{"id":977832,"date":"2024-12-27T06:32:50","date_gmt":"2024-12-26T22:32:50","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/977832.html"},"modified":"2024-12-27T06:32:53","modified_gmt":"2024-12-26T22:32:53","slug":"python%e7%94%bb%e5%9b%be%e5%a6%82%e4%bd%95%e5%ba%94%e7%94%a8list","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/977832.html","title":{"rendered":"python\u753b\u56fe\u5982\u4f55\u5e94\u7528list"},"content":{"rendered":"

\"python\u753b\u56fe\u5982\u4f55\u5e94\u7528list\"<\/p>\n

\u5728Python\u753b\u56fe\u65f6\uff0clist\u53ef\u4ee5\u7528\u4e8e\u5b58\u50a8\u6570\u636e\u3001\u7b80\u5316\u4ee3\u7801\u3001\u63d0\u9ad8\u7075\u6d3b\u6027<\/strong>\u3002\u5176\u4e2d\uff0c\u5b58\u50a8\u6570\u636e<\/strong>\u8fd9\u4e00\u70b9\u5c24\u4e3a\u91cd\u8981\uff0clist\u53ef\u4ee5\u65b9\u4fbf\u5730\u5b58\u50a8\u548c\u64cd\u4f5c\u5927\u89c4\u6a21\u7684\u6570\u636e\u96c6\uff0c\u4f7f\u5f97\u6570\u636e\u7684\u53ef\u89c6\u5316\u66f4\u4e3a\u4fbf\u6377\u3002\u901a\u8fc7\u5c06\u6570\u636e\u5b58\u50a8\u5728list\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u5bf9\u6570\u636e\u8fdb\u884c\u8fed\u4ee3\u3001\u6392\u5e8f\u548c\u5207\u7247\u7b49\u64cd\u4f5c\uff0c\u8fd9\u4e0d\u4ec5\u63d0\u9ad8\u4e86\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\uff0c\u8fd8\u5927\u5927\u589e\u5f3a\u4e86\u4ee3\u7801\u7684\u7075\u6d3b\u6027\u548c\u6269\u5c55\u6027\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u8ba8\u8bba\u5982\u4f55\u5728Python\u753b\u56fe\u65f6\u5e94\u7528list\uff0c\u4ee5\u53calist\u7684\u5404\u79cd\u4f18\u52bf\u548c\u7528\u6cd5\u3002<\/p>\n<\/p>\n

\u4e00\u3001LIST\u5728\u6570\u636e\u5b58\u50a8\u4e2d\u7684\u4f5c\u7528<\/p>\n<\/p>\n

\u5728\u6570\u636e\u53ef\u89c6\u5316\u4e2d\uff0clist\u662f\u7528\u4e8e\u5b58\u50a8\u6570\u636e\u7684\u57fa\u672c\u7ed3\u6784\u4e4b\u4e00\u3002\u5b83\u80fd\u591f\u5b58\u50a8\u591a\u79cd\u7c7b\u578b\u7684\u6570\u636e\uff0c\u5305\u62ec\u6574\u6570\u3001\u6d6e\u70b9\u6570\u3001\u5b57\u7b26\u4e32\uff0c\u751a\u81f3\u662f\u5176\u4ed6list\u3002\u8fd9\u4f7f\u5f97list\u6210\u4e3aPython\u4e2d\u8fdb\u884c\u6570\u636e\u64cd\u4f5c\u7684\u4e00\u4e2a\u5f3a\u5927\u5de5\u5177\u3002<\/p>\n<\/p>\n

