{"id":972751,"date":"2024-12-27T05:51:12","date_gmt":"2024-12-26T21:51:12","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/972751.html"},"modified":"2024-12-27T05:51:14","modified_gmt":"2024-12-26T21:51:14","slug":"python%e5%a6%82%e4%bd%95%e8%af%bb%e5%8f%96%e5%88%97%e8%a1%a8%e7%9f%a9%e9%98%b5","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/972751.html","title":{"rendered":"python\u5982\u4f55\u8bfb\u53d6\u5217\u8868\u77e9\u9635"},"content":{"rendered":"

\"python\u5982\u4f55\u8bfb\u53d6\u5217\u8868\u77e9\u9635\"<\/p>\n

Python\u8bfb\u53d6\u5217\u8868\u77e9\u9635\u53ef\u4ee5\u901a\u8fc7\u7d22\u5f15\u8bbf\u95ee\u5143\u7d20\u3001\u4f7f\u7528\u5faa\u73af\u904d\u5386\u77e9\u9635\u3001\u5229\u7528NumPy\u5e93\u8fdb\u884c\u9ad8\u7ea7\u64cd\u4f5c\u3002<\/strong>\u5728Python\u4e2d\uff0c\u5217\u8868\u53ef\u4ee5\u7528\u6765\u8868\u793a\u77e9\u9635\u7ed3\u6784\u3002\u77e9\u9635\u662f\u4e00\u4e2a\u4e8c\u7ef4\u7684\u5217\u8868\uff0c\u901a\u5e38\u7531\u591a\u4e2a\u5217\u8868\u7ec4\u6210\uff0c\u6bcf\u4e2a\u5217\u8868\u4ee3\u8868\u77e9\u9635\u7684\u4e00\u884c\u3002\u901a\u8fc7\u7d22\u5f15\u64cd\u4f5c\uff0c\u53ef\u4ee5\u76f4\u63a5\u8bbf\u95ee\u548c\u4fee\u6539\u77e9\u9635\u4e2d\u7684\u7279\u5b9a\u5143\u7d20\u3002\u6b64\u5916\uff0c\u53ef\u4ee5\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u904d\u5386\u6574\u4e2a\u77e9\u9635\u3002\u4e3a\u4e86\u66f4\u9ad8\u6548\u548c\u65b9\u4fbf\u5730\u5904\u7406\u77e9\u9635\uff0cNumPy\u5e93\u63d0\u4f9b\u4e86\u4e13\u95e8\u7684\u6570\u636e\u7ed3\u6784\u548c\u51fd\u6570\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u7d22\u5f15\u8bbf\u95ee\u77e9\u9635\u5143\u7d20<\/p>\n<\/p>\n

Python\u4e2d\uff0c\u5217\u8868\u662f\u4e00\u4e2a\u53ef\u53d8\u7684\u6570\u636e\u7c7b\u578b\uff0c\u5141\u8bb8\u901a\u8fc7\u7d22\u5f15\u6765\u8bbf\u95ee\u548c\u4fee\u6539\u5176\u4e2d\u7684\u5143\u7d20\u3002\u5bf9\u4e8e\u77e9\u9635\u8fd9\u79cd\u4e8c\u7ef4\u5217\u8868\u7ed3\u6784\uff0c\u53ef\u4ee5\u901a\u8fc7\u4e24\u4e2a\u7d22\u5f15\u6765\u8bbf\u95ee\u7279\u5b9a\u7684\u5143\u7d20\u3002\u7b2c\u4e00\u4e2a\u7d22\u5f15\u7528\u4e8e\u9009\u62e9\u884c\uff0c\u7b2c\u4e8c\u4e2a\u7d22\u5f15\u7528\u4e8e\u9009\u62e9\u5217\u3002<\/p>\n<\/p>\n

matrix = [<\/p>\n
    [1, 2, 3],<\/p>\n
    [4, 5, 6],<\/p>\n
    [7, 8, 9]<\/p>\n
]<\/p>\n
\u8bbf\u95ee\u7b2c\u4e8c\u884c\u7b2c\u4e09\u5217\u7684\u5143\u7d20<\/strong><\/h2>\n
element = matrix[1][2]<\/p>\n
print(element)  # \u8f93\u51fa\uff1a6<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u5728\u4e0a\u8ff0\u4f8b\u5b50\u4e2d\uff0cmatrix[1][2]<\/code>\u8868\u793a\u8bbf\u95ee\u77e9\u9635\u7684\u7b2c\u4e8c\u884c\u7b2c\u4e09\u5217\u7684\u5143\u7d20\uff0c\u8f93\u51fa\u7ed3\u679c\u4e3a6\u3002<\/p>\n<\/p>\n
