{"id":1024176,"date":"2024-12-30T14:11:31","date_gmt":"2024-12-30T06:11:31","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1024176.html"},"modified":"2024-12-30T14:11:34","modified_gmt":"2024-12-30T06:11:34","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e7%94%bb%e5%9b%be%e4%bb%a3%e7%a0%81-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1024176.html","title":{"rendered":"\u5982\u4f55\u7528python\u753b\u56fe\u4ee3\u7801"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u753b\u56fe\u4ee3\u7801\"<\/p>\n

\u5f00\u5934\u6bb5\u843d: \u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Seaborn\u5e93\u3001\u4f7f\u7528Plotly\u5e93\u3001\u4f7f\u7528Bokeh\u5e93\u3001\u5b66\u4e60Pygal\u5e93\u3001\u638c\u63e1\u7ed8\u56fe\u57fa\u672c\u6982\u5ff5\u3001\u7406\u89e3\u6570\u636e\u7c7b\u578b\u548c\u7ed3\u6784\u3001\u5b9e\u73b0\u591a\u79cd\u56fe\u8868\u7c7b\u578b<\/strong>\u3002\u4e3a\u4e86\u5728Python\u4e2d\u753b\u56fe\uff0c\u6700\u5e38\u7528\u7684\u5de5\u5177\u662fMatplotlib\u5e93\u3002Matplotlib\u662f\u4e00\u4e2a\u5f3a\u5927\u800c\u7075\u6d3b\u7684\u5e93\uff0c\u53ef\u4ee5\u751f\u6210\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5305\u62ec\u6298\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u3001\u67f1\u72b6\u56fe\u548c\u997c\u56fe\u3002\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u6211\u4eec\u80fd\u591f\u7cbe\u786e\u63a7\u5236\u56fe\u8868\u7684\u5916\u89c2\u548c\u884c\u4e3a\u3002\u4e0b\u9762\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Matplotlib\u5e93\u8fdb\u884c\u7ed8\u56fe\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u4f7f\u7528MATPLOTLIB\u5e93<\/p>\n<\/p>\n

Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u5b83\u7684\u529f\u80fd\u975e\u5e38\u5f3a\u5927\uff0c\u80fd\u591f\u7ed8\u5236\u591a\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4f7f\u7528Matplotlib\u5e93\u7ed8\u56fe\u7684\u57fa\u672c\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n

    \n
  1. \u5bfc\u5165Matplotlib\u5e93<\/li>\n<\/ol>\n

    \u5728\u4f7f\u7528Matplotlib\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165\u8be5\u5e93\u3002\u901a\u5e38\uff0c\u6211\u4eec\u4f1a\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165Matplotlib\u5e93\uff1a<\/p>\n<\/p>\n

    import matplotlib.pyplot as plt<\/p>\n
    <\/code><\/pre>\n<\/p>\n
      \n
    1. \u521b\u5efa\u6570\u636e<\/li>\n<\/ol>\n
      \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u7528\u4e8e\u7ed8\u56fe\u7684\u6570\u636e\u3002\u6570\u636e\u53ef\u4ee5\u662f\u5217\u8868\u3001NumPy\u6570\u7ec4\u6216Pandas\u6570\u636e\u6846\u3002\u4ee5\u4e0b\u662f\u521b\u5efa\u4e00\u4e9b\u7b80\u5355\u6570\u636e\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
      import numpy as np<\/p>\n
      x = np.linspace(0, 10, 100)<\/p>\n
      y = np.sin(x)<\/p>\n
      <\/code><\/pre>\n<\/p>\n
        \n
      1. \u521b\u5efa\u56fe\u8868<\/li>\n<\/ol>\n
        \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Matplotlib\u5e93\u4e2d\u7684\u5404\u79cd\u51fd\u6570\u6765\u521b\u5efa\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u53ca\u5176\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
          \n
        • \u6298\u7ebf\u56fe\uff1a<\/li>\n<\/ul>\n
          plt.plot(x, y)<\/p>\n
          plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
          plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
          plt.title('\u6298\u7ebf\u56fe\u6807\u9898')<\/p>\n
          plt.show()<\/p>\n
          <\/code><\/pre>\n<\/p>\n
            \n
          • \u6563\u70b9\u56fe\uff1a<\/li>\n<\/ul>\n
            plt.scatter(x, y)<\/p>\n
            plt.xlabel('X\u8f74\u6807\u7b7e')<\/p>\n
            plt.ylabel('Y\u8f74\u6807\u7b7e')<\/p>\n
            plt.title('\u6563\u70b9\u56fe\u6807\u9898')<\/p>\n
            plt.show()<\/p>\n
            <\/code><\/pre>\n<\/p>\n
              \n
            • \u67f1\u72b6\u56fe\uff1a<\/li>\n<\/ul>\n
              categories = ['A', 'B', 'C', 'D']<\/p>\n
              values = [3, 7, 5, 6]<\/p>\n
              plt.bar(categories, values)<\/p>\n
              plt.xlabel('\u7c7b\u522b')<\/p>\n
              plt.ylabel('\u503c')<\/p>\n
              plt.title('\u67f1\u72b6\u56fe\u6807\u9898')<\/p>\n
              plt.show()<\/p>\n
              <\/code><\/pre>\n<\/p>\n
                \n
              • \u997c\u56fe\uff1a<\/li>\n<\/ul>\n
                sizes = [15, 30, 45, 10]<\/p>\n
                labels = ['A', 'B', 'C', 'D']<\/p>\n
                plt.pie(sizes, labels=labels, autopct='%1.1f%%')<\/p>\n
                plt.title('\u997c\u56fe\u6807\u9898')<\/p>\n
                plt.show()<\/p>\n
                <\/code><\/pre>\n<\/p>\n
                  \n
                1. \u81ea\u5b9a\u4e49\u56fe\u8868<\/li>\n<\/ol>\n