    \n
  1. \u6570\u636e\u5b58\u50a8\u4e0e\u64cd\u4f5c<\/li>\n<\/ol>\n

    \u5728\u7ed8\u56fe\u65f6\uff0c\u6211\u4eec\u5e38\u5e38\u9700\u8981\u5904\u7406\u5927\u91cf\u7684\u6570\u636e\u3002list\u4f7f\u5f97\u6570\u636e\u7684\u5b58\u50a8\u53d8\u5f97\u975e\u5e38\u7b80\u5355\u3002\u6211\u4eec\u53ef\u4ee5\u5c06\u6570\u636e\u96c6\u5b58\u50a8\u5728list\u4e2d\uff0c\u7136\u540e\u5bf9\u5176\u8fdb\u884c\u5404\u79cd\u64cd\u4f5c\uff0c\u4f8b\u5982\u6392\u5e8f\u3001\u7b5b\u9009\u3001\u8ba1\u7b97\u7b49\u3002\u4e3e\u4e2a\u4f8b\u5b50\uff0c\u5982\u679c\u6211\u4eec\u6709\u4e00\u7ec4\u8868\u793a\u80a1\u7968\u4ef7\u683c\u7684\u6570\u636e\uff0c\u6211\u4eec\u53ef\u4ee5\u5c06\u5176\u5b58\u50a8\u5728\u4e00\u4e2alist\u4e2d\uff0c\u7136\u540e\u4f7f\u7528Python\u7684\u5185\u7f6e\u51fd\u6570\u5bf9\u5176\u8fdb\u884c\u6392\u5e8f\uff0c\u4ee5\u4fbf\u5206\u6790\u4ef7\u683c\u7684\u53d8\u5316\u8d8b\u52bf\u3002<\/p>\n<\/p>\n

      \n
    1. \u6570\u636e\u7684\u52a8\u6001\u64cd\u4f5c<\/li>\n<\/ol>\n

      list\u7684\u53e6\u4e00\u4e2a\u4f18\u52bf\u5728\u4e8e\u5176\u52a8\u6001\u6027\u3002\u4e0e\u6570\u7ec4\u4e0d\u540c\uff0clist\u7684\u5927\u5c0f\u662f\u52a8\u6001\u53ef\u53d8\u7684\uff0c\u8fd9\u610f\u5473\u7740\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u9700\u8981\u6dfb\u52a0\u6216\u5220\u9664\u5143\u7d20\uff0c\u800c\u65e0\u9700\u62c5\u5fc3\u5185\u5b58\u7ba1\u7406\u95ee\u9898\u3002\u8fd9\u79cd\u52a8\u6001\u7279\u6027\u4f7f\u5f97list\u7279\u522b\u9002\u5408\u7528\u4e8e\u5904\u7406\u52a8\u6001\u6570\u636e\u96c6\uff0c\u4f8b\u5982\u5b9e\u65f6\u66f4\u65b0\u7684\u4f20\u611f\u5668\u6570\u636e\u3002<\/p>\n<\/p>\n

      \u4e8c\u3001LIST\u5728\u7b80\u5316\u4ee3\u7801\u4e2d\u7684\u5e94\u7528<\/p>\n<\/p>\n

      \u4f7f\u7528list\u53ef\u4ee5\u663e\u8457\u7b80\u5316\u4ee3\u7801\uff0c\u51cf\u5c11\u91cd\u590d\uff0c\u63d0\u9ad8\u4ee3\u7801\u7684\u53ef\u8bfb\u6027\u548c\u7ef4\u62a4\u6027\u3002\u6211\u4eec\u53ef\u4ee5\u5229\u7528list\u7684\u7279\u6027\uff0c\u901a\u8fc7\u7b80\u5355\u800c\u4f18\u96c5\u7684\u8bed\u6cd5\u6765\u5b9e\u73b0\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u548c\u7ed8\u56fe\u4efb\u52a1\u3002<\/p>\n<\/p>\n

        \n
      1. \u5faa\u73af\u4e0e\u8fed\u4ee3<\/li>\n<\/ol>\n

        list\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u4e0efor\u5faa\u73af\u7ed3\u5408\u4f7f\u7528\uff0c\u4ee5\u5b9e\u73b0\u5bf9\u6570\u636e\u7684\u8fed\u4ee3\u5904\u7406\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u4e00\u4e2afor\u5faa\u73af\u904d\u5386list\u4e2d\u7684\u6bcf\u4e2a\u5143\u7d20\uff0c\u5bf9\u5176\u8fdb\u884c\u64cd\u4f5c\u5e76\u7ed8\u5236\u76f8\u5e94\u7684\u56fe\u5f62\u3002\u8fd9\u79cd\u65b9\u6cd5\u4e0d\u4ec5\u7b80\u5316\u4e86\u4ee3\u7801\uff0c\u8fd8\u63d0\u9ad8\u4e86\u7a0b\u5e8f\u7684\u6267\u884c\u6548\u7387\u3002<\/p>\n<\/p>\n

