{"id":890,"date":"2025-01-11T15:53:22","date_gmt":"2025-01-11T07:53:22","guid":{"rendered":"https:\/\/www.laixuexila.com\/?p=890"},"modified":"2025-01-11T15:53:22","modified_gmt":"2025-01-11T07:53:22","slug":"%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8python%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e5%8f%af%e8%a7%86%e5%8c%96%ef%bc%9a%e5%b7%a5%e5%85%b7%e4%b8%8e%e6%8a%80%e6%9c%af%e8%a7%a3%e6%9e%90","status":"publish","type":"post","link":"https:\/\/www.laixuexila.com\/index.php\/2025\/01\/11\/%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8python%e8%bf%9b%e8%a1%8c%e6%95%b0%e6%8d%ae%e5%8f%af%e8%a7%86%e5%8c%96%ef%bc%9a%e5%b7%a5%e5%85%b7%e4%b8%8e%e6%8a%80%e6%9c%af%e8%a7%a3%e6%9e%90\/","title":{"rendered":"\u5982\u4f55\u4f7f\u7528Python\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\uff1a\u5de5\u5177\u4e0e\u6280\u672f\u89e3\u6790"},"content":{"rendered":"\n
\n

\u6570\u636e\u53ef\u89c6\u5316\u662f\u6570\u636e\u5206\u6790\u4e2d\u7684\u4e00\u4e2a\u91cd\u8981\u73af\u8282\uff0c\u5b83\u901a\u8fc7\u56fe\u5f62\u5316\u7684\u65b9\u5f0f\u5e2e\u52a9\u6211\u4eec\u7406\u89e3\u548c\u5c55\u793a\u6570\u636e\u7684\u8d8b\u52bf\u3001\u6a21\u5f0f\u3001\u5173\u7cfb\u7b49\u3002\u5728 Python \u4e2d\uff0c\u6570\u636e\u53ef\u89c6\u5316\u6709\u5f88\u591a\u5f3a\u5927\u7684\u5de5\u5177\u548c\u6280\u672f\uff0c\u4e0b\u9762\u6211\u5c06\u4ecb\u7ecd\u5e38\u7528\u7684 Python \u53ef\u89c6\u5316\u5de5\u5177\u53ca\u5176\u5e94\u7528\uff0c\u5305\u62ec\u5982\u4f55\u4f7f\u7528\u5b83\u4eec\u8fdb\u884c\u5e38\u89c1\u7684\u6570\u636e\u53ef\u89c6\u5316\u4efb\u52a1\u3002<\/p>\n<\/blockquote>\n\n\n\n

1. \u5e38\u7528\u7684 Python \u6570\u636e\u53ef\u89c6\u5316\u5de5\u5177<\/h2>\n\n\n\n

1.1 Matplotlib<\/strong><\/h3>\n\n\n\n

Matplotlib<\/strong> \u662f Python \u4e2d\u6700\u57fa\u7840\u548c\u6700\u5e7f\u6cdb\u4f7f\u7528\u7684\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u529f\u80fd\u5f3a\u5927\uff0c\u652f\u6301\u591a\u79cd\u56fe\u5f62\u7c7b\u578b\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u3001\u76f4\u65b9\u56fe\u7b49\u3002<\/p>\n\n\n\n

    \n
  • \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
      pip install matplotlib<\/code><\/pre>\n\n\n\n
      \n
    • \u5e38\u89c1\u56fe\u5f62\u7c7b\u578b<\/strong>\uff1a<\/li>\n\n\n\n
    • \u6298\u7ebf\u56fe\uff08Line Plot\uff09<\/li>\n\n\n\n
    • \u6563\u70b9\u56fe\uff08Scatter Plot\uff09<\/li>\n\n\n\n
    • \u76f4\u65b9\u56fe\uff08Histogram\uff09<\/li>\n\n\n\n
    • \u67f1\u72b6\u56fe\uff08Bar Plot\uff09<\/li>\n\n\n\n
    • \u997c\u56fe\uff08Pie Chart\uff09<\/li>\n<\/ul>\n\n\n\n
      \u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a<\/p>\n\n\n\n