                  Matplotlib\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u6211\u4eec\u80fd\u591f\u7cbe\u786e\u63a7\u5236\u56fe\u8868\u7684\u5916\u89c2\u548c\u884c\u4e3a\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u989c\u8272\u3001\u7ebf\u578b\u3001\u6807\u8bb0\u3001\u56fe\u4f8b\u7b49\u6765\u5b9a\u5236\u56fe\u8868\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                  plt.plot(x, y, color='red', linestyle='--', marker='o', label='\u6570\u636e1')<\/p>\n
                  plt.legend()<\/p>\n
                  plt.show()<\/p>\n
                  <\/code><\/pre>\n<\/p>\n
                  \u4e8c\u3001\u4f7f\u7528SEABORN\u5e93<\/p>\n<\/p>\n
                  Seaborn\u662f\u57fa\u4e8eMatplotlib\u7684\u53e6\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u5b83\u4f7f\u5f97\u521b\u5efa\u7f8e\u89c2\u7684\u56fe\u8868\u66f4\u52a0\u5bb9\u6613\u3002Seaborn\u5e93\u5185\u7f6e\u4e86\u8bb8\u591a\u9ed8\u8ba4\u8bbe\u7f6e\uff0c\u4f7f\u56fe\u8868\u66f4\u52a0\u7f8e\u89c2\u3002\u4f7f\u7528Seaborn\u5e93\u7ed8\u56fe\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                    \n
                  1. \u5bfc\u5165Seaborn\u5e93<\/li>\n<\/ol>\n
                    \u5728\u4f7f\u7528Seaborn\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165\u8be5\u5e93\u3002\u901a\u5e38\uff0c\u6211\u4eec\u4f1a\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165Seaborn\u5e93\uff1a<\/p>\n<\/p>\n
                    import seaborn as sns<\/p>\n
                    <\/code><\/pre>\n<\/p>\n
                      \n
                    1. \u52a0\u8f7d\u6570\u636e\u96c6<\/li>\n<\/ol>\n
                      Seaborn\u5e93\u5185\u7f6e\u4e86\u4e00\u4e9b\u5e38\u7528\u7684\u6570\u636e\u96c6\uff0c\u6211\u4eec\u53ef\u4ee5\u76f4\u63a5\u52a0\u8f7d\u8fd9\u4e9b\u6570\u636e\u96c6\u8fdb\u884c\u7ed8\u56fe\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                      data = sns.load_dataset('tips')<\/p>\n
                      <\/code><\/pre>\n<\/p>\n
                        \n
                      1. \u521b\u5efa\u56fe\u8868<\/li>\n<\/ol>\n
                        \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Seaborn\u5e93\u4e2d\u7684\u5404\u79cd\u51fd\u6570\u6765\u521b\u5efa\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u53ca\u5176\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
                          \n
                        • \u6298\u7ebf\u56fe\uff1a<\/li>\n<\/ul>\n
                          sns.lineplot(x='total_bill', y='tip', data=data)<\/p>\n
                          plt.xlabel('\u603b\u8d26\u5355')<\/p>\n
                          plt.ylabel('\u5c0f\u8d39')<\/p>\n
                          plt.title('\u6298\u7ebf\u56fe\u6807\u9898')<\/p>\n
                          plt.show()<\/p>\n
                          <\/code><\/pre>\n<\/p>\n
                            \n
                          • \u6563\u70b9\u56fe\uff1a<\/li>\n<\/ul>\n
                            sns.scatterplot(x='total_bill', y='tip', data=data)<\/p>\n
                            plt.xlabel('\u603b\u8d26\u5355')<\/p>\n
                            plt.ylabel('\u5c0f\u8d39')<\/p>\n
                            plt.title('\u6563\u70b9\u56fe\u6807\u9898')<\/p>\n
                            plt.show()<\/p>\n
                            <\/code><\/pre>\n<\/p>\n
                              \n
                            • \u67f1\u72b6\u56fe\uff1a<\/li>\n<\/ul>\n
                              sns.barplot(x='day', y='total_bill', data=data)<\/p>\n
                              plt.xlabel('\u661f\u671f\u51e0')<\/p>\n
                              plt.ylabel('\u603b\u8d26\u5355')<\/p>\n
                              plt.title('\u67f1\u72b6\u56fe\u6807\u9898')<\/p>\n
                              plt.show()<\/p>\n
                              <\/code><\/pre>\n<\/p>\n
                                \n
                              • \u7bb1\u7ebf\u56fe\uff1a<\/li>\n<\/ul>\n
                                sns.boxplot(x='day', y='total_bill', data=data)<\/p>\n
                                plt.xlabel('\u661f\u671f\u51e0')<\/p>\n
                                plt.ylabel('\u603b\u8d26\u5355')<\/p>\n
                                plt.title('\u7bb1\u7ebf\u56fe\u6807\u9898')<\/p>\n
                                plt.show()<\/p>\n
                                <\/code><\/pre>\n<\/p>\n
                                  \n
                                1. \u81ea\u5b9a\u4e49\u56fe\u8868<\/li>\n<\/ol>\n
                                  Seaborn\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u6211\u4eec\u80fd\u591f\u7cbe\u786e\u63a7\u5236\u56fe\u8868\u7684\u5916\u89c2\u548c\u884c\u4e3a\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u989c\u8272\u3001\u6837\u5f0f\u3001\u5927\u5c0f\u7b49\u6765\u5b9a\u5236\u56fe\u8868\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                                  sns.set(style='whitegrid')<\/p>\n
                                  sns.lineplot(x='total_bill', y='tip', data=data, hue='sex', style='sex', markers=True)<\/p>\n
                                  plt.show()<\/p>\n