        import matplotlib.pyplot as plt<\/p>\n
        data = [1, 2, 3, 4, 5]<\/p>\n
        plt.plot(data)<\/p>\n
        plt.show()<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u5207\u7247\u64cd\u4f5c<\/li>\n<\/ol>\n
          list\u7684\u5207\u7247\u529f\u80fd\u4f7f\u5f97\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u83b7\u53d6\u6570\u636e\u96c6\u7684\u4e00\u90e8\u5206\uff0c\u800c\u65e0\u9700\u7f16\u5199\u590d\u6742\u7684\u4ee3\u7801\u3002\u8fd9\u5728\u5904\u7406\u5927\u578b\u6570\u636e\u96c6\u65f6\u5c24\u4e3a\u6709\u7528\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u5207\u7247\u64cd\u4f5c\u5feb\u901f\u83b7\u53d6\u67d0\u4e2a\u65f6\u95f4\u6bb5\u5185\u7684\u6570\u636e\uff0c\u5e76\u5c06\u5176\u7ed8\u5236\u6210\u56fe\u8868\u3002<\/p>\n<\/p>\n
          data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]<\/p>\n
          subset = data[2:5]  # \u83b7\u53d6list\u7684\u7b2c\u4e09\u5230\u7b2c\u4e94\u4e2a\u5143\u7d20<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4e09\u3001LIST\u5728\u63d0\u9ad8\u7075\u6d3b\u6027\u4e2d\u7684\u4f5c\u7528<\/p>\n<\/p>\n
          list\u7684\u7075\u6d3b\u6027\u4f53\u73b0\u5728\u5176\u80fd\u591f\u5b58\u50a8\u4e0d\u540c\u7c7b\u578b\u7684\u6570\u636e\u3001\u652f\u6301\u591a\u79cd\u64cd\u4f5c\u4ee5\u53ca\u80fd\u591f\u4e0e\u5176\u4ed6\u6570\u636e\u7ed3\u6784\u65e0\u7f1d\u7ed3\u5408\u3002\u901a\u8fc7\u7075\u6d3b\u4f7f\u7528list\uff0c\u6211\u4eec\u53ef\u4ee5\u5b9e\u73b0\u66f4\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u548c\u53ef\u89c6\u5316\u4efb\u52a1\u3002<\/p>\n<\/p>\n
            \n
          1. \u4e0e\u5176\u4ed6\u6570\u636e\u7ed3\u6784\u7684\u7ed3\u5408<\/li>\n<\/ol>\n
            list\u53ef\u4ee5\u4e0e\u5176\u4ed6\u6570\u636e\u7ed3\u6784\uff08\u5982\u5b57\u5178\u3001\u96c6\u5408\u7b49\uff09\u7ed3\u5408\u4f7f\u7528\uff0c\u4ee5\u5b9e\u73b0\u66f4\u590d\u6742\u7684\u6570\u636e\u5b58\u50a8\u548c\u64cd\u4f5c\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528list\u5b58\u50a8\u6570\u636e\u96c6\u7684\u5177\u4f53\u503c\uff0c\u540c\u65f6\u4f7f\u7528\u5b57\u5178\u5b58\u50a8\u6570\u636e\u96c6\u7684\u5143\u6570\u636e\uff08\u5982\u6807\u7b7e\u3001\u5355\u4f4d\u7b49\uff09\u3002\u8fd9\u79cd\u7ed3\u5408\u4f7f\u5f97\u6570\u636e\u7684\u7ba1\u7406\u548c\u64cd\u4f5c\u66f4\u52a0\u7075\u6d3b\u548c\u9ad8\u6548\u3002<\/p>\n<\/p>\n
              \n
            1. \u81ea\u5b9a\u4e49\u6570\u636e\u5904\u7406\u6d41\u7a0b<\/li>\n<\/ol>\n
              list\u7684\u7075\u6d3b\u6027\u8fd8\u4f53\u73b0\u5728\u5176\u80fd\u591f\u652f\u6301\u81ea\u5b9a\u4e49\u7684\u6570\u636e\u5904\u7406\u6d41\u7a0b\u3002\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u5177\u4f53\u9700\u6c42\uff0c\u81ea\u7531\u5b9a\u4e49list\u7684\u64cd\u4f5c\u548c\u5904\u7406\u65b9\u5f0f\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u7f16\u5199\u81ea\u5b9a\u4e49\u7684\u51fd\u6570\uff0c\u7528\u4e8e\u5bf9list\u4e2d\u7684\u6570\u636e\u8fdb\u884c\u7279\u5b9a\u7684\u8f6c\u6362\u6216\u8ba1\u7b97\uff0c\u7136\u540e\u5c06\u7ed3\u679c\u7528\u4e8e\u7ed8\u56fe\u3002<\/p>\n<\/p>\n