      import matplotlib.pyplot as plt\n\n# \u7b80\u5355\u7684\u6298\u7ebf\u56fe\nx = [1, 2, 3, 4, 5]\ny = [1, 4, 9, 16, 25]\n\nplt.plot(x, y)\nplt.title(\"Simple Line Plot\")\nplt.xlabel(\"X Axis\")\nplt.ylabel(\"Y Axis\")\nplt.show()\n\n# \u7b80\u5355\u7684\u6563\u70b9\u56fe\nplt.scatter(x, y, color='r')\nplt.title(\"Simple Scatter Plot\")\nplt.xlabel(\"X Axis\")\nplt.ylabel(\"Y Axis\")\nplt.show()<\/code><\/pre>\n\n\n\n
      1.2 Seaborn<\/strong><\/h3>\n\n\n\n
      Seaborn<\/strong> \u57fa\u4e8e Matplotlib\uff0c\u63d0\u4f9b\u4e86\u66f4\u4e3a\u9ad8\u7ea7\u548c\u7f8e\u89c2\u7684\u56fe\u5f62\uff0c\u5c24\u5176\u64c5\u957f\u5904\u7406\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u5f62\u3002Seaborn \u53ef\u4ee5\u66f4\u5bb9\u6613\u5730\u7ed8\u5236\u70ed\u529b\u56fe\u3001\u5206\u7c7b\u56fe\u548c\u56de\u5f52\u56fe\u3002<\/p>\n\n\n\n
        \n
      • \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
          pip install seaborn<\/code><\/pre>\n\n\n\n
          \n
        • \u5e38\u89c1\u56fe\u5f62\u7c7b\u578b<\/strong>\uff1a<\/li>\n\n\n\n
        • \u70ed\u529b\u56fe\uff08Heatmap\uff09<\/li>\n\n\n\n
        • \u5206\u7c7b\u56fe\uff08Boxplot, Violin Plot\uff09<\/li>\n\n\n\n
        • \u5206\u5e03\u56fe\uff08Distplot\uff09<\/li>\n\n\n\n
        • \u914d\u5bf9\u56fe\uff08Pairplot\uff09<\/li>\n<\/ul>\n\n\n\n
          \u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a<\/p>\n\n\n\n
          import seaborn as sns\nimport matplotlib.pyplot as plt\n\n# \u4f7f\u7528 Seaborn \u7ed8\u5236\u70ed\u529b\u56fe\ndata = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]\nsns.heatmap(data, annot=True, cmap='coolwarm')\n\nplt.title(\"Heatmap\")\nplt.show()\n\n# \u4f7f\u7528 Seaborn \u7ed8\u5236\u7bb1\u578b\u56fe\ntips = sns.load_dataset('tips')  # Seaborn \u5185\u7f6e\u7684\u6570\u636e\u96c6\nsns.boxplot(x='day', y='total_bill', data=tips)\nplt.title(\"Boxplot\")\nplt.show()<\/code><\/pre>\n\n\n\n
          1.3 Plotly<\/strong><\/h3>\n\n\n\n
          Plotly<\/strong> \u662f\u4e00\u4e2a\u4ea4\u4e92\u5f0f\u56fe\u8868\u5e93\uff0c\u652f\u6301 Web \u9875\u9762\u5d4c\u5165\u3002\u5b83\u53ef\u4ee5\u751f\u6210\u9ad8\u5ea6\u4ea4\u4e92\u7684\u56fe\u5f62\uff0c\u975e\u5e38\u9002\u5408\u5c55\u793a\u52a8\u6001\u6570\u636e\u548c\u9700\u8981\u7528\u6237\u4ea4\u4e92\u7684\u56fe\u8868\u3002<\/p>\n\n\n\n
            \n
          • \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
              pip install plotly<\/code><\/pre>\n\n\n\n
              \n
            • \u5e38\u89c1\u56fe\u5f62\u7c7b\u578b<\/strong>\uff1a<\/li>\n\n\n\n
            • \u6298\u7ebf\u56fe\uff08Line Plot\uff09<\/li>\n\n\n\n
            • \u6563\u70b9\u56fe\uff08Scatter Plot\uff09<\/li>\n\n\n\n
            • \u5730\u7406\u56fe\uff08Geo Plot\uff09<\/li>\n\n\n\n
            • 3D \u56fe\u5f62\uff083D Plot\uff09<\/li>\n<\/ul>\n\n\n\n