                                  <\/code><\/pre>\n<\/p>\n
                                  \u4e09\u3001\u4f7f\u7528PLOTLY\u5e93<\/p>\n<\/p>\n
                                  Plotly\u662f\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\u4e14\u4ea4\u4e92\u6027\u5f3a\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\u3002\u4f7f\u7528Plotly\u5e93\uff0c\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u4ea4\u4e92\u5f0f\u56fe\u8868\uff0c\u5305\u62ec\u6298\u7ebf\u56fe\u3001\u6563\u70b9\u56fe\u3001\u67f1\u72b6\u56fe\u548c\u997c\u56fe\u3002\u4f7f\u7528Plotly\u5e93\u7ed8\u56fe\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                                    \n
                                  1. \u5bfc\u5165Plotly\u5e93<\/li>\n<\/ol>\n
                                    \u5728\u4f7f\u7528Plotly\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165\u8be5\u5e93\u3002\u901a\u5e38\uff0c\u6211\u4eec\u4f1a\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165Plotly\u5e93\uff1a<\/p>\n<\/p>\n
                                    import plotly.express as px<\/p>\n
                                    <\/code><\/pre>\n<\/p>\n
                                      \n
                                    1. \u521b\u5efa\u6570\u636e<\/li>\n<\/ol>\n
                                      \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u7528\u4e8e\u7ed8\u56fe\u7684\u6570\u636e\u3002\u6570\u636e\u53ef\u4ee5\u662fPandas\u6570\u636e\u6846\u6216\u5176\u4ed6\u683c\u5f0f\u3002\u4ee5\u4e0b\u662f\u521b\u5efa\u4e00\u4e9b\u7b80\u5355\u6570\u636e\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
                                      import pandas as pd<\/p>\n
                                      data = pd.DataFrame({<\/p>\n
                                          'x': range(10),<\/p>\n
                                          'y': [1, 3, 2, 4, 3, 5, 4, 6, 5, 7]<\/p>\n
                                      })<\/p>\n
                                      <\/code><\/pre>\n<\/p>\n
                                        \n
                                      1. \u521b\u5efa\u56fe\u8868<\/li>\n<\/ol>\n
                                        \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Plotly\u5e93\u4e2d\u7684\u5404\u79cd\u51fd\u6570\u6765\u521b\u5efa\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u53ca\u5176\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
                                          \n
                                        • \u6298\u7ebf\u56fe\uff1a<\/li>\n<\/ul>\n
                                          fig = px.line(data, x='x', y='y', title='\u6298\u7ebf\u56fe\u6807\u9898')<\/p>\n
                                          fig.show()<\/p>\n
                                          <\/code><\/pre>\n<\/p>\n
                                            \n
                                          • \u6563\u70b9\u56fe\uff1a<\/li>\n<\/ul>\n
                                            fig = px.scatter(data, x='x', y='y', title='\u6563\u70b9\u56fe\u6807\u9898')<\/p>\n
                                            fig.show()<\/p>\n
                                            <\/code><\/pre>\n<\/p>\n
                                              \n
                                            • \u67f1\u72b6\u56fe\uff1a<\/li>\n<\/ul>\n
                                              fig = px.bar(data, x='x', y='y', title='\u67f1\u72b6\u56fe\u6807\u9898')<\/p>\n
                                              fig.show()<\/p>\n
                                              <\/code><\/pre>\n<\/p>\n
                                                \n
                                              • \u997c\u56fe\uff1a<\/li>\n<\/ul>\n
                                                labels = ['A', 'B', 'C', 'D']<\/p>\n
                                                values = [15, 30, 45, 10]<\/p>\n
                                                fig = px.pie(names=labels, values=values, title='\u997c\u56fe\u6807\u9898')<\/p>\n
                                                fig.show()<\/p>\n
                                                <\/code><\/pre>\n<\/p>\n
                                                  \n
                                                1. \u81ea\u5b9a\u4e49\u56fe\u8868<\/li>\n<\/ol>\n
                                                  Plotly\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u6211\u4eec\u80fd\u591f\u7cbe\u786e\u63a7\u5236\u56fe\u8868\u7684\u5916\u89c2\u548c\u884c\u4e3a\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u989c\u8272\u3001\u6837\u5f0f\u3001\u5927\u5c0f\u7b49\u6765\u5b9a\u5236\u56fe\u8868\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                                                  fig = px.line(data, x='x', y='y', title='\u6298\u7ebf\u56fe\u6807\u9898', color_discrete_sequence=['red'])<\/p>\n
                                                  fig.update_layout(xaxis_title='X\u8f74\u6807\u7b7e', yaxis_title='Y\u8f74\u6807\u7b7e')<\/p>\n