              \u56db\u3001\u5982\u4f55\u5728MATPLOTLIB\u4e2d\u5e94\u7528LIST\u7ed8\u56fe<\/p>\n<\/p>\n
              Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u5e76\u4e14\u53ef\u4ee5\u4e0elist\u65e0\u7f1d\u7ed3\u5408\uff0c\u8f7b\u677e\u5b9e\u73b0\u6570\u636e\u7684\u53ef\u89c6\u5316\u3002<\/p>\n<\/p>\n
                \n
              1. \u57fa\u672c\u7ed8\u56fe\u65b9\u6cd5<\/li>\n<\/ol>\n
                \u4f7f\u7528Matplotlib\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u7b80\u5355\u7684\u4ee3\u7801\u5c06list\u4e2d\u7684\u6570\u636e\u7ed8\u5236\u6210\u5404\u79cd\u56fe\u5f62\uff0c\u5305\u62ec\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u7b49\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528list\u7ed8\u5236\u6298\u7ebf\u56fe\uff1a<\/p>\n<\/p>\n
                import matplotlib.pyplot as plt<\/p>\n
                x = [0, 1, 2, 3, 4, 5]<\/p>\n
                y = [0, 1, 4, 9, 16, 25]<\/p>\n
                plt.plot(x, y)<\/p>\n
                plt.xlabel('X Axis')<\/p>\n
                plt.ylabel('Y Axis')<\/p>\n
                plt.title('Line Plot Example')<\/p>\n
                plt.show()<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                \u5728\u8fd9\u4e2a\u793a\u4f8b\u4e2d\uff0c\u6211\u4eec\u4f7f\u7528\u4e24\u4e2alist\uff08x\u548cy\uff09\u5b58\u50a8\u6570\u636e\u70b9\u7684\u5750\u6807\uff0c\u7136\u540e\u4f7f\u7528Matplotlib\u7684plot\u51fd\u6570\u7ed8\u5236\u6298\u7ebf\u56fe\u3002<\/p>\n<\/p>\n
                  \n
                1. \u9ad8\u7ea7\u7ed8\u56fe\u6280\u5de7<\/li>\n<\/ol>\n
                  Matplotlib\u8fd8\u63d0\u4f9b\u4e86\u8bb8\u591a\u9ad8\u7ea7\u529f\u80fd\uff0c\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u521b\u5efa\u66f4\u590d\u6742\u548c\u7f8e\u89c2\u7684\u56fe\u5f62\u3002\u4f8b\u5982\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528list\u7ed3\u5408\u989c\u8272\u3001\u6807\u8bb0\u3001\u7ebf\u578b\u7b49\u53c2\u6570\uff0c\u81ea\u5b9a\u4e49\u7ed8\u56fe\u7684\u5916\u89c2\uff1a<\/p>\n<\/p>\n
                  plt.plot(x, y, color='red', marker='o', linestyle='--')<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u6b64\u5916\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528list\u5b58\u50a8\u4e0d\u540c\u6570\u636e\u7cfb\u5217\u7684\u503c\uff0c\u5e76\u5728\u540c\u4e00\u5f20\u56fe\u4e2d\u7ed8\u5236\u591a\u4e2a\u6570\u636e\u7cfb\u5217\uff1a<\/p>\n<\/p>\n
                  x = [0, 1, 2, 3, 4, 5]<\/p>\n
                  y1 = [0, 1, 4, 9, 16, 25]<\/p>\n
                  y2 = [0, 1, 2, 3, 4, 5]<\/p>\n
                  plt.plot(x, y1, label='y1')<\/p>\n
                  plt.plot(x, y2, label='y2')<\/p>\n
                  plt.legend()<\/p>\n
                  plt.show()<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u4e94\u3001LIST\u7684\u5176\u4ed6\u5e94\u7528\u573a\u666f<\/p>\n<\/p>\n
                  \u9664\u4e86\u5728Matplotlib\u4e2d\u7684\u5e94\u7528\uff0clist\u8fd8\u53ef\u4ee5\u5728\u5176\u4ed6\u7ed8\u56fe\u5e93\uff08\u5982Seaborn\u3001Plotly\u7b49\uff09\u4e2d\u7528\u4e8e\u6570\u636e\u5b58\u50a8\u548c\u64cd\u4f5c\u3002\u901a\u8fc7\u638c\u63e1list\u7684\u4f7f\u7528\u6280\u5de7\uff0c\u6211\u4eec\u53ef\u4ee5\u5728\u5404\u79cd\u7ed8\u56fe\u5e93\u4e2d\u7075\u6d3b\u5e94\u7528list\uff0c\u5b9e\u73b0\u590d\u6742\u7684\u6570\u636e\u53ef\u89c6\u5316\u4efb\u52a1\u3002<\/p>\n<\/p>\n
