{"id":1124201,"date":"2025-01-08T19:39:17","date_gmt":"2025-01-08T11:39:17","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1124201.html"},"modified":"2025-01-08T19:39:20","modified_gmt":"2025-01-08T11:39:20","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e7%94%bb%e5%9b%be%e5%8a%a0%e6%a8%aa%e7%ba%b5%e5%9d%90%e6%a0%87%e5%90%8d%e7%a7%b0","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1124201.html","title":{"rendered":"\u5982\u4f55\u7528python\u753b\u56fe\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u753b\u56fe\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\"<\/p>\n

\u8981\u7528Python\u753b\u56fe\u5e76\u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\uff0c\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u6b65\u9aa4\u8fdb\u884c\uff1a\u9009\u62e9\u5408\u9002\u7684\u7ed8\u56fe\u5e93\u3001\u8bbe\u7f6e\u56fe\u5f62\u548c\u5750\u6807\u540d\u79f0\u3001\u5c55\u793a\u56fe\u5f62\u3002<\/strong> \u9996\u5148\uff0c\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u662fMatplotlib\uff0c\u5b83\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u529f\u80fd\u6765\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\u3002\u5176\u6b21\uff0c\u5728\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7plt.xlabel()<\/code>\u548cplt.ylabel()<\/code>\u51fd\u6570\u5206\u522b\u8bbe\u7f6e\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\u3002\u6700\u540e\uff0c\u901a\u8fc7plt.show()<\/code>\u5c55\u793a\u56fe\u5f62\u3002\u4ee5\u4e0b\u662f\u8be6\u7ec6\u6b65\u9aa4\u548c\u793a\u4f8b\u4ee3\u7801\u3002<\/p>\n<\/p>\n

\u4e00\u3001\u9009\u62e9\u5408\u9002\u7684\u7ed8\u56fe\u5e93<\/strong><\/p>\n<\/p>\n

Python\u63d0\u4f9b\u4e86\u591a\u4e2a\u7528\u4e8e\u7ed8\u56fe\u7684\u5e93\uff0c\u5176\u4e2d\u6700\u5e38\u7528\u7684\u662fMatplotlib\u3002\u5b83\u4e0d\u4ec5\u529f\u80fd\u5f3a\u5927\uff0c\u4e14\u6613\u4e8e\u4f7f\u7528\uff0c\u9002\u5408\u5404\u79cd\u590d\u6742\u7684\u7ed8\u56fe\u9700\u6c42\u3002\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u89c1\u7684\u7ed8\u56fe\u5e93\u53ca\u5176\u7279\u70b9\uff1a<\/p>\n<\/p>\n

    \n
  1. Matplotlib<\/strong>\uff1a\u8fd9\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\uff0c\u652f\u6301\u591a\u79cd\u56fe\u5f62\u7c7b\u578b\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u7b49\u3002Matplotlib\u7684API\u8bbe\u8ba1\u7075\u6d3b\uff0c\u80fd\u591f\u751f\u6210\u9ad8\u8d28\u91cf\u7684\u56fe\u5f62\u3002<\/li>\n
  2. Seaborn<\/strong>\uff1a\u57fa\u4e8eMatplotlib\uff0c\u63d0\u4f9b\u66f4\u9ad8\u7ea7\u7684\u56fe\u5f62\u7ed8\u5236\u63a5\u53e3\uff0c\u9002\u5408\u8fdb\u884c\u7edf\u8ba1\u6570\u636e\u53ef\u89c6\u5316\u3002Seaborn\u7684\u9ed8\u8ba4\u914d\u8272\u548c\u6837\u5f0f\u8f83\u4e3a\u7f8e\u89c2\u3002<\/li>\n
  3. Plotly<\/strong>\uff1a\u652f\u6301\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u9002\u7528\u4e8e\u9700\u8981\u52a8\u6001\u5c55\u793a\u6570\u636e\u7684\u60c5\u666f\u3002Plotly\u56fe\u5f62\u53ef\u4ee5\u65b9\u4fbf\u5730\u5d4c\u5165\u5728\u7f51\u9875\u4e2d\u3002<\/li>\n
  4. Bokeh<\/strong>\uff1a\u7c7b\u4f3c\u4e8ePlotly\uff0c\u4e5f\u652f\u6301\u4ea4\u4e92\u5f0f\u56fe\u5f62\uff0c\u9002\u5408\u5927\u89c4\u6a21\u6570\u636e\u7684\u53ef\u89c6\u5316\u3002<\/li>\n<\/ol>\n