                                                  fig.show()<\/p>\n
                                                  <\/code><\/pre>\n<\/p>\n
                                                  \u56db\u3001\u4f7f\u7528BOKEH\u5e93<\/p>\n<\/p>\n
                                                  Bokeh\u662f\u4e00\u4e2a\u7528\u4e8e\u521b\u5efa\u4ea4\u4e92\u5f0f\u548c\u53ef\u89c6\u5316\u56fe\u8868\u7684Python\u5e93\u3002\u5b83\u4f7f\u5f97\u5728\u7f51\u9875\u4e0a\u5d4c\u5165\u9ad8\u6548\u3001\u6f02\u4eae\u7684\u56fe\u8868\u53d8\u5f97\u66f4\u52a0\u5bb9\u6613\u3002\u4f7f\u7528Bokeh\u5e93\u7ed8\u56fe\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                                                    \n
                                                  1. \u5bfc\u5165Bokeh\u5e93<\/li>\n<\/ol>\n
                                                    \u5728\u4f7f\u7528Bokeh\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165\u8be5\u5e93\u3002\u901a\u5e38\uff0c\u6211\u4eec\u4f1a\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165Bokeh\u5e93\uff1a<\/p>\n<\/p>\n
                                                    from bokeh.plotting import figure, show<\/p>\n
                                                    <\/code><\/pre>\n<\/p>\n
                                                      \n
                                                    1. \u521b\u5efa\u6570\u636e<\/li>\n<\/ol>\n
                                                      \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u7528\u4e8e\u7ed8\u56fe\u7684\u6570\u636e\u3002\u6570\u636e\u53ef\u4ee5\u662f\u5217\u8868\u3001NumPy\u6570\u7ec4\u6216Pandas\u6570\u636e\u6846\u3002\u4ee5\u4e0b\u662f\u521b\u5efa\u4e00\u4e9b\u7b80\u5355\u6570\u636e\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
                                                      x = [1, 2, 3, 4, 5]<\/p>\n
                                                      y = [6, 7, 2, 4, 5]<\/p>\n
                                                      <\/code><\/pre>\n<\/p>\n
                                                        \n
                                                      1. \u521b\u5efa\u56fe\u8868<\/li>\n<\/ol>\n
                                                        \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Bokeh\u5e93\u4e2d\u7684\u5404\u79cd\u51fd\u6570\u6765\u521b\u5efa\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u53ca\u5176\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
                                                          \n
                                                        • \u6298\u7ebf\u56fe\uff1a<\/li>\n<\/ul>\n
                                                          p = figure(title='\u6298\u7ebf\u56fe\u6807\u9898', x_axis_label='X\u8f74\u6807\u7b7e', y_axis_label='Y\u8f74\u6807\u7b7e')<\/p>\n
                                                          p.line(x, y, legend_label='\u6570\u636e1', line_width=2)<\/p>\n
                                                          show(p)<\/p>\n
                                                          <\/code><\/pre>\n<\/p>\n
                                                            \n
                                                          • \u6563\u70b9\u56fe\uff1a<\/li>\n<\/ul>\n
                                                            p = figure(title='\u6563\u70b9\u56fe\u6807\u9898', x_axis_label='X\u8f74\u6807\u7b7e', y_axis_label='Y\u8f74\u6807\u7b7e')<\/p>\n
                                                            p.circle(x, y, size=10, color='navy', alpha=0.5)<\/p>\n
                                                            show(p)<\/p>\n
                                                            <\/code><\/pre>\n<\/p>\n
                                                              \n
                                                            • \u67f1\u72b6\u56fe\uff1a<\/li>\n<\/ul>\n
                                                              from bokeh.io import output_file<\/p>\n
                                                              from bokeh.plotting import figure, show<\/p>\n
                                                              output_file("bars.html")<\/p>\n
                                                              p = figure(x_range=categories, title="\u67f1\u72b6\u56fe\u6807\u9898",<\/p>\n
                                                                         toolbar_location=None, tools="")<\/p>\n
                                                              p.vbar(x=categories, top=values, width=0.9)<\/p>\n
                                                              show(p)<\/p>\n
                                                              <\/code><\/pre>\n<\/p>\n
                                                                \n
                                                              • \u997c\u56fe\uff1a<\/li>\n<\/ul>\n