                    \n
                  1. \u5728Seaborn\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n
                    Seaborn\u662f\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u7ed8\u56fe\u5e93\uff0c\u63d0\u4f9b\u4e86\u66f4\u4e3a\u7f8e\u89c2\u548c\u7b80\u6d01\u7684\u7ed8\u56fe\u63a5\u53e3\u3002\u5728Seaborn\u4e2d\uff0c\u6211\u4eec\u540c\u6837\u53ef\u4ee5\u4f7f\u7528list\u5b58\u50a8\u548c\u64cd\u4f5c\u6570\u636e\uff0c\u4ee5\u751f\u6210\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u5f62\u3002<\/p>\n<\/p>\n
                    import seaborn as sns<\/p>\n
                    data = [1, 2, 3, 4, 5]<\/p>\n
                    sns.lineplot(data=data)<\/p>\n
                    <\/code><\/pre>\n<\/p>\n
                      \n
                    1. \u5728Plotly\u4e2d\u7684\u5e94\u7528<\/li>\n<\/ol>\n
                      Plotly\u662f\u4e00\u6b3e\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u5e93\uff0c\u652f\u6301\u4e30\u5bcc\u7684\u4ea4\u4e92\u529f\u80fd\u3002\u5728Plotly\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528list\u5b58\u50a8\u6570\u636e\uff0c\u5e76\u7ed3\u5408Plotly\u7684\u63a5\u53e3\u751f\u6210\u52a8\u6001\u548c\u4ea4\u4e92\u5f0f\u7684\u56fe\u5f62\u3002<\/p>\n<\/p>\n
                      import plotly.express as px<\/p>\n
                      x = [0, 1, 2, 3, 4, 5]<\/p>\n
                      y = [0, 1, 4, 9, 16, 25]<\/p>\n
                      fig = px.line(x=x, y=y)<\/p>\n
                      fig.show()<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                      \u516d\u3001\u603b\u7ed3<\/p>\n<\/p>\n
                      \u5728Python\u753b\u56fe\u65f6\uff0clist\u662f\u4e00\u4e2a\u975e\u5e38\u91cd\u8981\u7684\u6570\u636e\u7ed3\u6784\uff0c\u5b83\u53ef\u4ee5\u7528\u4e8e\u5b58\u50a8\u6570\u636e\u3001\u7b80\u5316\u4ee3\u7801\u3001\u63d0\u9ad8\u7075\u6d3b\u6027\u3002\u901a\u8fc7\u5408\u7406\u4f7f\u7528list\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u590d\u6742\u7684\u6570\u636e\u5904\u7406\u548c\u53ef\u89c6\u5316\u4efb\u52a1\u3002\u5728\u672a\u6765\u7684\u5de5\u4f5c\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u7ed3\u5408\u4e0d\u540c\u7684\u7ed8\u56fe\u5e93\uff0c\u7075\u6d3b\u5e94\u7528list\uff0c\u521b\u9020\u51fa\u66f4\u52a0\u4e30\u5bcc\u548c\u7f8e\u89c2\u7684\u6570\u636e\u53ef\u89c6\u5316\u4f5c\u54c1\u3002\u65e0\u8bba\u662f\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff0c\u8fd8\u662f\u590d\u6742\u7684\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0clist\u90fd\u80fd\u4e3a\u6211\u4eec\u63d0\u4f9b\u5f3a\u5927\u7684\u652f\u6301\u3002<\/p>\n<\/p>\n
                      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                       \u5982\u4f55\u5728Python\u4e2d\u4f7f\u7528\u5217\u8868\u7ed8\u5236\u56fe\u5f62\uff1f<\/strong>
