{"id":954954,"date":"2024-12-27T02:06:50","date_gmt":"2024-12-26T18:06:50","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/954954.html"},"modified":"2024-12-27T02:06:53","modified_gmt":"2024-12-26T18:06:53","slug":"python%e4%bd%9c%e5%9b%be%e5%a6%82%e4%bd%95%e5%87%ba%e7%8e%b0%e6%b1%89%e5%ad%97","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/954954.html","title":{"rendered":"python\u4f5c\u56fe\u5982\u4f55\u51fa\u73b0\u6c49\u5b57"},"content":{"rendered":"

\"python\u4f5c\u56fe\u5982\u4f55\u51fa\u73b0\u6c49\u5b57\"<\/p>\n

\u5f00\u5934\u6bb5\u843d\uff1a
\u5728Python\u4e2d\u4f5c\u56fe\u65f6\u51fa\u73b0\u6c49\u5b57\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u5b57\u4f53\u3001\u4f7f\u7528matplotlib\u5e93\u3001\u89e3\u51b3\u4e71\u7801\u95ee\u9898<\/strong>\u7b49\u65b9\u6cd5\u6765\u5b9e\u73b0\u3002\u5176\u4e2d\uff0c\u8bbe\u7f6e\u5b57\u4f53<\/strong>\u662f\u5b9e\u73b0\u6c49\u5b57\u663e\u793a\u7684\u5173\u952e\u6b65\u9aa4\u3002\u901a\u5e38\uff0cmatplotlib\u9ed8\u8ba4\u4f7f\u7528\u7684\u5b57\u4f53\u4e0d\u652f\u6301\u4e2d\u6587\uff0c\u56e0\u6b64\u9700\u8981\u624b\u52a8\u6307\u5b9a\u652f\u6301\u4e2d\u6587\u7684\u5b57\u4f53\u3002\u53ef\u4ee5\u901a\u8fc7matplotlib.font_manager<\/code>\u4e2d\u7684FontProperties<\/code>\u7c7b\u6765\u6307\u5b9a\u5b57\u4f53\u6587\u4ef6\u8def\u5f84\uff0c\u6216\u8005\u901a\u8fc7rcParams<\/code>\u5168\u5c40\u8bbe\u7f6e\u5b57\u4f53\u3002\u89e3\u51b3\u4e71\u7801\u95ee\u9898\u65f6\uff0c\u8fd8\u9700\u786e\u4fdd\u6587\u672c\u7f16\u7801\u6b63\u786e\uff0c\u5e76\u5728\u5fc5\u8981\u65f6\u8c03\u6574\u73af\u5883\u914d\u7f6e\u4ee5\u652f\u6301\u4e2d\u6587\u663e\u793a\u3002 <\/p>\n<\/p>\n

\u4e00\u3001\u8bbe\u7f6e\u5b57\u4f53<\/p>\n<\/p>\n

\u5728Python\u4e2d\u4f7f\u7528matplotlib\u8fdb\u884c\u4f5c\u56fe\u65f6\uff0c\u9ed8\u8ba4\u5b57\u4f53\u4e0d\u652f\u6301\u6c49\u5b57\u663e\u793a\uff0c\u56e0\u6b64\u9700\u8981\u624b\u52a8\u8bbe\u7f6e\u5b57\u4f53\u6765\u663e\u793a\u6c49\u5b57\u3002\u53ef\u4ee5\u4f7f\u7528matplotlib.font_manager<\/code>\u6a21\u5757\u4e2d\u7684FontProperties<\/code>\u7c7b\u6216rcParams<\/code>\u5b57\u5178\u6765\u8bbe\u7f6e\u5b57\u4f53\u3002<\/p>\n<\/p>\n

    \n
  1. \u4f7f\u7528FontProperties\u7c7b<\/li>\n<\/ol>\n

    FontProperties<\/code>\u7c7b\u5141\u8bb8\u6211\u4eec\u6307\u5b9a\u5b57\u4f53\u6587\u4ef6\u7684\u8def\u5f84\u3002\u9996\u5148\uff0c\u627e\u5230\u652f\u6301\u4e2d\u6587\u7684\u5b57\u4f53\u6587\u4ef6\uff0c\u5982\u5fae\u8f6f\u96c5\u9ed1\u6216SimHei\u3002\u7136\u540e\u5728\u4ee3\u7801\u4e2d\u4f7f\u7528FontProperties<\/code>\u7c7b\u6765\u52a0\u8f7d\u8be5\u5b57\u4f53\u6587\u4ef6\uff0c\u5e76\u5728\u7ed8\u56fe\u65f6\u6307\u5b9a\u4f7f\u7528\u8fd9\u4e2a\u5b57\u4f53\u3002<\/p>\n<\/p>\n