                                                                from math import pi<\/p>\n
                                                                from bokeh.palettes import Category20c<\/p>\n
                                                                from bokeh.transform import cumsum<\/p>\n
                                                                data = pd.Series(values, index=labels).reset_index(name='value').rename(columns={'index': 'label'})<\/p>\n
                                                                data['angle'] = data['value']\/data['value'].sum() * 2*pi<\/p>\n
                                                                data['color'] = Category20c[len(data)]<\/p>\n
                                                                p = figure(plot_height=350, title="\u997c\u56fe\u6807\u9898", toolbar_location=None,<\/p>\n
                                                                           tools="hover", tooltips="@label: @value", x_range=(-0.5, 1.0))<\/p>\n
                                                                p.wedge(x=0, y=1, radius=0.4, <\/p>\n
                                                                        start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'),<\/p>\n
                                                                        line_color="white", fill_color='color', legend_field='label', source=data)<\/p>\n
                                                                show(p)<\/p>\n
                                                                <\/code><\/pre>\n<\/p>\n
                                                                  \n
                                                                1. \u81ea\u5b9a\u4e49\u56fe\u8868<\/li>\n<\/ol>\n
                                                                  Bokeh\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u6211\u4eec\u80fd\u591f\u7cbe\u786e\u63a7\u5236\u56fe\u8868\u7684\u5916\u89c2\u548c\u884c\u4e3a\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u989c\u8272\u3001\u6837\u5f0f\u3001\u5927\u5c0f\u7b49\u6765\u5b9a\u5236\u56fe\u8868\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                                                                  p = figure(title='\u6298\u7ebf\u56fe\u6807\u9898', x_axis_label='X\u8f74\u6807\u7b7e', y_axis_label='Y\u8f74\u6807\u7b7e')<\/p>\n
                                                                  p.line(x, y, legend_label='\u6570\u636e1', line_width=2, line_color='green', line_dash='dashed')<\/p>\n
                                                                  show(p)<\/p>\n
                                                                  <\/code><\/pre>\n<\/p>\n
                                                                  \u4e94\u3001\u5b66\u4e60PYGAL\u5e93<\/p>\n<\/p>\n
                                                                  Pygal\u662f\u4e00\u4e2a\u7528\u4e8e\u751f\u6210SVG\u56fe\u8868\u7684Python\u5e93\u3002\u5b83\u4f7f\u5f97\u521b\u5efa\u9ad8\u8d28\u91cf\u7684SVG\u56fe\u8868\u53d8\u5f97\u975e\u5e38\u5bb9\u6613\u3002\u4f7f\u7528Pygal\u5e93\u7ed8\u56fe\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/p>\n<\/p>\n
                                                                    \n
                                                                  1. \u5bfc\u5165Pygal\u5e93<\/li>\n<\/ol>\n
                                                                    \u5728\u4f7f\u7528Pygal\u5e93\u4e4b\u524d\uff0c\u9996\u5148\u9700\u8981\u5bfc\u5165\u8be5\u5e93\u3002\u901a\u5e38\uff0c\u6211\u4eec\u4f1a\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u5bfc\u5165Pygal\u5e93\uff1a<\/p>\n<\/p>\n
                                                                    import pygal<\/p>\n
                                                                    <\/code><\/pre>\n<\/p>\n
                                                                      \n
                                                                    1. \u521b\u5efa\u6570\u636e<\/li>\n<\/ol>\n
                                                                      \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u9700\u8981\u521b\u5efa\u7528\u4e8e\u7ed8\u56fe\u7684\u6570\u636e\u3002\u6570\u636e\u53ef\u4ee5\u662f\u5217\u8868\u3001\u5b57\u5178\u7b49\u3002\u4ee5\u4e0b\u662f\u521b\u5efa\u4e00\u4e9b\u7b80\u5355\u6570\u636e\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n
                                                                      data = [1, 3, 2, 5, 4]<\/p>\n
                                                                      <\/code><\/pre>\n<\/p>\n
                                                                        \n
                                                                      1. \u521b\u5efa\u56fe\u8868<\/li>\n<\/ol>\n