\u4e8c\u3001\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u904d\u5386\u77e9\u9635<\/p>\n<\/p>\n
\u904d\u5386\u77e9\u9635\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u901a\u5e38\u9700\u8981\u4f7f\u7528\u5d4c\u5957\u5faa\u73af\u3002\u5916\u5c42\u5faa\u73af\u7528\u4e8e\u8fed\u4ee3\u884c\uff0c\u5185\u5c42\u5faa\u73af\u7528\u4e8e\u8fed\u4ee3\u5217\u3002<\/p>\n<\/p>\n
for row in matrix:<\/p>\n
    for element in row:<\/p>\n
        print(element, end=' ')<\/p>\n
    print()<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e0a\u8ff0\u4ee3\u7801\u5c06\u9010\u884c\u8f93\u51fa\u77e9\u9635\u7684\u6240\u6709\u5143\u7d20\u3002\u5916\u5c42for<\/code>\u5faa\u73af\u904d\u5386\u6bcf\u4e00\u884c\uff0c\u5185\u5c42for<\/code>\u5faa\u73af\u904d\u5386\u884c\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\uff0c\u5e76\u5728\u4e00\u884c\u4e2d\u8f93\u51fa\u3002<\/p>\n<\/p>\n
\u4e09\u3001\u4f7f\u7528NumPy\u5e93\u8fdb\u884c\u9ad8\u7ea7\u64cd\u4f5c<\/p>\n<\/p>\n
NumPy\u662fPython\u4e2d\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u4e13\u95e8\u7528\u4e8e\u5904\u7406\u6570\u7ec4\u548c\u77e9\u9635\u8fd0\u7b97\u3002\u5b83\u63d0\u4f9b\u4e86\u66f4\u9ad8\u6548\u548c\u7b80\u6d01\u7684\u77e9\u9635\u64cd\u4f5c\u65b9\u6cd5\u3002<\/p>\n<\/p>\n
    \n
  1. \u5b89\u88c5NumPy\u5e93<\/strong><\/li>\n<\/ol>\n
    \u5728\u4f7f\u7528NumPy\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86\u8be5\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n
    pip install numpy<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u521b\u5efaNumPy\u6570\u7ec4<\/strong><\/li>\n<\/ol>\n
      NumPy\u63d0\u4f9b\u4e86array()<\/code>\u51fd\u6570\uff0c\u53ef\u4ee5\u5c06Python\u5217\u8868\u8f6c\u6362\u4e3aNumPy\u6570\u7ec4\u3002<\/p>\n<\/p>\n
      import numpy as np<\/p>\n
      matrix = np.array([<\/p>\n
          [1, 2, 3],<\/p>\n
          [4, 5, 6],<\/p>\n
          [7, 8, 9]<\/p>\n
      ])<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      1. \u8bbf\u95eeNumPy\u6570\u7ec4\u5143\u7d20<\/strong><\/li>\n<\/ol>\n
        \u4e0e\u666e\u901aPython\u5217\u8868\u7c7b\u4f3c\uff0c\u53ef\u4ee5\u901a\u8fc7\u7d22\u5f15\u8bbf\u95eeNumPy\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\u3002<\/p>\n<\/p>\n
        element = matrix[1, 2]<\/p>\n
        print(element)  # \u8f93\u51fa\uff1a6<\/p>\n
        <\/code><\/pre>\n<\/p>\n
        NumPy\u5141\u8bb8\u4f7f\u7528\u9017\u53f7\u5206\u9694\u7684\u7d22\u5f15\u6765\u8bbf\u95ee\u591a\u7ef4\u6570\u7ec4\u4e2d\u7684\u5143\u7d20\uff0c\u8fd9\u4f7f\u5f97\u4ee3\u7801\u66f4\u52a0\u7b80\u6d01\u3002<\/p>\n<\/p>\n