              \u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a<\/p>\n\n\n\n
              import plotly.express as px\n\n# \u4f7f\u7528 Plotly \u7ed8\u5236\u6563\u70b9\u56fe\ndf = px.data.iris()  # Plotly \u5185\u7f6e\u7684\u6570\u636e\u96c6\nfig = px.scatter(df, x='sepal_width', y='sepal_length', color='species')\nfig.show()\n\n# \u4f7f\u7528 Plotly \u7ed8\u5236\u67f1\u72b6\u56fe\nfig = px.bar(df, x='species', y='petal_length', color='species')\nfig.show()<\/code><\/pre>\n\n\n\n
              1.4 Bokeh<\/strong><\/h3>\n\n\n\n
              Bokeh<\/strong> \u662f\u4e00\u4e2a\u9ad8\u6548\u7684\u4ea4\u4e92\u5f0f\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u7279\u522b\u9002\u5408\u7528\u4e8e\u5927\u89c4\u6a21\u6570\u636e\u96c6\u548c\u52a8\u6001\u6570\u636e\u5c55\u793a\u3002\u5b83\u53ef\u4ee5\u751f\u6210 Web \u5e94\u7528\uff0c\u5177\u6709\u826f\u597d\u7684\u4ea4\u4e92\u4f53\u9a8c\u3002<\/p>\n\n\n\n
                \n
              • \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
                  pip install bokeh<\/code><\/pre>\n\n\n\n
                  \n
                • \u5e38\u89c1\u56fe\u5f62\u7c7b\u578b<\/strong>\uff1a<\/li>\n\n\n\n
                • \u6298\u7ebf\u56fe\uff08Line Plot\uff09<\/li>\n\n\n\n
                • \u6563\u70b9\u56fe\uff08Scatter Plot\uff09<\/li>\n\n\n\n
                • \u5730\u56fe\u53ef\u89c6\u5316\uff08Map Plot\uff09<\/li>\n\n\n\n
                • \u52a8\u6001\u56fe\u5f62\uff08Interactive Plot\uff09<\/li>\n<\/ul>\n\n\n\n
                  \u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a<\/p>\n\n\n\n
                  from bokeh.plotting import figure, show\nfrom bokeh.models import ColumnDataSource\n\n# \u521b\u5efa\u6570\u636e\u6e90\nx = [1, 2, 3, 4, 5]\ny = [1, 4, 9, 16, 25]\nsource = ColumnDataSource(data=dict(x=x, y=y))\n\n# \u521b\u5efa\u7ed8\u56fe\np = figure(title=\"Simple Line Plot\", x_axis_label='X', y_axis_label='Y')\np.line('x', 'y', source=source, line_width=2)\n\n# \u663e\u793a\u56fe\u5f62\nshow(p)<\/code><\/pre>\n\n\n\n
                  1.5 Altair<\/strong><\/h3>\n\n\n\n
                  Altair<\/strong> \u662f\u4e00\u4e2a\u58f0\u660e\u5f0f\u7684\u53ef\u89c6\u5316\u5e93\uff0c\u5b83\u7b80\u5316\u4e86\u56fe\u5f62\u7684\u521b\u5efa\u8fc7\u7a0b\uff0c\u975e\u5e38\u9002\u5408\u7528\u4e8e\u751f\u6210\u7edf\u8ba1\u56fe\u5f62\uff0c\u8bed\u6cd5\u7b80\u6d01\uff0c\u6613\u4e8e\u7406\u89e3\u3002<\/p>\n\n\n\n
                    \n
                  • \u5b89\u88c5<\/strong>\uff1a<\/li>\n<\/ul>\n\n\n\n
                      pip install altair<\/code><\/pre>\n\n\n\n
                      \n
                    • \u5e38\u89c1\u56fe\u5f62\u7c7b\u578b<\/strong>\uff1a<\/li>\n\n\n\n