                      \u5728Python\u4e2d\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528matplotlib<\/code>\u5e93\u6765\u7ed8\u5236\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u5f62\u3002\u901a\u8fc7\u5c06\u6570\u636e\u5b58\u50a8\u5728\u5217\u8868\u4e2d\uff0c\u60a8\u53ef\u4ee5\u8f7b\u677e\u5730\u5c06\u5176\u4f20\u9012\u7ed9\u7ed8\u56fe\u51fd\u6570\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u5305\u542bx\u8f74\u548cy\u8f74\u5750\u6807\u7684\u5217\u8868\uff0c\u5e76\u4f7f\u7528plt.plot()<\/code>\u51fd\u6570\u6765\u7ed8\u5236\u8fd9\u4e9b\u70b9\u3002<\/p>\n
                      \u4f7f\u7528\u5217\u8868\u7ed8\u56fe\u65f6\uff0c\u5982\u4f55\u5904\u7406\u6570\u636e\u7684\u53d8\u5316\uff1f<\/strong>
                      \u5f53\u60a8\u7684\u6570\u636e\u53d1\u751f\u53d8\u5316\u65f6\uff0c\u60a8\u53ef\u4ee5\u76f4\u63a5\u66f4\u65b0\u5217\u8868\u4e2d\u7684\u503c\uff0c\u5e76\u91cd\u65b0\u8c03\u7528\u7ed8\u56fe\u51fd\u6570\u3002\u4e3a\u4e86\u52a8\u6001\u66f4\u65b0\u56fe\u5f62\uff0c\u53ef\u4ee5\u5728\u5faa\u73af\u4e2d\u4f7f\u7528plt.pause()<\/code>\u51fd\u6570\uff0c\u4f7f\u56fe\u5f62\u5b9e\u65f6\u66f4\u65b0\u3002\u8fd9\u79cd\u65b9\u6cd5\u975e\u5e38\u9002\u5408\u5904\u7406\u5b9e\u65f6\u6570\u636e\u6216\u9700\u8981\u66f4\u65b0\u7684\u56fe\u8868\u3002<\/p>\n
                      \u5728\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u5982\u4f55\u81ea\u5b9a\u4e49\u5217\u8868\u4e2d\u7684\u6570\u636e\u70b9\uff1f<\/strong>
                      \u60a8\u53ef\u4ee5\u5bf9\u5217\u8868\u4e2d\u7684\u6570\u636e\u70b9\u8fdb\u884c\u5404\u79cd\u81ea\u5b9a\u4e49\uff0c\u4f8b\u5982\u4fee\u6539\u70b9\u7684\u989c\u8272\u3001\u5f62\u72b6\u548c\u5927\u5c0f\u3002\u901a\u8fc7\u5728plt.plot()<\/code>\u4e2d\u6dfb\u52a0\u53c2\u6570\uff0c\u4f8b\u5982color<\/code>, marker<\/code>\u548cmarkersize<\/code>\uff0c\u53ef\u4ee5\u5b9e\u73b0\u4e2a\u6027\u5316\u7684\u56fe\u5f62\u6548\u679c\u3002\u6b64\u5916\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528plt.title()<\/code>\u548cplt.xlabel()<\/code>\u7b49\u51fd\u6570\u4e3a\u56fe\u5f62\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e\uff0c\u4f7f\u56fe\u5f62\u66f4\u5177\u53ef\u8bfb\u6027\u548c\u4e13\u4e1a\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5728Python\u753b\u56fe\u65f6\uff0clist\u53ef\u4ee5\u7528\u4e8e\u5b58\u50a8\u6570\u636e\u3001\u7b80\u5316\u4ee3\u7801\u3001\u63d0\u9ad8\u7075\u6d3b\u6027\u3002\u5176\u4e2d\uff0c\u5b58\u50a8\u6570\u636e\u8fd9\u4e00\u70b9\u5c24\u4e3a\u91cd\u8981\uff0clist\u53ef […]","protected":false},"author":3,"featured_media":977844,"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\/977832"}],"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=977832"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/977832\/revisions"}],"predecessor-version":[{"id":977848,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/977832\/revisions\/977848"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/977844"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=977832"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=977832"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=977832"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}