          \n
        1. \u77e9\u9635\u8fd0\u7b97<\/strong><\/li>\n<\/ol>\n
          NumPy\u652f\u6301\u591a\u79cd\u77e9\u9635\u8fd0\u7b97\uff0c\u5982\u77e9\u9635\u52a0\u6cd5\u3001\u51cf\u6cd5\u3001\u4e58\u6cd5\u4ee5\u53ca\u8f6c\u7f6e\u7b49\u3002<\/p>\n<\/p>\n
          # \u77e9\u9635\u52a0\u6cd5<\/p>\n
          matrix2 = np.array([<\/p>\n
              [9, 8, 7],<\/p>\n
              [6, 5, 4],<\/p>\n
              [3, 2, 1]<\/p>\n
          ])<\/p>\n
          result = matrix + matrix2<\/p>\n
          print(result)<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4e0a\u8ff0\u4ee3\u7801\u5c06\u4e24\u4e2a\u77e9\u9635\u76f8\u52a0\uff0c\u5e76\u8f93\u51fa\u7ed3\u679c\u77e9\u9635\u3002<\/p>\n<\/p>\n
          \u56db\u3001\u77e9\u9635\u8f6c\u7f6e\u4e0e\u5207\u7247\u64cd\u4f5c<\/p>\n<\/p>\n
            \n
          1. \u77e9\u9635\u8f6c\u7f6e<\/strong><\/li>\n<\/ol>\n
            \u8f6c\u7f6e\u64cd\u4f5c\u5c06\u77e9\u9635\u7684\u884c\u548c\u5217\u8fdb\u884c\u4e92\u6362\u3002\u5728NumPy\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528transpose()<\/code>\u65b9\u6cd5\u6216.T<\/code>\u5c5e\u6027\u8fdb\u884c\u8f6c\u7f6e\u3002<\/p>\n<\/p>\n
            transposed_matrix = matrix.T<\/p>\n
            print(transposed_matrix)<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            1. \u77e9\u9635\u5207\u7247<\/strong><\/li>\n<\/ol>\n
              NumPy\u652f\u6301\u5bf9\u6570\u7ec4\u8fdb\u884c\u5207\u7247\u64cd\u4f5c\uff0c\u53ef\u4ee5\u65b9\u4fbf\u5730\u63d0\u53d6\u5b50\u77e9\u9635\u3002<\/p>\n<\/p>\n
              sub_matrix = matrix[0:2, 1:3]<\/p>\n
              print(sub_matrix)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u4e0a\u8ff0\u4ee3\u7801\u63d0\u53d6\u4e86\u77e9\u9635\u7684\u524d\u4e24\u884c\u548c\u7b2c2\u5230\u7b2c3\u5217\u7ec4\u6210\u7684\u5b50\u77e9\u9635\u3002<\/p>\n<\/p>\n
              \u4e94\u3001\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u5904\u7406\u77e9\u9635<\/p>\n<\/p>\n
              \u5217\u8868\u63a8\u5bfc\u5f0f\u662fPython\u4e2d\u7684\u4e00\u79cd\u7b80\u6d01\u7684\u8bed\u6cd5\uff0c\u53ef\u4ee5\u7528\u4e8e\u521b\u5efa\u548c\u64cd\u4f5c\u5217\u8868\u3002\u5bf9\u4e8e\u77e9\u9635\u8fd9\u79cd\u4e8c\u7ef4\u5217\u8868\u7ed3\u6784\uff0c\u5217\u8868\u63a8\u5bfc\u5f0f\u4e5f\u540c\u6837\u9002\u7528\u3002<\/p>\n<\/p>\n
              # \u5c06\u77e9\u9635\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\u4e58\u4ee52<\/p>\n
              doubled_matrix = [[element * 2 for element in row] for row in matrix]<\/p>\n
              print(doubled_matrix)<\/p>\n
              <\/code><\/pre>\n<\/p>\n