                                                                        \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Pygal\u5e93\u4e2d\u7684\u5404\u79cd\u7c7b\u6765\u521b\u5efa\u4e0d\u540c\u7c7b\u578b\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u53ca\u5176\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
                                                                          \n
                                                                        • \u6298\u7ebf\u56fe\uff1a<\/li>\n<\/ul>\n
                                                                          line_chart = pygal.Line()<\/p>\n
                                                                          line_chart.title = '\u6298\u7ebf\u56fe\u6807\u9898'<\/p>\n
                                                                          line_chart.x_labels = map(str, range(1, 6))<\/p>\n
                                                                          line_chart.add('\u6570\u636e1', data)<\/p>\n
                                                                          line_chart.render_to_file('line_chart.svg')<\/p>\n
                                                                          <\/code><\/pre>\n<\/p>\n
                                                                            \n
                                                                          • \u67f1\u72b6\u56fe\uff1a<\/li>\n<\/ul>\n
                                                                            bar_chart = pygal.Bar()<\/p>\n
                                                                            bar_chart.title = '\u67f1\u72b6\u56fe\u6807\u9898'<\/p>\n
                                                                            bar_chart.x_labels = ['A', 'B', 'C', 'D']<\/p>\n
                                                                            bar_chart.add('\u6570\u636e1', [1, 3, 2, 5])<\/p>\n
                                                                            bar_chart.render_to_file('bar_chart.svg')<\/p>\n
                                                                            <\/code><\/pre>\n<\/p>\n
                                                                              \n
                                                                            • \u997c\u56fe\uff1a<\/li>\n<\/ul>\n
                                                                              pie_chart = pygal.Pie()<\/p>\n
                                                                              pie_chart.title = '\u997c\u56fe\u6807\u9898'<\/p>\n
                                                                              pie_chart.add('A', 15)<\/p>\n
                                                                              pie_chart.add('B', 30)<\/p>\n
                                                                              pie_chart.add('C', 45)<\/p>\n
                                                                              pie_chart.add('D', 10)<\/p>\n
                                                                              pie_chart.render_to_file('pie_chart.svg')<\/p>\n
                                                                              <\/code><\/pre>\n<\/p>\n
                                                                                \n
                                                                              1. \u81ea\u5b9a\u4e49\u56fe\u8868<\/li>\n<\/ol>\n
                                                                                Pygal\u5e93\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u81ea\u5b9a\u4e49\u9009\u9879\uff0c\u4f7f\u6211\u4eec\u80fd\u591f\u7cbe\u786e\u63a7\u5236\u56fe\u8868\u7684\u5916\u89c2\u548c\u884c\u4e3a\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u989c\u8272\u3001\u6837\u5f0f\u3001\u5927\u5c0f\u7b49\u6765\u5b9a\u5236\u56fe\u8868\u3002\u4f8b\u5982\uff1a<\/p>\n<\/p>\n
                                                                                line_chart = pygal.Line()<\/p>\n
                                                                                line_chart.title = '\u6298\u7ebf\u56fe\u6807\u9898'<\/p>\n
                                                                                line_chart.x_labels = map(str, range(1, 6))<\/p>\n
                                                                                line_chart.add('\u6570\u636e1', data, stroke_style={'width': 2, 'dasharray': '5, 5'}, dots_size=5)<\/p>\n
                                                                                line_chart.render_to_file('custom_line_chart.svg')<\/p>\n
                                                                                <\/code><\/pre>\n<\/p>\n
                                                                                \u516d\u3001\u638c\u63e1\u7ed8\u56fe\u57fa\u672c\u6982\u5ff5<\/p>\n<\/p>\n