    from matplotlib.font_manager import FontProperties<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    font = FontProperties(fname='\/path\/to\/your\/font.ttf')<\/p>\n
    plt.title('\u4e2d\u6587\u6807\u9898', fontproperties=font)<\/p>\n
    plt.xlabel('X\u8f74', fontproperties=font)<\/p>\n
    plt.ylabel('Y\u8f74', fontproperties=font)<\/p>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u4f7f\u7528rcParams\u5b57\u5178<\/li>\n<\/ol>\n
      rcParams<\/code>\u5b57\u5178\u63d0\u4f9b\u4e86\u4e00\u79cd\u5168\u5c40\u65b9\u5f0f\u6765\u8bbe\u7f6ematplotlib\u7684\u9ed8\u8ba4\u53c2\u6570\uff0c\u5305\u62ec\u5b57\u4f53\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7rcParams<\/code>\u5b57\u5178\u6765\u8bbe\u7f6e\u9ed8\u8ba4\u5b57\u4f53\u4e3a\u652f\u6301\u4e2d\u6587\u7684\u5b57\u4f53\u3002<\/p>\n<\/p>\n
      import matplotlib.pyplot as plt<\/p>\n
      plt.rcParams['font.sans-serif'] = ['SimHei']  # \u7528\u9ed1\u4f53\u663e\u793a\u4e2d\u6587<\/p>\n
      plt.rcParams['axes.unicode_minus'] = False    # \u89e3\u51b3\u8d1f\u53f7\u663e\u793a\u95ee\u9898<\/p>\n
      plt.title('\u4e2d\u6587\u6807\u9898')<\/p>\n
      plt.xlabel('X\u8f74')<\/p>\n
      plt.ylabel('Y\u8f74')<\/p>\n
      plt.show()<\/p>\n
      <\/code><\/pre>\n<\/p>\n
      \u4e8c\u3001\u4f7f\u7528matplotlib\u5e93<\/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\u540c\u65f6\u4e5f\u652f\u6301\u663e\u793a\u6c49\u5b57\u3002\u5728matplotlib\u4e2d\u663e\u793a\u6c49\u5b57\uff0c\u901a\u5e38\u9700\u8981\u5904\u7406\u5b57\u4f53\u8bbe\u7f6e\u53ca\u7f16\u7801\u95ee\u9898\u3002<\/p>\n<\/p>\n
        \n
      1. \u5b89\u88c5matplotlib<\/li>\n<\/ol>\n
        \u5728\u4f7f\u7528matplotlib\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u5176\u5df2\u5b89\u88c5\u3002\u53ef\u4ee5\u901a\u8fc7pip\u547d\u4ee4\u6765\u5b89\u88c5matplotlib\uff1a<\/p>\n<\/p>\n
        pip install matplotlib<\/p>\n
        <\/code><\/pre>\n<\/p>\n
          \n
        1. \u57fa\u672c\u4f7f\u7528\u65b9\u6cd5<\/li>\n<\/ol>\n
          matplotlib\u63d0\u4f9b\u4e86\u591a\u79cd\u7ed8\u56fe\u51fd\u6570\uff0c\u5982plot()<\/code>\u3001scatter()<\/code>\u3001bar()<\/code>\u7b49\u3002\u53ef\u4ee5\u4f7f\u7528\u8fd9\u4e9b\u51fd\u6570\u6765\u7ed8\u5236\u56fe\u5f62\uff0c\u5e76\u901a\u8fc7\u8bbe\u7f6e\u5b57\u4f53\u53c2\u6570\u6765\u663e\u793a\u6c49\u5b57\u3002<\/p>\n<\/p>\n
          import matplotlib.pyplot as plt<\/p>\n
          x = [1, 2, 3, 4]<\/p>\n
          y = [10, 20, 25, 30]<\/p>\n
          plt.plot(x, y, label='\u7ebf\u6027', color='r')<\/p>\n
          plt.title('\u4e2d\u6587\u6807\u9898')<\/p>\n
          plt.xlabel('X\u8f74')<\/p>\n
          plt.ylabel('Y\u8f74')<\/p>\n