    \u4e8c\u3001\u5b89\u88c5Matplotlib<\/strong><\/p>\n<\/p>\n

    \u5728\u5f00\u59cb\u7ed8\u56fe\u4e4b\u524d\uff0c\u9700\u8981\u786e\u4fdd\u5df2\u5b89\u88c5Matplotlib\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u8fdb\u884c\u5b89\u88c5\uff1a<\/p>\n<\/p>\n

    pip install matplotlib<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e09\u3001\u57fa\u672c\u7ed8\u56fe\u53ca\u6dfb\u52a0\u5750\u6807\u540d\u79f0<\/strong><\/p>\n<\/p>\n
    \u4e0b\u9762\u6211\u4eec\u4ee5Matplotlib\u4e3a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u7ed8\u5236\u7b80\u5355\u7684\u56fe\u5f62\u5e76\u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u521b\u5efa\u6570\u636e<\/strong><\/h2>\n
    x = [1, 2, 3, 4, 5]<\/p>\n
    y = [2, 3, 5, 7, 11]<\/p>\n
    \u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
    plt.plot(x, y)<\/p>\n
    \u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0<\/strong><\/h2>\n
    plt.xlabel("X\u8f74\u540d\u79f0")<\/p>\n
    plt.ylabel("Y\u8f74\u540d\u79f0")<\/p>\n
    \u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e0a\u9762\u7684\u4ee3\u7801\u5c55\u793a\u4e86\u4e00\u4e2a\u7b80\u5355\u7684\u6298\u7ebf\u56fe\uff0c\u5e76\u901a\u8fc7plt.xlabel("X\u8f74\u540d\u79f0")<\/code>\u548cplt.ylabel("Y\u8f74\u540d\u79f0")<\/code>\u5206\u522b\u4e3a\u6a2a\u7eb5\u5750\u6807\u6dfb\u52a0\u4e86\u540d\u79f0\u3002<\/p>\n<\/p>\n
    \u56db\u3001\u8be6\u7ec6\u7ed8\u56fe\u6280\u5de7<\/strong><\/p>\n<\/p>\n
    1\u3001\u8bbe\u7f6e\u56fe\u5f62\u6807\u9898\u548c\u56fe\u4f8b<\/h3>\n<\/p>\n
    \u56fe\u5f62\u6807\u9898\u548c\u56fe\u4f8b\u662f\u56fe\u8868\u7684\u91cd\u8981\u7ec4\u6210\u90e8\u5206\uff0c\u80fd\u591f\u5e2e\u52a9\u8bfb\u8005\u66f4\u597d\u5730\u7406\u89e3\u56fe\u5f62\u5185\u5bb9\u3002<\/p>\n<\/p>\n
    # \u8bbe\u7f6e\u56fe\u5f62\u6807\u9898<\/p>\n
    plt.title("\u6298\u7ebf\u56fe\u793a\u4f8b")<\/p>\n
    \u6dfb\u52a0\u56fe\u4f8b<\/strong><\/h2>\n
    plt.plot(x, y, label="\u6570\u636e1")<\/p>\n
    plt.legend()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    2\u3001\u8bbe\u7f6e\u5750\u6807\u8f74\u523b\u5ea6\u548c\u8303\u56f4<\/h3>\n<\/p>\n
    \u53ef\u4ee5\u901a\u8fc7plt.xticks()<\/code>\u548cplt.yticks()<\/code>\u8bbe\u7f6e\u5750\u6807\u8f74\u523b\u5ea6\uff0c\u901a\u8fc7plt.xlim()<\/code>\u548cplt.ylim()<\/code>\u8bbe\u7f6e\u5750\u6807\u8f74\u8303\u56f4\u3002<\/p>\n<\/p>\n
    # \u8bbe\u7f6e\u5750\u6807\u8f74\u523b\u5ea6<\/p>\n
