{"id":1014545,"date":"2024-12-27T11:57:07","date_gmt":"2024-12-27T03:57:07","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1014545.html"},"modified":"2024-12-27T11:57:10","modified_gmt":"2024-12-27T03:57:10","slug":"%e5%a6%82%e4%bd%95%e6%89%be%e5%88%b0python%e7%94%bb%e5%9b%be%e8%bd%af%e4%bb%b6","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1014545.html","title":{"rendered":"\u5982\u4f55\u627e\u5230python\u753b\u56fe\u8f6f\u4ef6"},"content":{"rendered":"

\"\u5982\u4f55\u627e\u5230python\u753b\u56fe\u8f6f\u4ef6\"<\/p>\n

\u8981\u627e\u5230\u9002\u5408\u7684Python\u753b\u56fe\u8f6f\u4ef6\uff0c\u53ef\u4ee5\u4ece\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\u5165\u624b\uff1a\u6839\u636e\u9879\u76ee\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u3001\u4e86\u89e3\u4e0d\u540c\u5e93\u7684\u529f\u80fd\u7279\u70b9\u3001\u8003\u8651\u793e\u533a\u652f\u6301\u548c\u6587\u6863\u8d28\u91cf\u3002<\/strong> \u5176\u4e2d\uff0c\u6839\u636e\u9879\u76ee\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93<\/strong>\u5c24\u5176\u91cd\u8981\uff0c\u56e0\u4e3a\u4e0d\u540c\u7684\u9879\u76ee\u53ef\u80fd\u5bf9\u56fe\u5f62\u7684\u590d\u6742\u6027\u3001\u4ea4\u4e92\u6027\u4ee5\u53ca\u56fe\u5f62\u79cd\u7c7b\u6709\u4e0d\u540c\u7684\u8981\u6c42\u3002\u6bd4\u5982\uff0c\u5982\u679c\u4f60\u9700\u8981\u7b80\u5355\u7684\u9759\u6001\u56fe\u8868\uff0cMatplotlib\u53ef\u80fd\u662f\u4e00\u4e2a\u4e0d\u9519\u7684\u9009\u62e9\uff1b\u5982\u679c\u4f60\u9700\u8981\u66f4\u590d\u6742\u7684\u4ea4\u4e92\u56fe\uff0cPlotly\u53ef\u80fd\u66f4\u9002\u5408\u3002<\/p>\n<\/p>\n

\u9009\u62e9\u5408\u9002\u7684\u5e93\u53ef\u4ee5\u5927\u5927\u63d0\u5347\u5f00\u53d1\u6548\u7387\u548c\u56fe\u5f62\u6548\u679c\u3002\u4e86\u89e3\u5e93\u7684\u529f\u80fd\u7279\u70b9\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u627e\u5230\u6700\u9002\u5408\u9879\u76ee\u9700\u6c42\u7684\u5de5\u5177\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u7684Python\u753b\u56fe\u5e93\u7684\u7279\u70b9\u548c\u9002\u7528\u573a\u666f\uff1a<\/p>\n<\/p>\n

\u4e00\u3001MATPLOTLIB<\/p>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u9002\u5408\u7528\u4e8e\u521b\u5efa\u9759\u6001\u7684\u3001\u51fa\u7248\u8d28\u91cf\u7684\u56fe\u8868\u3002\u5176\u6700\u5927\u7684\u4f18\u52bf\u5728\u4e8e\u7075\u6d3b\u6027\u548c\u5e7f\u6cdb\u7684\u652f\u6301\u3002<\/p>\n<\/p>\n

    \n
  1. \n

    \u7075\u6d3b\u6027<\/strong>\uff1aMatplotlib\u51e0\u4e4e\u53ef\u4ee5\u751f\u6210\u4efb\u4f55\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5e76\u4e14\u53ef\u4ee5\u8fdb\u884c\u8be6\u7ec6\u7684\u81ea\u5b9a\u4e49\u3002\u8fd9\u4f7f\u5f97\u5b83\u5728\u9700\u8981\u7279\u5b9a\u6837\u5f0f\u6216\u683c\u5f0f\u7684\u60c5\u51b5\u4e0b\u975e\u5e38\u6709\u7528\u3002<\/p>\n<\/p>\n<\/li>\n