          plt.legend()<\/p>\n
          plt.show()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
          \u4e09\u3001\u89e3\u51b3\u4e71\u7801\u95ee\u9898<\/p>\n<\/p>\n
          \u5728Python\u4e2d\u4f5c\u56fe\u65f6\u51fa\u73b0\u4e71\u7801\u95ee\u9898\uff0c\u901a\u5e38\u662f\u7531\u4e8e\u5b57\u4f53\u8bbe\u7f6e\u4e0d\u6b63\u786e\u6216\u7f16\u7801\u4e0d\u5339\u914d\u6240\u5bfc\u81f4\u3002\u4e3a\u4e86\u89e3\u51b3\u8fd9\u4e9b\u95ee\u9898\uff0c\u53ef\u4ee5\u4ece\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\u5165\u624b\u3002<\/p>\n<\/p>\n
            \n
          1. \u786e\u4fdd\u4f7f\u7528\u652f\u6301\u4e2d\u6587\u7684\u5b57\u4f53<\/li>\n<\/ol>\n
            \u786e\u4fdd\u5728\u4ee3\u7801\u4e2d\u4f7f\u7528\u7684\u5b57\u4f53\u6587\u4ef6\u652f\u6301\u4e2d\u6587\u5b57\u7b26\u3002\u5982\u679c\u9ed8\u8ba4\u5b57\u4f53\u4e0d\u652f\u6301\u4e2d\u6587\uff0c\u53ef\u4ee5\u901a\u8fc7FontProperties<\/code>\u7c7b\u6216rcParams<\/code>\u5b57\u5178\u6765\u8bbe\u7f6e\u652f\u6301\u4e2d\u6587\u7684\u5b57\u4f53\u3002<\/p>\n<\/p>\n
              \n
            1. \u68c0\u67e5\u6587\u672c\u7f16\u7801<\/li>\n<\/ol>\n
              \u786e\u4fdd\u4ee3\u7801\u6587\u4ef6\u7684\u7f16\u7801\u683c\u5f0f\u4e3aUTF-8\uff0c\u5e76\u4e14\u5728\u7ed8\u56fe\u65f6\u4f7f\u7528\u7684\u5b57\u7b26\u4e32\u4e5f\u662fUTF-8\u7f16\u7801\u3002\u53ef\u4ee5\u5728\u4ee3\u7801\u6587\u4ef6\u7684\u5f00\u5934\u6307\u5b9a\u7f16\u7801\u683c\u5f0f\uff1a<\/p>\n<\/p>\n
              # -*- coding: utf-8 -*-<\/p>\n
              <\/code><\/pre>\n<\/p>\n
                \n
              1. \u8c03\u6574\u73af\u5883\u914d\u7f6e<\/li>\n<\/ol>\n
                \u5728\u67d0\u4e9b\u60c5\u51b5\u4e0b\uff0c\u53ef\u80fd\u9700\u8981\u8c03\u6574\u73af\u5883\u914d\u7f6e\u4ee5\u652f\u6301\u4e2d\u6587\u663e\u793a\u3002\u4f8b\u5982\uff0c\u5728Jupyter Notebook\u4e2d\uff0c\u53ef\u4ee5\u901a\u8fc7\u914d\u7f6e\u6587\u4ef6\u6765\u8bbe\u7f6e\u9ed8\u8ba4\u5b57\u4f53\u3002<\/p>\n<\/p>\n
                \u56db\u3001\u5176\u4ed6\u6ce8\u610f\u4e8b\u9879<\/p>\n<\/p>\n
                \u5728Python\u4e2d\u4f5c\u56fe\u65f6\u663e\u793a\u6c49\u5b57\uff0c\u8fd8\u6709\u4e00\u4e9b\u5176\u4ed6\u6ce8\u610f\u4e8b\u9879\u9700\u8981\u8003\u8651\uff0c\u4ee5\u786e\u4fdd\u56fe\u5f62\u80fd\u591f\u6b63\u786e\u663e\u793a\u3002<\/p>\n<\/p>\n
                  \n
                1. \u64cd\u4f5c\u7cfb\u7edf\u5b57\u4f53\u652f\u6301<\/li>\n<\/ol>\n
                  \u5728\u4e0d\u540c\u64cd\u4f5c\u7cfb\u7edf\u4e0a\uff0c\u5b57\u4f53\u6587\u4ef6\u7684\u8def\u5f84\u53ef\u80fd\u4e0d\u540c\u3002\u9700\u8981\u786e\u4fdd\u5728\u4ee3\u7801\u4e2d\u6307\u5b9a\u7684\u5b57\u4f53\u6587\u4ef6\u8def\u5f84\u662f\u6b63\u786e\u7684\uff0c\u5e76\u4e14\u5bf9\u5e94\u7684\u5b57\u4f53\u6587\u4ef6\u652f\u6301\u4e2d\u6587\u663e\u793a\u3002<\/p>\n<\/p>\n