              \u5728\u4e0a\u8ff0\u4ee3\u7801\u4e2d\uff0c\u4f7f\u7528\u5217\u8868\u63a8\u5bfc\u5f0f\u5bf9\u77e9\u9635\u7684\u6bcf\u4e2a\u5143\u7d20\u8fdb\u884c\u64cd\u4f5c\uff0c\u5e76\u5c06\u7ed3\u679c\u5b58\u50a8\u5728\u65b0\u7684\u77e9\u9635\u4e2d\u3002<\/p>\n<\/p>\n
              \u516d\u3001\u5904\u7406\u5927\u89c4\u6a21\u77e9\u9635\u6570\u636e<\/p>\n<\/p>\n
              \u5f53\u5904\u7406\u5927\u89c4\u6a21\u77e9\u9635\u6570\u636e\u65f6\uff0c\u4f7f\u7528NumPy\u5e93\u53ef\u4ee5\u663e\u8457\u63d0\u9ad8\u6027\u80fd\u3002NumPy\u7684\u5e95\u5c42\u5b9e\u73b0\u4f7f\u7528\u4e86\u9ad8\u6548\u7684C\u548cFortran\u4ee3\u7801\uff0c\u5bf9\u5927\u89c4\u6a21\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\u65f6\u901f\u5ea6\u66f4\u5feb\u3002<\/p>\n<\/p>\n
                \n
              1. \u751f\u6210\u5927\u89c4\u6a21\u77e9\u9635<\/strong><\/li>\n<\/ol>\n
                NumPy\u63d0\u4f9b\u4e86\u591a\u79cd\u51fd\u6570\u7528\u4e8e\u751f\u6210\u5927\u89c4\u6a21\u77e9\u9635\uff0c\u5982zeros()<\/code>\u3001ones()<\/code>\u3001random()<\/code>\u7b49\u3002<\/p>\n<\/p>\n
                # \u751f\u6210\u4e00\u4e2a1000x1000\u7684\u968f\u673a\u77e9\u9635<\/p>\n
                large_matrix = np.random.random((1000, 1000))<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                  \n
                1. \u5927\u89c4\u6a21\u77e9\u9635\u8fd0\u7b97<\/strong><\/li>\n<\/ol>\n
                  \u5bf9\u4e8e\u5927\u89c4\u6a21\u77e9\u9635\uff0cNumPy\u63d0\u4f9b\u7684\u77e9\u9635\u8fd0\u7b97\u51fd\u6570\u80fd\u591f\u5145\u5206\u5229\u7528\u5e95\u5c42\u7684\u4f18\u5316\u7b97\u6cd5\uff0c\u5904\u7406\u901f\u5ea6\u8fdc\u5feb\u4e8e\u7eafPython\u5b9e\u73b0\u3002<\/p>\n<\/p>\n
                  # \u8ba1\u7b97\u77e9\u9635\u7684\u884c\u548c<\/p>\n
                  row_sums = np.sum(large_matrix, axis=1)<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u4e0a\u8ff0\u4ee3\u7801\u8ba1\u7b97\u4e86\u5927\u89c4\u6a21\u77e9\u9635\u7684\u6bcf\u4e00\u884c\u7684\u548c\u3002<\/p>\n<\/p>\n
                  \u4e03\u3001\u77e9\u9635\u7684\u5b9e\u9645\u5e94\u7528<\/p>\n<\/p>\n
                  \u77e9\u9635\u5728\u79d1\u5b66\u8ba1\u7b97\u3001\u6570\u636e\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60<\/a>\u7b49\u9886\u57df\u6709\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u5728\u8fd9\u4e9b\u5e94\u7528\u4e2d\uff0c\u77e9\u9635\u901a\u5e38\u7528\u4e8e\u8868\u793a\u6570\u636e\u96c6\u3001\u8ba1\u7b97\u53d8\u6362\u4ee5\u53ca\u89e3\u51b3\u65b9\u7a0b\u7ec4\u7b49\u3002<\/p>\n<\/p>\n
                    \n
                  1. \u6570\u636e\u5206\u6790<\/strong><\/li>\n<\/ol>\n