  2. \n

    \u5e7f\u6cdb\u7684\u652f\u6301<\/strong>\uff1a\u7531\u4e8e\u5176\u5386\u53f2\u60a0\u4e45\uff0cMatplotlib\u62e5\u6709\u4e30\u5bcc\u7684\u6587\u6863\u548c\u5f3a\u5927\u7684\u793e\u533a\u652f\u6301\u3002\u65e0\u8bba\u4f60\u9047\u5230\u4ec0\u4e48\u95ee\u9898\uff0c\u51e0\u4e4e\u603b\u80fd\u5728\u7f51\u4e0a\u627e\u5230\u89e3\u51b3\u65b9\u6848\u3002<\/p>\n<\/p>\n<\/li>\n

  3. \n

    \u4e0e\u5176\u4ed6\u5e93\u7684\u96c6\u6210<\/strong>\uff1aMatplotlib\u53ef\u4ee5\u4e0eNumPy\u3001Pandas\u548cSciPy\u7b49\u79d1\u5b66\u8ba1\u7b97\u5e93\u65e0\u7f1d\u96c6\u6210\uff0c\u8fd9\u4f7f\u5f97\u5b83\u975e\u5e38\u9002\u5408\u7528\u4e8e\u6570\u636e\u5206\u6790\u548c\u79d1\u5b66\u7814\u7a76\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

    \u4e8c\u3001SEABORN<\/p>\n<\/p>\n

    Seaborn\u662f\u57fa\u4e8eMatplotlib\u6784\u5efa\u7684\uff0c\u4e13\u6ce8\u4e8e\u7b80\u5316\u7edf\u8ba1\u56fe\u8868\u7684\u521b\u5efa\u3002\u5b83\u7684\u8bbe\u8ba1\u76ee\u6807\u662f\u8ba9\u6570\u636e\u53ef\u89c6\u5316\u53d8\u5f97\u66f4\u52a0\u76f4\u89c2\u548c\u6613\u4e8e\u7406\u89e3\u3002<\/p>\n<\/p>\n

      \n
    1. \n

      \u7b80\u5316\u7684API<\/strong>\uff1aSeaborn\u7684API\u6bd4Matplotlib\u66f4\u52a0\u7b80\u6d01\uff0c\u5c24\u5176\u5728\u521b\u5efa\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u8868\u65f6\uff0c\u53ef\u4ee5\u5927\u5927\u51cf\u5c11\u4ee3\u7801\u91cf\u3002<\/p>\n<\/p>\n<\/li>\n

    2. \n

      \u5185\u7f6e\u7684\u4e3b\u9898\u548c\u8c03\u8272\u677f<\/strong>\uff1aSeaborn\u63d0\u4f9b\u4e86\u4e00\u4e9b\u9884\u5b9a\u4e49\u7684\u4e3b\u9898\u548c\u8c03\u8272\u677f\uff0c\u4f7f\u5f97\u751f\u6210\u7684\u56fe\u8868\u66f4\u52a0\u7f8e\u89c2\u548c\u4e13\u4e1a\u3002<\/p>\n<\/p>\n<\/li>\n

    3. \n

      \u9ad8\u7ea7\u7edf\u8ba1\u56fe\u8868<\/strong>\uff1aSeaborn\u53ef\u4ee5\u8f7b\u677e\u521b\u5efa\u5982\u70ed\u56fe\u3001\u5206\u5e03\u56fe\u3001\u56de\u5f52\u56fe\u7b49\u9ad8\u7ea7\u7edf\u8ba1\u56fe\u8868\uff0c\u975e\u5e38\u9002\u5408\u6570\u636e\u5206\u6790\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