                    \n
                  1. \u5b57\u4f53\u6587\u4ef6\u7684\u8bb8\u53ef\u95ee\u9898<\/li>\n<\/ol>\n
                    \u5728\u4f7f\u7528\u67d0\u4e9b\u5b57\u4f53\u6587\u4ef6\u65f6\uff0c\u9700\u8981\u6ce8\u610f\u5176\u8bb8\u53ef\u95ee\u9898\u3002\u6709\u4e9b\u5b57\u4f53\u6587\u4ef6\u53ef\u80fd\u6709\u4f7f\u7528\u9650\u5236\uff0c\u5728\u5546\u7528\u6216\u5206\u53d1\u65f6\u9700\u8981\u9075\u5faa\u76f8\u5e94\u7684\u8bb8\u53ef\u534f\u8bae\u3002<\/p>\n<\/p>\n
                      \n
                    1. \u591a\u8bed\u8a00\u652f\u6301<\/li>\n<\/ol>\n
                      \u5982\u679c\u9700\u8981\u652f\u6301\u591a\u79cd\u8bed\u8a00\u7684\u663e\u793a\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u591a\u4e2a\u5b57\u4f53\u6765\u5b9e\u73b0\u3002\u53ef\u4ee5\u5728\u4ee3\u7801\u4e2d\u5b9a\u4e49\u591a\u4e2aFontProperties<\/code>\u5bf9\u8c61\uff0c\u5e76\u6839\u636e\u9700\u8981\u9009\u62e9\u4f7f\u7528\u4e0d\u540c\u7684\u5b57\u4f53\u3002<\/p>\n<\/p>\n
                      \u901a\u8fc7\u4ee5\u4e0a\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5728Python\u4e2d\u4f7f\u7528matplotlib\u5e93\u7ed8\u5236\u56fe\u5f62\u65f6\u6b63\u786e\u663e\u793a\u6c49\u5b57\u3002\u786e\u4fdd\u5b57\u4f53\u8bbe\u7f6e\u6b63\u786e\u3001\u6587\u672c\u7f16\u7801\u5339\u914d\uff0c\u5e76\u6839\u636e\u73af\u5883\u9700\u6c42\u8c03\u6574\u914d\u7f6e\uff0c\u53ef\u4ee5\u6709\u6548\u89e3\u51b3\u6c49\u5b57\u663e\u793a\u95ee\u9898\u3002<\/p>\n<\/p>\n
                      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                       \u5982\u4f55\u5728Python\u4f5c\u56fe\u4e2d\u663e\u793a\u6c49\u5b57\uff1f<\/strong>
                      \u5728Python\u4f5c\u56fe\u65f6\uff0c\u4f7f\u7528Matplotlib\u5e93\u53ef\u4ee5\u8f7b\u677e\u5730\u663e\u793a\u6c49\u5b57\u3002\u9700\u8981\u786e\u4fdd\u6240\u7528\u5b57\u4f53\u652f\u6301\u6c49\u5b57\u663e\u793a\u3002\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u5b57\u4f53\u53c2\u6570\u6765\u6307\u5b9a\u4e2d\u6587\u5b57\u4f53\uff0c\u4f8b\u5982\u4f7f\u7528\u201cSimHei\u201d\u6216\u201cMicrosoft YaHei\u201d\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u7b80\u5355\u7684\u793a\u4f8b\u4ee3\u7801\uff1a  <\/p>\n
                      import matplotlib.pyplot as plt\nplt.rcParams['font.sans-serif'] = ['SimHei']  # \u6307\u5b9a\u5b57\u4f53\nplt.title('\u8fd9\u662f\u6807\u9898')  # \u4e2d\u6587\u6807\u9898\nplt.plot([1, 2, 3], [1, 4, 9])\nplt.xlabel('\u6a2a\u8f74\u6807\u7b7e')  # \u4e2d\u6587\u6a2a\u8f74\u6807\u7b7e\nplt.ylabel('\u7eb5\u8f74\u6807\u7b7e')  # \u4e2d\u6587\u7eb5\u8f74\u6807\u7b7e\nplt.show()\n<\/code><\/pre>\n