                    • \u6563\u70b9\u56fe\uff08Scatter Plot\uff09<\/li>\n\n\n\n
                    • \u6761\u5f62\u56fe\uff08Bar Chart\uff09<\/li>\n\n\n\n
                    • \u6298\u7ebf\u56fe\uff08Line Chart\uff09<\/li>\n<\/ul>\n\n\n\n
                      \u793a\u4f8b\u4ee3\u7801<\/strong>\uff1a<\/p>\n\n\n\n
                      import altair as alt\nimport pandas as pd\n\n# \u521b\u5efa\u6570\u636e\ndf = pd.DataFrame({\n    'x': [1, 2, 3, 4, 5],\n    'y': [1, 4, 9, 16, 25]\n})\n\n# \u521b\u5efa Altair \u56fe\u5f62\nchart = alt.Chart(df).mark_line().encode(\n    x='x',\n    y='y'\n)\n\nchart.show()<\/code><\/pre>\n\n\n\n
                      2. \u6570\u636e\u53ef\u89c6\u5316\u7684\u6280\u672f\u4e0e\u6280\u5de7<\/h2>\n\n\n\n
                      2.1 \u9009\u62e9\u5408\u9002\u7684\u56fe\u8868\u7c7b\u578b<\/strong><\/h3>\n\n\n\n
                      \u4e0d\u540c\u7c7b\u578b\u7684\u6570\u636e\u9002\u5408\u4e0d\u540c\u7684\u56fe\u8868\uff1a<\/p>\n\n\n\n
                        \n
                      • \u65f6\u95f4\u5e8f\u5217\u6570\u636e<\/strong>\uff1a\u4f7f\u7528\u6298\u7ebf\u56fe\uff08Line Plot\uff09\u3002<\/li>\n\n\n\n
                      • \u7c7b\u522b\u6570\u636e<\/strong>\uff1a\u4f7f\u7528\u67f1\u72b6\u56fe\uff08Bar Plot\uff09\u6216\u997c\u56fe\uff08Pie Chart\uff09\u3002<\/li>\n\n\n\n
                      • \u5206\u5e03\u6570\u636e<\/strong>\uff1a\u4f7f\u7528\u76f4\u65b9\u56fe\uff08Histogram\uff09\u6216\u7bb1\u578b\u56fe\uff08Boxplot\uff09\u3002<\/li>\n\n\n\n
                      • \u53d8\u91cf\u95f4\u5173\u7cfb<\/strong>\uff1a\u4f7f\u7528\u6563\u70b9\u56fe\uff08Scatter Plot\uff09\u6216\u70ed\u529b\u56fe\uff08Heatmap\uff09\u3002<\/li>\n<\/ul>\n\n\n\n
                        2.2 \u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316<\/strong><\/h3>\n\n\n\n
                        \u5728\u5c55\u793a\u6570\u636e\u65f6\uff0c\u5982\u679c\u9700\u8981\u4e0e\u7528\u6237\u8fdb\u884c\u4ea4\u4e92\uff08\u5982\u653e\u5927\u7f29\u5c0f\u3001\u9f20\u6807\u60ac\u505c\u663e\u793a\u8be6\u7ec6\u4fe1\u606f\u7b49\uff09\uff0c\u53ef\u4ee5\u4f7f\u7528 Plotly<\/strong>\u3001Bokeh<\/strong> \u6216 Altair<\/strong> \u6765\u751f\u6210\u4ea4\u4e92\u5f0f\u56fe\u8868\u3002\u8fd9\u79cd\u65b9\u5f0f\u5bf9\u4e8e\u6570\u636e\u5c55\u793a\u5c24\u5176\u6709\u7528\uff0c\u80fd\u591f\u8ba9\u7528\u6237\u81ea\u5df1\u63a2\u7d22\u6570\u636e\u3002<\/p>\n\n\n\n
                        2.3 \u6570\u636e\u6e05\u6d17\u4e0e\u9884\u5904\u7406<\/strong><\/h3>\n\n\n\n
                        \u5728\u7ed8\u5236\u56fe\u8868\u4e4b\u524d\uff0c\u786e\u4fdd\u6570\u636e\u5df2\u7ecf\u7ecf\u8fc7\u9002\u5f53\u7684\u6e05\u6d17\u548c\u9884\u5904\u7406\u3002\u5904\u7406\u7f3a\u5931\u503c\u3001\u5f02\u5e38\u503c\uff0c\u4ee5\u53ca\u8fdb\u884c\u9002\u5f53\u7684\u5f52\u4e00\u5316\u548c\u6807\u51c6\u5316\uff0c\u4f1a\u4f7f\u53ef\u89c6\u5316\u7ed3\u679c\u66f4\u4e3a\u51c6\u786e\u548c\u6709\u610f\u4e49\u3002<\/p>\n\n\n\n