      \u4e09\u3001PLOTLY<\/p>\n<\/p>\n

      Plotly\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u7684\u5e93\uff0c\u7528\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u7684\u3001\u5b9e\u65f6\u66f4\u65b0\u7684\u56fe\u8868\uff0c\u9002\u5408\u7528\u4e8eWeb\u5e94\u7528\u548c\u6570\u636e\u5c55\u793a\u3002<\/p>\n<\/p>\n

        \n
      1. \n

        \u4ea4\u4e92\u6027<\/strong>\uff1aPlotly\u751f\u6210\u7684\u56fe\u8868\u662f\u4ea4\u4e92\u5f0f\u7684\uff0c\u7528\u6237\u53ef\u4ee5\u5728\u7f51\u9875\u4e0a\u8fdb\u884c\u7f29\u653e\u3001\u60ac\u505c\u67e5\u770b\u8be6\u7ec6\u4fe1\u606f\u7b49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<\/li>\n

      2. \n

        \u652f\u6301\u591a\u79cd\u8f93\u51fa\u683c\u5f0f<\/strong>\uff1aPlotly\u7684\u56fe\u8868\u53ef\u4ee5\u5bfc\u51fa\u4e3aHTML\u3001PDF\u548c\u56fe\u50cf\u6587\u4ef6\uff0c\u8fd9\u4f7f\u5f97\u5b83\u975e\u5e38\u9002\u5408\u7528\u4e8e\u62a5\u544a\u548c\u5c55\u793a\u3002<\/p>\n<\/p>\n<\/li>\n

      3. \n

        \u652f\u6301\u591a\u5e73\u53f0<\/strong>\uff1aPlotly\u4e0d\u4ec5\u652f\u6301Python\uff0c\u8fd8\u652f\u6301R\u3001Matlab\u548cJavaScript\uff0c\u8fd9\u4f7f\u5f97\u5b83\u5728\u8de8\u5e73\u53f0\u9879\u76ee\u4e2d\u975e\u5e38\u5b9e\u7528\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

        \u56db\u3001BOKEH<\/p>\n<\/p>\n

        Bokeh\u662f\u4e13\u6ce8\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u548c\u53ef\u6269\u5c55\u7684\u56fe\u8868\uff0c\u7279\u522b\u662f\u5728\u5927\u6570\u636e\u96c6\u7684\u53ef\u89c6\u5316\u65b9\u9762\u8868\u73b0\u51fa\u8272\u3002<\/p>\n<\/p>\n

          \n
        1. \n

          \u5927\u6570\u636e\u96c6\u652f\u6301<\/strong>\uff1aBokeh\u80fd\u591f\u5904\u7406\u5927\u6570\u636e\u96c6\uff0c\u5e76\u4e14\u5728\u6d4f\u89c8\u5668\u4e2d\u5b9e\u65f6\u6e32\u67d3\u56fe\u5f62\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u9700\u8981\u5b9e\u65f6\u4ea4\u4e92\u7684\u5e94\u7528\u3002<\/p>\n<\/p>\n<\/li>\n

        2. \n

          \u4e30\u5bcc\u7684\u4ea4\u4e92\u529f\u80fd<\/strong>\uff1aBokeh\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u4ea4\u4e92\u529f\u80fd\uff0c\u5982\u7f29\u653e\u3001\u9009\u62e9\u3001\u60ac\u505c\u7b49\uff0c\u7528\u6237\u4f53\u9a8c\u975e\u5e38\u53cb\u597d\u3002<\/p>\n<\/p>\n<\/li>\n

        3. \n

          \u4e0eWeb\u6846\u67b6\u7684\u96c6\u6210<\/strong>\uff1aBokeh\u53ef\u4ee5\u4e0eFlask\u3001Django\u7b49Web\u6846\u67b6\u96c6\u6210\uff0c\u9002\u5408\u7528\u4e8e\u6784\u5efa\u6570\u636e\u9a71\u52a8\u7684Web\u5e94\u7528\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