    plt.xticks([1, 2, 3, 4, 5])<\/p>\n
    plt.yticks([2, 3, 5, 7, 11])<\/p>\n
    \u8bbe\u7f6e\u5750\u6807\u8f74\u8303\u56f4<\/strong><\/h2>\n
    plt.xlim(0, 6)<\/p>\n
    plt.ylim(0, 12)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    3\u3001\u6dfb\u52a0\u7f51\u683c\u7ebf<\/h3>\n<\/p>\n
    \u7f51\u683c\u7ebf\u53ef\u4ee5\u5e2e\u52a9\u8bfb\u8005\u66f4\u5bb9\u6613\u5730\u8bfb\u53d6\u56fe\u5f62\u4e2d\u7684\u6570\u636e\u503c\u3002<\/p>\n<\/p>\n
    # \u6dfb\u52a0\u7f51\u683c\u7ebf<\/p>\n
    plt.grid(True)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    4\u3001\u4fdd\u5b58\u56fe\u5f62<\/h3>\n<\/p>\n
    \u5728\u5c55\u793a\u56fe\u5f62\u4e4b\u524d\uff0c\u53ef\u4ee5\u901a\u8fc7plt.savefig()<\/code>\u5c06\u56fe\u5f62\u4fdd\u5b58\u4e3a\u6587\u4ef6\u3002<\/p>\n<\/p>\n
    # \u4fdd\u5b58\u56fe\u5f62<\/p>\n
    plt.savefig("plot.png")<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u4e94\u3001\u7efc\u5408\u793a\u4f8b<\/strong><\/p>\n<\/p>\n
    \u4e0b\u9762\u662f\u4e00\u4e2a\u7efc\u5408\u793a\u4f8b\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528Matplotlib\u7ed8\u5236\u5e26\u6709\u6807\u9898\u3001\u56fe\u4f8b\u3001\u5750\u6807\u8f74\u540d\u79f0\u3001\u523b\u5ea6\u3001\u8303\u56f4\u3001\u7f51\u683c\u7ebf\u7684\u6298\u7ebf\u56fe\uff0c\u5e76\u4fdd\u5b58\u4e3a\u6587\u4ef6\u3002<\/p>\n<\/p>\n
    import matplotlib.pyplot as plt<\/p>\n
    \u521b\u5efa\u6570\u636e<\/strong><\/h2>\n
    x = [1, 2, 3, 4, 5]<\/p>\n
    y1 = [2, 3, 5, 7, 11]<\/p>\n
    y2 = [1, 4, 6, 8, 10]<\/p>\n
    \u7ed8\u5236\u6298\u7ebf\u56fe<\/strong><\/h2>\n
    plt.plot(x, y1, label="\u6570\u636e1")<\/p>\n
    plt.plot(x, y2, label="\u6570\u636e2")<\/p>\n
    \u8bbe\u7f6e\u56fe\u5f62\u6807\u9898<\/strong><\/h2>\n
    plt.title("\u6298\u7ebf\u56fe\u793a\u4f8b")<\/p>\n
    \u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0<\/strong><\/h2>\n
    plt.xlabel("X\u8f74\u540d\u79f0")<\/p>\n
    plt.ylabel("Y\u8f74\u540d\u79f0")<\/p>\n
    \u8bbe\u7f6e\u5750\u6807\u8f74\u523b\u5ea6<\/strong><\/h2>\n
    plt.xticks([1, 2, 3, 4, 5])<\/p>\n
    plt.yticks([1, 3, 5, 7, 9, 11])<\/p>\n
    \u8bbe\u7f6e\u5750\u6807\u8f74\u8303\u56f4<\/strong><\/h2>\n
    plt.xlim(0, 6)<\/p>\n
    plt.ylim(0, 12)<\/p>\n
    \u6dfb\u52a0\u7f51\u683c\u7ebf<\/strong><\/h2>\n
    plt.grid(True)<\/p>\n
    \u6dfb\u52a0\u56fe\u4f8b<\/strong><\/h2>\n
    plt.legend()<\/p>\n
    \u4fdd\u5b58\u56fe\u5f62<\/strong><\/h2>\n
