.concatenateheaders = list('abcdefghik')a = np.arange(len(headers)).reshape(1, -1)#Output: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])headers_2 = list('abcdefghijk')b = np.arange(len(headers_2)*2).reshape(2,-1)#Output: array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10],#       [11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21]])col_to_remove = headers_2.index('j')np.delete(b, col_to_remove, axis = 1) #note that this does not modify original array, returns a copy.#Output: array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8, 10],#       [11, 12, 13, 14, 15, 16, 17, 18, 19, 21]])result = np.concatenate((a, np.delete(b, col_to_remove, axis = 1)))#Output: array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9],#       [ 0,  1,  2,  3,  4,  5,  6,  7,  8, 10],#       [11, 12, 13, 14, 15, 16, 17, 18, 19, 21]])