          \u4e94\u3001GG PLOT<\/p>\n<\/p>\n

          \u867d\u7136ggplot\u662fR\u8bed\u8a00\u4e2d\u7684\u4e00\u5927\u7279\u8272\uff0c\u4f46\u5728Python\u4e2d\u4e5f\u6709\u7c7b\u4f3c\u7684\u5b9e\u73b0\uff0c\u5982plotnine<\/code>\u3002\u5b83\u4eec\u90fd\u57fa\u4e8e\u201cGrammar of Graphics\u201d\u7406\u5ff5\u3002<\/p>\n<\/p>\n

            \n
          1. \n

            \u4e00\u81f4\u7684\u8bed\u6cd5<\/strong>\uff1aggplot\u7684\u8bed\u6cd5\u975e\u5e38\u4e00\u81f4\uff0c\u6240\u6709\u56fe\u8868\u90fd\u662f\u901a\u8fc7\u5c06\u56fe\u5c42\u53e0\u52a0\u8d77\u6765\u6784\u5efa\u7684\uff0c\u8fd9\u4f7f\u5f97\u5b66\u4e60\u548c\u4f7f\u7528\u53d8\u5f97\u7b80\u5355\u3002<\/p>\n<\/p>\n<\/li>\n

          2. \n

            \u9ad8\u6c34\u5e73\u7684\u62bd\u8c61<\/strong>\uff1a\u7531\u4e8e\u5176\u62bd\u8c61\u7a0b\u5ea6\u9ad8\uff0cggplot\u975e\u5e38\u9002\u5408\u7528\u4e8e\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790\u548c\u5feb\u901f\u539f\u578b\u8bbe\u8ba1\u3002<\/p>\n<\/p>\n<\/li>\n

          3. \n

            \u53ef\u5b9a\u5236\u6027\u5f3a<\/strong>\uff1aggplot\u5141\u8bb8\u7528\u6237\u7cbe\u7ec6\u8c03\u6574\u56fe\u8868\u7684\u5404\u4e2a\u65b9\u9762\uff0c\u4ece\u800c\u5b9e\u73b0\u975e\u5e38\u7cbe\u7f8e\u7684\u56fe\u8868\u6548\u679c\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

            \u516d\u3001\u9009\u62e9\u5408\u9002\u7684\u5e93<\/p>\n<\/p>\n

            \u9009\u62e9\u5408\u9002\u7684Python\u753b\u56fe\u8f6f\u4ef6\u9700\u8981\u7efc\u5408\u8003\u8651\u9879\u76ee\u9700\u6c42\u3001\u4e2a\u4eba\u504f\u597d\u4ee5\u53ca\u56e2\u961f\u7684\u6280\u672f\u6808\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u9009\u62e9\u5efa\u8bae\uff1a<\/p>\n<\/p>\n

              \n
            1. \n

              \u9879\u76ee\u9700\u6c42<\/strong>\uff1a\u5982\u679c\u4f60\u7684\u9879\u76ee\u9700\u8981\u9759\u6001\u548c\u9ad8\u8d28\u91cf\u7684\u56fe\u8868\uff0cMatplotlib\u548cSeaborn\u53ef\u80fd\u662f\u6700\u4f73\u9009\u62e9\u3002\u5982\u679c\u9700\u8981\u4ea4\u4e92\u5f0f\u56fe\u8868\uff0cPlotly\u548cBokeh\u4f1a\u66f4\u5408\u9002\u3002<\/p>\n<\/p>\n<\/li>\n

            2. \n

              \u4e2a\u4eba\u504f\u597d<\/strong>\uff1a\u5982\u679c\u4f60\u559c\u6b22\u7b80\u6d01\u7684\u8bed\u6cd5\u548c\u5feb\u901f\u751f\u6210\u56fe\u8868\uff0cSeaborn\u548cggplot\u53ef\u80fd\u66f4\u9002\u5408\u3002\u5982\u679c\u4f60\u9700\u8981\u9ad8\u5ea6\u81ea\u5b9a\u4e49\u7684\u56fe\u8868\uff0cMatplotlib\u53ef\u80fd\u66f4\u597d\u3002<\/p>\n<\/p>\n<\/li>\n