    plt.savefig("plot.png")<\/p>\n
    \u663e\u793a\u56fe\u5f62<\/strong><\/h2>\n
    plt.show()<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u603b\u7ed3<\/strong><\/p>\n<\/p>\n
    \u4f7f\u7528Python\u8fdb\u884c\u7ed8\u56fe\u5e76\u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\u662f\u6570\u636e\u53ef\u89c6\u5316\u4e2d\u7684\u57fa\u672c\u64cd\u4f5c\u3002\u901a\u8fc7\u9009\u62e9\u5408\u9002\u7684\u7ed8\u56fe\u5e93\uff08\u5982Matplotlib\uff09\uff0c\u53ef\u4ee5\u8f7b\u677e\u5730\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u5f62\uff0c\u5e76\u901a\u8fc7\u7b80\u5355\u7684\u51fd\u6570\u8c03\u7528\u6dfb\u52a0\u5750\u6807\u540d\u79f0\u3001\u6807\u9898\u3001\u56fe\u4f8b\u7b49\u4fe1\u606f\u3002\u5e0c\u671b\u672c\u6587\u7684\u8be6\u7ec6\u4ecb\u7ecd\u80fd\u5e2e\u52a9\u4f60\u66f4\u597d\u5730\u638c\u63e1Python\u7ed8\u56fe\u7684\u6280\u5de7\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u5728Python\u4e2d\u9009\u62e9\u5408\u9002\u7684\u7ed8\u56fe\u5e93\u6765\u7ed8\u5236\u56fe\u5f62\uff1f<\/strong>
    \u5728Python\u4e2d\uff0c\u6709\u591a\u4e2a\u7ed8\u56fe\u5e93\u53ef\u4f9b\u9009\u62e9\uff0c\u5305\u62ecMatplotlib\u3001Seaborn\u548cPlotly\u7b49\u3002Matplotlib\u662f\u6700\u5e38\u7528\u7684\u57fa\u7840\u5e93\uff0c\u9002\u5408\u7b80\u5355\u7684\u56fe\u5f62\u7ed8\u5236\uff0c\u800cSeaborn\u5728\u7edf\u8ba1\u56fe\u8868\u65b9\u9762\u8868\u73b0\u66f4\u4f73\uff0cPlotly\u5219\u9002\u5408\u4ea4\u4e92\u5f0f\u56fe\u5f62\u3002\u5982\u679c\u4f60\u9700\u8981\u5728\u56fe\u4e2d\u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\uff0cMatplotlib\u662f\u4e00\u4e2a\u975e\u5e38\u5408\u9002\u7684\u9009\u62e9\u3002<\/p>\n
    \u600e\u6837\u5728Matplotlib\u4e2d\u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\uff1f<\/strong>
    \u4f7f\u7528Matplotlib\u7ed8\u56fe\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7plt.xlabel()<\/code>\u548cplt.ylabel()<\/code>\u51fd\u6570\u8f7b\u677e\u6dfb\u52a0\u6a2a\u7eb5\u5750\u6807\u540d\u79f0\u3002\u4f8b\u5982\uff0cplt.xlabel('X\u8f74\u540d\u79f0')<\/code>\u548cplt.ylabel('Y\u8f74\u540d\u79f0')<\/code>\u53ef\u4ee5\u5728\u56fe\u5f62\u4e2d\u660e\u786e\u6307\u793a\u5750\u6807\u7684\u542b\u4e49\uff0c\u4f7f\u5f97\u56fe\u8868\u66f4\u52a0\u6613\u4e8e\u7406\u89e3\u3002<\/p>\n
    \u5728\u7ed8\u5236\u56fe\u5f62\u65f6\uff0c\u5982\u4f55\u8c03\u6574\u5750\u6807\u540d\u79f0\u7684\u6837\u5f0f\uff1f<\/strong>
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