                    \u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u77e9\u9635\u5e38\u7528\u4e8e\u8868\u793a\u6570\u636e\u96c6\uff0c\u6bcf\u4e00\u884c\u4ee3\u8868\u4e00\u4e2a\u6570\u636e\u6837\u672c\uff0c\u6bcf\u4e00\u5217\u4ee3\u8868\u4e00\u4e2a\u7279\u5f81\u3002NumPy\u548cPandas\u5e93\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u80fd\u529b\uff0c\u53ef\u4ee5\u5bf9\u6570\u636e\u96c6\u8fdb\u884c\u5404\u79cd\u5206\u6790\u548c\u64cd\u4f5c\u3002<\/p>\n<\/p>\n
                      \n
                    1. \u673a\u5668\u5b66\u4e60<\/strong><\/li>\n<\/ol>\n
                      \u5728\u673a\u5668\u5b66\u4e60\u4e2d\uff0c\u77e9\u9635\u8fd0\u7b97\u662f\u8bb8\u591a\u7b97\u6cd5\u7684\u6838\u5fc3\u3002\u4f8b\u5982\uff0c\u7ebf\u6027\u56de\u5f52\u4e2d\u7684\u53c2\u6570\u4f30\u8ba1\u3001\u795e\u7ecf\u7f51\u7edc\u4e2d\u7684\u6743\u91cd\u66f4\u65b0\u7b49\uff0c\u90fd\u4f9d\u8d56\u4e8e\u77e9\u9635\u8fd0\u7b97\u3002<\/p>\n<\/p>\n
                        \n
                      1. \u56fe\u50cf\u5904\u7406<\/strong><\/li>\n<\/ol>\n
                        \u56fe\u50cf\u53ef\u4ee5\u770b\u4f5c\u662f\u4e00\u4e2a\u50cf\u7d20\u77e9\u9635\uff0c\u5176\u4e2d\u6bcf\u4e2a\u50cf\u7d20\u70b9\u5305\u542b\u989c\u8272\u4fe1\u606f\u3002\u56fe\u50cf\u5904\u7406\u64cd\u4f5c\u901a\u5e38\u901a\u8fc7\u5bf9\u56fe\u50cf\u77e9\u9635\u8fdb\u884c\u64cd\u4f5c\u5b9e\u73b0\uff0c\u5982\u6ee4\u6ce2\u3001\u65cb\u8f6c\u3001\u7f29\u653e\u7b49\u3002<\/p>\n<\/p>\n
                        \u7efc\u4e0a\u6240\u8ff0\uff0cPython\u901a\u8fc7\u7d22\u5f15\u3001\u5faa\u73af\u4ee5\u53caNumPy\u5e93\u7b49\u591a\u79cd\u65b9\u5f0f\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u5217\u8868\u77e9\u9635\u8bfb\u53d6\u548c\u64cd\u4f5c\u529f\u80fd\u3002\u8fd9\u4e9b\u6280\u672f\u4e0d\u4ec5\u9002\u7528\u4e8e\u7b80\u5355\u7684\u77e9\u9635\u8bfb\u53d6\uff0c\u4e5f\u80fd\u6ee1\u8db3\u590d\u6742\u7684\u77e9\u9635\u8fd0\u7b97\u9700\u6c42\uff0c\u662f\u79d1\u5b66\u8ba1\u7b97\u548c\u6570\u636e\u5206\u6790\u9886\u57df\u7684\u91cd\u8981\u5de5\u5177\u3002<\/p>\n<\/p>\n
                        \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                         \u5982\u4f55\u5728Python\u4e2d\u521b\u5efa\u4e00\u4e2a\u5217\u8868\u77e9\u9635\uff1f<\/strong>
                        \u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528\u5d4c\u5957\u5217\u8868\u6765\u521b\u5efa\u4e00\u4e2a\u5217\u8868\u77e9\u9635\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u4ee3\u7801\u521b\u5efa\u4e00\u4e2a2×3\u7684\u77e9\u9635\uff1a  <\/p>\n
                        matrix = [[1, 2, 3], [4, 5, 6]]\n<\/code><\/pre>\n