            3. \n

              \u56e2\u961f\u6280\u672f\u6808<\/strong>\uff1a\u8003\u8651\u56e2\u961f\u4e2d\u5176\u4ed6\u6210\u5458\u7684\u6280\u80fd\u6c34\u5e73\u548c\u719f\u6089\u7a0b\u5ea6\uff0c\u4ee5\u53ca\u516c\u53f8\u6216\u9879\u76ee\u4e2d\u5df2\u6709\u7684\u6280\u672f\u6808\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

              \u4e03\u3001\u793e\u533a\u652f\u6301\u548c\u6587\u6863<\/p>\n<\/p>\n

              \u793e\u533a\u652f\u6301\u548c\u6587\u6863\u8d28\u91cf\u4e5f\u662f\u9009\u62e9Python\u753b\u56fe\u8f6f\u4ef6\u7684\u91cd\u8981\u56e0\u7d20\u3002\u4e00\u4e2a\u6d3b\u8dc3\u7684\u793e\u533a\u53ef\u4ee5\u63d0\u4f9b\u53ca\u65f6\u7684\u5e2e\u52a9\u548c\u4e30\u5bcc\u7684\u8d44\u6e90\uff0c\u800c\u9ad8\u8d28\u91cf\u7684\u6587\u6863\u53ef\u4ee5\u5927\u5927\u964d\u4f4e\u5b66\u4e60\u66f2\u7ebf\u3002<\/p>\n<\/p>\n

                \n
              1. \n

                \u793e\u533a\u652f\u6301<\/strong>\uff1a\u9009\u62e9\u4e00\u4e2a\u6709\u6d3b\u8dc3\u793e\u533a\u7684\u5e93\u610f\u5473\u7740\u4f60\u53ef\u4ee5\u83b7\u5f97\u53ca\u65f6\u7684\u5e2e\u52a9\u548c\u6700\u65b0\u7684\u8d44\u6e90\u3002\u67e5\u770bGitHub\u4e0a\u7684\u6d3b\u8dc3\u5ea6\u3001\u8bba\u575b\u548c\u793e\u4ea4\u5a92\u4f53\u4e0a\u7684\u8ba8\u8bba\u662f\u4e86\u89e3\u793e\u533a\u652f\u6301\u7684\u597d\u65b9\u6cd5\u3002<\/p>\n<\/p>\n<\/li>\n

              2. \n

                \u6587\u6863\u8d28\u91cf<\/strong>\uff1a\u9605\u8bfb\u6587\u6863\u662f\u5feb\u901f\u638c\u63e1\u4e00\u4e2a\u5e93\u7684\u6700\u4f73\u9014\u5f84\u3002\u9009\u62e9\u4e00\u4e2a\u6709\u6e05\u6670\u3001\u8be6\u7ec6\u6587\u6863\u7684\u5e93\uff0c\u53ef\u4ee5\u5e2e\u52a9\u4f60\u66f4\u5feb\u4e0a\u624b\u3002<\/p>\n<\/p>\n<\/li>\n<\/ol>\n

                \u516b\u3001\u603b\u7ed3<\/p>\n<\/p>\n

                \u9009\u62e9\u5408\u9002\u7684Python\u753b\u56fe\u8f6f\u4ef6\u9700\u8981\u7efc\u5408\u8003\u8651\u591a\u4e2a\u56e0\u7d20\uff0c\u5305\u62ec\u9879\u76ee\u9700\u6c42\u3001\u4e2a\u4eba\u504f\u597d\u3001\u56e2\u961f\u6280\u672f\u6808\u3001\u793e\u533a\u652f\u6301\u548c\u6587\u6863\u8d28\u91cf\u3002\u65e0\u8bba\u4f60\u9009\u62e9\u54ea\u4e00\u4e2a\u5e93\uff0c\u90fd\u53ef\u4ee5\u901a\u8fc7\u5b66\u4e60\u548c\u5b9e\u8df5\uff0c\u5145\u5206\u53d1\u6325\u5176\u529f\u80fd\uff0c\u5b9e\u73b0\u6570\u636e\u7684\u53ef\u89c6\u5316\u548c\u5206\u6790\u3002<\/p>\n<\/p>\n

                \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n

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