                      \u5728Python\u4e2d\u5982\u4f55\u5904\u7406\u6c49\u5b57\u7f16\u7801\u95ee\u9898\uff1f<\/strong>
                      \u5904\u7406\u6c49\u5b57\u65f6\uff0c\u7f16\u7801\u95ee\u9898\u662f\u4e00\u4e2a\u5e38\u89c1\u7684\u6311\u6218\u3002\u786e\u4fdd\u4f60\u7684Python\u6587\u4ef6\u4f7f\u7528UTF-8\u7f16\u7801\uff0c\u8fd9\u6837\u53ef\u4ee5\u907f\u514d\u5f88\u591a\u5b57\u7b26\u663e\u793a\u9519\u8bef\u3002\u5728\u8bfb\u53d6\u6216\u5199\u5165\u6587\u4ef6\u65f6\uff0c\u4e5f\u5e94\u6307\u5b9a\u7f16\u7801\u4e3aUTF-8\u3002\u4f8b\u5982\uff1a  <\/p>\n
                      with open('data.txt', 'r', encoding='utf-8') as f:\n    data = f.read()\n<\/code><\/pre>\n
                      \u4f7f\u7528Python\u4f5c\u56fe\u65f6\uff0c\u5982\u4f55\u907f\u514d\u6c49\u5b57\u91cd\u53e0\uff1f<\/strong>
                      \u6c49\u5b57\u5728\u56fe\u8868\u4e2d\u53ef\u80fd\u4f1a\u56e0\u4e3a\u7a7a\u95f4\u4e0d\u8db3\u800c\u91cd\u53e0\uff0c\u5f71\u54cd\u53ef\u8bfb\u6027\u3002\u53ef\u4ee5\u901a\u8fc7\u8c03\u6574\u56fe\u8868\u7684\u5927\u5c0f\u3001\u5b57\u4f53\u5927\u5c0f\u6216\u4f7f\u7528\u65cb\u8f6c\u53c2\u6570\u6765\u89e3\u51b3\u6b64\u95ee\u9898\u3002\u4f8b\u5982\uff0c\u53ef\u4ee5\u8bbe\u7f6eplt.xticks(rotation=45)<\/code>\u6765\u65cb\u8f6cx\u8f74\u7684\u6807\u7b7e\uff0c\u907f\u514d\u91cd\u53e0\u3002\u6b64\u5916\uff0c\u589e\u5927\u56fe\u8868\u7684\u5c3a\u5bf8\u4e5f\u6709\u52a9\u4e8e\u63d0\u4f9b\u66f4\u591a\u7a7a\u95f4\u3002  <\/p>\n
                      plt.figure(figsize=(10, 5))  # \u8c03\u6574\u56fe\u5f62\u5927\u5c0f\nplt.xticks(rotation=45)  # \u65cb\u8f6cx\u8f74\u6807\u7b7e\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"\u5f00\u5934\u6bb5\u843d\uff1a\u5728Python\u4e2d\u4f5c\u56fe\u65f6\u51fa\u73b0\u6c49\u5b57\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u5b57\u4f53\u3001\u4f7f\u7528matplotlib\u5e93\u3001\u89e3\u51b3\u4e71\u7801\u95ee\u9898\u7b49\u65b9\u6cd5\u6765\u5b9e […]","protected":false},"author":3,"featured_media":954958,"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\/954954"}],"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=954954"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/954954\/revisions"}],"predecessor-version":[{"id":954961,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/954954\/revisions\/954961"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/954958"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=954954"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=954954"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=954954"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}