                                                                                \u5728\u4f7f\u7528\u8fd9\u4e9b\u7ed8\u56fe\u5e93\u4e4b\u524d\uff0c\u638c\u63e1\u4e00\u4e9b\u7ed8\u56fe\u7684\u57fa\u672c\u6982\u5ff5\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u8fd9\u4e9b\u6982\u5ff5\u5305\u62ec\uff1a<\/p>\n<\/p>\n
                                                                                  \n
                                                                                • \u5750\u6807\u8f74\uff1a\u56fe\u8868\u7684X\u8f74\u548cY\u8f74\uff0c\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u7ef4\u5ea6\u3002<\/li>\n
                                                                                • \u6570\u636e\u70b9\uff1a\u5728\u56fe\u8868\u4e0a\u7684\u6bcf\u4e00\u4e2a\u70b9\uff0c\u8868\u793a\u6570\u636e\u7684\u4e00\u4e2a\u89c2\u6d4b\u503c\u3002<\/li>\n
                                                                                • \u6807\u8bb0\uff1a\u7528\u4e8e\u6807\u8bc6\u6570\u636e\u70b9\u7684\u7b26\u53f7\uff0c\u5982\u5706\u5708\u3001\u65b9\u5757\u7b49\u3002<\/li>\n
                                                                                • \u7ebf\u578b\uff1a\u7528\u4e8e\u8fde\u63a5\u6570\u636e\u70b9\u7684\u7ebf\u6761\uff0c\u5982\u5b9e\u7ebf\u3001\u865a\u7ebf\u7b49\u3002<\/li>\n
                                                                                • \u989c\u8272\uff1a\u7528\u4e8e\u533a\u5206\u4e0d\u540c\u6570\u636e\u96c6\u6216\u7c7b\u522b\u7684\u989c\u8272\u3002<\/li>\n
                                                                                • \u56fe\u4f8b\uff1a\u7528\u4e8e\u8bf4\u660e\u4e0d\u540c\u6570\u636e\u96c6\u6216\u7c7b\u522b\u7684\u6807\u7b7e\u3002<\/li>\n
                                                                                • \u6807\u9898\uff1a\u56fe\u8868\u7684\u6807\u9898\uff0c\u7528\u4e8e\u63cf\u8ff0\u56fe\u8868\u7684\u5185\u5bb9\u3002<\/li>\n
                                                                                • \u6807\u7b7e\uff1a\u5750\u6807\u8f74\u7684\u6807\u7b7e\uff0c\u7528\u4e8e\u63cf\u8ff0\u6570\u636e\u7684\u7ef4\u5ea6\u3002<\/li>\n<\/ul>\n
                                                                                  \u4e03\u3001\u7406\u89e3\u6570\u636e\u7c7b\u578b\u548c\u7ed3\u6784<\/p>\n<\/p>\n
                                                                                  \u5728\u4f7f\u7528\u8fd9\u4e9b\u7ed8\u56fe\u5e93\u4e4b\u524d\uff0c\u7406\u89e3\u6570\u636e\u7684\u7c7b\u578b\u548c\u7ed3\u6784\u4e5f\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u8fd9\u4e9b\u6570\u636e\u7c7b\u578b\u548c\u7ed3\u6784\u5305\u62ec\uff1a<\/p>\n<\/p>\n
                                                                                    \n
                                                                                  • \u5217\u8868\uff1a\u4e00\u79cd\u6709\u5e8f\u7684\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u4e00\u7ec4\u6570\u636e\u3002<\/li>\n
                                                                                  • \u5b57\u5178\uff1a\u4e00\u79cd\u952e\u503c\u5bf9\u7684\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u4e00\u7ec4\u6570\u636e\u3002<\/li>\n
                                                                                  • NumPy\u6570\u7ec4\uff1a\u4e00\u79cd\u9ad8\u6548\u7684\u591a\u7ef4\u6570\u7ec4\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u548c\u64cd\u4f5c\u6570\u503c\u6570\u636e\u3002<\/li>\n
                                                                                  • Pandas\u6570\u636e\u6846\uff1a\u4e00\u79cd\u7c7b\u4f3c\u4e8e\u8868\u683c\u7684\u6570\u636e\u7ed3\u6784\uff0c\u7528\u4e8e\u5b58\u50a8\u548c\u64cd\u4f5c\u7ed3\u6784\u5316\u6570\u636e\u3002<\/li>\n<\/ul>\n
                                                                                    \u516b\u3001\u5b9e\u73b0\u591a\u79cd\u56fe\u8868\u7c7b\u578b<\/p>\n<\/p>\n
                                                                                    \u5728\u4f7f\u7528\u8fd9\u4e9b\u7ed8\u56fe\u5e93\u65f6\uff0c\u4e86\u89e3\u5982\u4f55\u5b9e\u73b0\u591a\u79cd\u56fe\u8868\u7c7b\u578b\u662f\u975e\u5e38\u91cd\u8981\u7684\u3002\u5e38\u89c1\u7684\u56fe\u8868\u7c7b\u578b\u5305\u62ec\uff1a<\/p>\n<\/p>\n
                                                                                      \n
                                                                                    • \u6298\u7ebf\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u53d8\u5316\u8d8b\u52bf\u3002<\/li>\n
                                                                                    • \u6563\u70b9\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u5206\u5e03\u548c\u5173\u7cfb\u3002<\/li>\n
                                                                                    • \u67f1\u72b6\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u6bd4\u8f83\u3002<\/li>\n
                                                                                    • \u997c\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u7ec4\u6210\u3002<\/li>\n