                        2.4 \u7f8e\u5b66\u8bbe\u8ba1<\/strong><\/h3>\n\n\n\n
                        \u56fe\u8868\u7684\u8bbe\u8ba1\u4e0d\u4ec5\u8981\u8868\u8fbe\u6570\u636e\u7684\u610f\u4e49\uff0c\u8fd8\u8981\u8ba9\u56fe\u8868\u6e05\u6670\u6613\u61c2\uff1a<\/p>\n\n\n\n
                          \n
                        • \u4f7f\u7528\u9002\u5f53\u7684\u6807\u9898\u3001\u6807\u7b7e\u3001\u6ce8\u91ca\u6765\u89e3\u91ca\u56fe\u8868\u5185\u5bb9\u3002<\/li>\n\n\n\n
                        • \u9009\u62e9\u5408\u9002\u7684\u914d\u8272\u65b9\u6848\uff0c\u786e\u4fdd\u56fe\u8868\u989c\u8272\u4e0e\u6570\u636e\u4e4b\u95f4\u7684\u5173\u8054\u6e05\u6670\u3002<\/li>\n\n\n\n
                        • \u907f\u514d\u8fc7\u5ea6\u590d\u6742\u5316\uff0c\u907f\u514d\u4e0d\u5fc5\u8981\u7684\u5143\u7d20\uff0c\u4fdd\u6301\u56fe\u8868\u7b80\u6d01\u3002<\/li>\n<\/ul>\n\n\n\n
                          3. \u603b\u7ed3<\/h2>\n\n\n\n
                          Python \u63d0\u4f9b\u4e86\u591a\u79cd\u5f3a\u5927\u7684\u6570\u636e\u53ef\u89c6\u5316\u5de5\u5177\uff0c\u6bcf\u4e2a\u5de5\u5177\u90fd\u6709\u4e0d\u540c\u7684\u4f18\u52bf\u548c\u7279\u70b9\uff1a<\/p>\n\n\n\n
                            \n
                          • Matplotlib<\/strong>\uff1a\u529f\u80fd\u5f3a\u5927\u3001\u7075\u6d3b\uff0c\u9002\u7528\u4e8e\u57fa\u7840\u56fe\u8868\u7ed8\u5236\u3002<\/li>\n\n\n\n
                          • Seaborn<\/strong>\uff1a\u57fa\u4e8e Matplotlib\uff0c\u6613\u4e8e\u7ed8\u5236\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u5f62\u3002<\/li>\n\n\n\n
                          • Plotly<\/strong>\uff1a\u652f\u6301\u4ea4\u4e92\u5f0f\u56fe\u8868\uff0c\u9002\u5408\u5c55\u793a\u52a8\u6001\u6570\u636e\u3002<\/li>\n\n\n\n
                          • Bokeh<\/strong>\uff1a\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e\u96c6\u548c\u52a8\u6001\u4ea4\u4e92\u5f0f\u5e94\u7528\u3002<\/li>\n\n\n\n
                          • Altair<\/strong>\uff1a\u58f0\u660e\u5f0f\u8bed\u6cd5\uff0c\u7b80\u6d01\u6613\u61c2\uff0c\u9002\u5408\u5feb\u901f\u521b\u5efa\u7edf\u8ba1\u56fe\u5f62\u3002<\/li>\n<\/ul>\n\n\n\n
                            \u9009\u62e9\u9002\u5408\u4f60\u9700\u6c42\u7684\u5de5\u5177\uff0c\u5e76\u7ed3\u5408\u5408\u9002\u7684\u56fe\u8868\u7c7b\u578b\u4e0e\u8bbe\u8ba1\u6280\u5de7\uff0c\u53ef\u4ee5\u8ba9\u4f60\u8f7b\u677e\u5730\u5c06\u6570\u636e\u8f6c\u5316\u4e3a\u53ef\u89c6\u5316\u7684\u4fe1\u606f\uff0c\u4e3a\u6570\u636e\u5206\u6790\u548c\u51b3\u7b56\u63d0\u4f9b\u6709\u529b\u652f\u6301\u3002<\/p>\n\n\n\n
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