                        \u8fd9\u91cc\uff0cmatrix<\/code>\u662f\u4e00\u4e2a\u5305\u542b\u4e24\u4e2a\u5b50\u5217\u8868\u7684\u5217\u8868\uff0c\u6bcf\u4e2a\u5b50\u5217\u8868\u53ef\u4ee5\u770b\u4f5c\u662f\u77e9\u9635\u7684\u4e00\u884c\u3002<\/p>\n
                        \u5982\u4f55\u8bbf\u95ee\u5217\u8868\u77e9\u9635\u4e2d\u7684\u7279\u5b9a\u5143\u7d20\uff1f<\/strong>
                        \u8981\u8bbf\u95ee\u5217\u8868\u77e9\u9635\u4e2d\u7684\u7279\u5b9a\u5143\u7d20\uff0c\u53ef\u4ee5\u4f7f\u7528\u7d22\u5f15\u3002\u4f8b\u5982\uff0c\u8981\u8bbf\u95ee\u4e0a\u9762\u77e9\u9635\u4e2d\u7684\u5143\u7d204\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a  <\/p>\n
                        element = matrix[1][0]  # \u8bbf\u95ee\u7b2c\u4e8c\u884c\u7b2c\u4e00\u5217\u7684\u5143\u7d20\n<\/code><\/pre>\n
                        \u5728Python\u4e2d\uff0c\u7d22\u5f15\u4ece0\u5f00\u59cb\uff0c\u56e0\u6b64matrix[1]<\/code>\u4ee3\u8868\u7b2c\u4e8c\u884c\uff0cmatrix[1][0]<\/code>\u5219\u4ee3\u8868\u8be5\u884c\u7684\u7b2c\u4e00\u4e2a\u5143\u7d20\u3002<\/p>\n
                        \u5982\u4f55\u5728Python\u4e2d\u904d\u5386\u5217\u8868\u77e9\u9635\u7684\u6bcf\u4e00\u884c\u548c\u6bcf\u4e00\u5217\uff1f<\/strong>
                        \u53ef\u4ee5\u4f7f\u7528\u5d4c\u5957\u7684for\u5faa\u73af\u6765\u904d\u5386\u5217\u8868\u77e9\u9635\u7684\u6bcf\u4e00\u884c\u548c\u6bcf\u4e00\u5217\u3002\u4f8b\u5982\uff1a  <\/p>\n
                        for row in matrix:\n    for element in row:\n        print(element)\n<\/code><\/pre>\n
                        \u8fd9\u6bb5\u4ee3\u7801\u5c06\u9010\u884c\u6253\u5370\u51fa\u77e9\u9635\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\uff0c\u5141\u8bb8\u60a8\u5bf9\u77e9\u9635\u4e2d\u7684\u6240\u6709\u6570\u636e\u8fdb\u884c\u64cd\u4f5c\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"Python\u8bfb\u53d6\u5217\u8868\u77e9\u9635\u53ef\u4ee5\u901a\u8fc7\u7d22\u5f15\u8bbf\u95ee\u5143\u7d20\u3001\u4f7f\u7528\u5faa\u73af\u904d\u5386\u77e9\u9635\u3001\u5229\u7528NumPy\u5e93\u8fdb\u884c\u9ad8\u7ea7\u64cd\u4f5c\u3002\u5728Python\u4e2d […]","protected":false},"author":3,"featured_media":972752,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/972751"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=972751"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/972751\/revisions"}],"predecessor-version":[{"id":972753,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/972751\/revisions\/972753"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/972752"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=972751"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=972751"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=972751"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}