                                                                                    • \u7bb1\u7ebf\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u5206\u5e03\u548c\u5f02\u5e38\u503c\u3002<\/li>\n
                                                                                    • \u70ed\u529b\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u5bc6\u5ea6\u548c\u76f8\u5173\u6027\u3002<\/li>\n
                                                                                    • \u76f4\u65b9\u56fe\uff1a\u7528\u4e8e\u8868\u793a\u6570\u636e\u7684\u5206\u5e03\u3002<\/li>\n<\/ul>\n
                                                                                      \u901a\u8fc7\u5b66\u4e60\u548c\u638c\u63e1\u8fd9\u4e9b\u7ed8\u56fe\u5e93\u7684\u4f7f\u7528\u65b9\u6cd5\u548c\u57fa\u672c\u6982\u5ff5\uff0c\u6211\u4eec\u53ef\u4ee5\u5728Python\u4e2d\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u4ece\u800c\u66f4\u597d\u5730\u7406\u89e3\u548c\u5c55\u793a\u6570\u636e\u3002<\/p>\n<\/p>\n
                                                                                      \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
                                                                                       \u5982\u4f55\u9009\u62e9\u5408\u9002\u7684Python\u5e93\u8fdb\u884c\u7ed8\u56fe\uff1f<\/strong>
                                                                                      \u5728Python\u4e2d\uff0c\u6709\u591a\u4e2a\u7ed8\u56fe\u5e93\u53ef\u4ee5\u9009\u62e9\uff0c\u5305\u62ecMatplotlib\u3001Seaborn\u548cPlotly\u7b49\u3002Matplotlib\u662f\u57fa\u7840\u5e93\uff0c\u9002\u5408\u7b80\u5355\u7684\u7ed8\u56fe\u9700\u6c42\uff1bSeaborn\u5219\u662f\u5728Matplotlib\u57fa\u7840\u4e0a\u8fdb\u884c\u7f8e\u5316\uff0c\u9002\u5408\u7edf\u8ba1\u56fe\u8868\u7684\u7ed8\u5236\uff1b\u800cPlotly\u5219\u63d0\u4f9b\u4ea4\u4e92\u5f0f\u56fe\u8868\uff0c\u9002\u5408\u9700\u8981\u52a8\u6001\u5c55\u793a\u6570\u636e\u7684\u573a\u5408\u3002\u6839\u636e\u4f60\u7684\u9700\u6c42\u9009\u62e9\u5408\u9002\u7684\u5e93\u5c06\u5927\u5927\u63d0\u9ad8\u7ed8\u56fe\u6548\u7387\u3002<\/p>\n
                                                                                      Python\u7ed8\u56fe\u65f6\u5982\u4f55\u8c03\u6574\u56fe\u8868\u7684\u6837\u5f0f\u548c\u989c\u8272\uff1f<\/strong>
                                                                                      \u8c03\u6574\u56fe\u8868\u7684\u6837\u5f0f\u548c\u989c\u8272\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u56fe\u8868\u7684\u53c2\u6570\u6765\u5b9e\u73b0\u3002\u4ee5Matplotlib\u4e3a\u4f8b\uff0c\u53ef\u4ee5\u4f7f\u7528plt.style.use()<\/code>\u51fd\u6570\u6765\u5e94\u7528\u4e0d\u540c\u7684\u6837\u5f0f\uff0c\u6bd4\u5982ggplot<\/code>\u6216seaborn<\/code>\u3002\u989c\u8272\u65b9\u9762\uff0c\u53ef\u4ee5\u901a\u8fc7color<\/code>\u53c2\u6570\u8bbe\u7f6e\u5355\u4e00\u989c\u8272\uff0c\u6216\u4f7f\u7528\u8c03\u8272\u677f\u6765\u8bbe\u7f6e\u591a\u4e2a\u989c\u8272\uff0c\u4f8b\u5982\u4f7f\u7528sns.color_palette()<\/code>\u3002\u8fd9\u4e9b\u8bbe\u7f6e\u80fd\u8ba9\u4f60\u7684\u56fe\u8868\u66f4\u52a0\u7f8e\u89c2\u548c\u6613\u4e8e\u9605\u8bfb\u3002<\/p>\n
                                                                                      \u5982\u4f55\u5c06Python\u7ed8\u5236\u7684\u56fe\u8868\u4fdd\u5b58\u4e3a\u56fe\u7247\u6587\u4ef6\uff1f<\/strong>
                                                                                      \u5728\u4f7f\u7528Matplotlib\u8fdb\u884c\u7ed8\u56fe\u540e\uff0c\u53ef\u4ee5\u901a\u8fc7plt.savefig('filename.png')<\/code>\u5c06\u56fe\u8868\u4fdd\u5b58\u4e3a\u56fe\u7247\u6587\u4ef6\u3002\u53ef\u4ee5\u6307\u5b9a\u6587\u4ef6\u683c\u5f0f\uff0c\u5982PNG\u3001JPG\u7b49\u3002\u6b64\u5916\uff0c\u4fdd\u5b58\u65f6\u53ef\u4ee5\u8bbe\u7f6e\u56fe\u50cf\u7684\u5206\u8fa8\u7387\uff0c\u901a\u8fc7dpi<\/code>\u53c2\u6570\u63d0\u9ad8\u56fe\u7247\u7684\u6e05\u6670\u5ea6\uff0c\u786e\u4fdd\u56fe\u8868\u5728\u4e0d\u540c\u5e73\u53f0\u4e0a\u7684\u5c55\u793a\u6548\u679c\u90fd\u80fd\u8fbe\u5230\u6700\u4f73\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5f00\u5934\u6bb5\u843d: \u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Seaborn\u5e93\u3001\u4f7f\u7528Plotly\u5e93\u3001\u4f7f\u7528Bokeh\u5e93\u3001\u5b66\u4e60Pyg […]","protected":false},"author":3,"featured_media":1024187,"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\/1024176"}],"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=1024176"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1024176\/revisions"}],"predecessor-version":[{"id":1024190,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1024176\/revisions\/1024190"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1024187"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1024176"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1024176"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1024176"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}