{"id":1092779,"date":"2025-01-08T14:24:31","date_gmt":"2025-01-08T06:24:31","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1092779.html"},"modified":"2025-01-08T14:24:34","modified_gmt":"2025-01-08T06:24:34","slug":"python%e5%a6%82%e4%bd%95%e7%94%bb%e5%87%ba%e4%b8%89%e8%a7%92%e5%87%bd%e6%95%b0-2","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1092779.html","title":{"rendered":"python\u5982\u4f55\u753b\u51fa\u4e09\u89d2\u51fd\u6570"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/24205655\/756c9e92-cf6c-44ee-a608-d5ef6b2c9424.webp\" alt=\"python\u5982\u4f55\u753b\u51fa\u4e09\u89d2\u51fd\u6570\" \/><\/p>\n<p><h2>PYTHON\u5982\u4f55\u753b\u51fa\u4e09\u89d2\u51fd\u6570<\/h2>\n<\/p>\n<p><p><strong>Python\u753b\u51fa\u4e09\u89d2\u51fd\u6570\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Numpy\u751f\u6210\u6570\u636e\u3001\u4f7f\u7528Seaborn\u8fdb\u884c\u7f8e\u5316\u3001\u5229\u7528Pandas\u5904\u7406\u6570\u636e\u3002<\/strong> \u5176\u4e2d\uff0c\u6700\u5e38\u7528\u7684\u65b9\u6cd5\u662f\u4f7f\u7528Matplotlib\u5e93\uff0c\u56e0\u4e3a\u5b83\u529f\u80fd\u5f3a\u5927\u4e14\u6613\u4e8e\u4f7f\u7528\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Matplotlib\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe\u3002<\/p>\n<\/p>\n<p><h3>\u4e00\u3001\u4f7f\u7528Matplotlib\u5e93\u7ed8\u5236\u4e09\u89d2\u51fd\u6570<\/h3>\n<\/p>\n<p><p>Matplotlib\u662fPython\u4e2d\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\u4e4b\u4e00\uff0c\u7279\u522b\u9002\u5408\u7528\u4e8e\u521b\u5efa\u9759\u6001\u3001\u52a8\u753b\u548c\u4ea4\u4e92\u5f0f\u7684\u56fe\u8868\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Matplotlib\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5Matplotlib\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u4f60\u9700\u8981\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86Matplotlib\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install matplotlib<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u5bfc\u5165\u5fc5\u8981\u7684\u5e93<\/h4>\n<\/p>\n<p><p>\u5728\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u4e4b\u524d\uff0c\u9700\u8981\u5bfc\u5165Matplotlib\u548cNumpy\u5e93\u3002Numpy\u5e93\u7528\u4e8e\u751f\u6210\u4e09\u89d2\u51fd\u6570\u7684\u6570\u636e\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import matplotlib.pyplot as plt<\/p>\n<p>import numpy as np<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u751f\u6210\u4e09\u89d2\u51fd\u6570\u7684\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Numpy\u751f\u6210x\u8f74\u7684\u6570\u636e\u8303\u56f4\u4ee5\u53ca\u5bf9\u5e94\u7684y\u8f74\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u751f\u6210sin\u548ccos\u51fd\u6570\u6570\u636e\u7684\u793a\u4f8b\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u751f\u6210x\u8f74\u6570\u636e\uff0c\u4ece0\u52302\u03c0\uff0c\u6b65\u957f\u4e3a0.01<\/p>\n<p>x = np.arange(0, 2 * np.pi, 0.01)<\/p>\n<h2><strong>\u751f\u6210sin\u548ccos\u51fd\u6570\u6570\u636e<\/strong><\/h2>\n<p>y_sin = np.sin(x)<\/p>\n<p>y_cos = np.cos(x)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u7ed8\u5236\u4e09\u89d2\u51fd\u6570<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Matplotlib\u7ed8\u5236sin\u548ccos\u51fd\u6570\u56fe\uff0c\u5e76\u6dfb\u52a0\u6807\u9898\u3001\u6807\u7b7e\u548c\u56fe\u4f8b\u3002<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">plt.figure(figsize=(10, 6))<\/p>\n<h2><strong>\u7ed8\u5236sin\u51fd\u6570<\/strong><\/h2>\n<p>plt.plot(x, y_sin, label=&#39;sin(x)&#39;, color=&#39;blue&#39;)<\/p>\n<h2><strong>\u7ed8\u5236cos\u51fd\u6570<\/strong><\/h2>\n<p>plt.plot(x, y_cos, label=&#39;cos(x)&#39;, color=&#39;red&#39;)<\/p>\n<h2><strong>\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n<p>plt.title(&#39;Sin and Cos Functions&#39;)<\/p>\n<p>plt.xlabel(&#39;x&#39;)<\/p>\n<p>plt.ylabel(&#39;y&#39;)<\/p>\n<h2><strong>\u6dfb\u52a0\u56fe\u4f8b<\/strong><\/h2>\n<p>plt.legend()<\/p>\n<h2><strong>\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e8c\u3001\u4f7f\u7528Numpy\u751f\u6210\u6570\u636e<\/h3>\n<\/p>\n<p><p>Numpy\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u79d1\u5b66\u8ba1\u7b97\u5e93\uff0c\u80fd\u591f\u9ad8\u6548\u5730\u751f\u6210\u548c\u64cd\u4f5c\u6570\u7ec4\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Numpy\u751f\u6210\u4e09\u89d2\u51fd\u6570\u6570\u636e\u7684\u8be6\u7ec6\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u751f\u6210x\u8f74\u6570\u636e<\/h4>\n<\/p>\n<p><p>x\u8f74\u6570\u636e\u901a\u5e38\u662f\u4ece0\u52302\u03c0\u7684\u8303\u56f4\u3002\u53ef\u4ee5\u4f7f\u7528Numpy\u7684arange\u51fd\u6570\u751f\u6210\u8fd9\u4e9b\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">x = np.arange(0, 2 * np.pi, 0.01)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u751f\u6210\u4e09\u89d2\u51fd\u6570\u6570\u636e<\/h4>\n<\/p>\n<p><p>\u53ef\u4ee5\u4f7f\u7528Numpy\u7684sin\u548ccos\u51fd\u6570\u751f\u6210\u5bf9\u5e94\u7684y\u8f74\u6570\u636e\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">y_sin = np.sin(x)<\/p>\n<p>y_cos = np.cos(x)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e09\u3001\u4f7f\u7528Seaborn\u8fdb\u884c\u7f8e\u5316<\/h3>\n<\/p>\n<p><p>Seaborn\u662f\u4e00\u4e2a\u57fa\u4e8eMatplotlib\u7684\u7edf\u8ba1\u6570\u636e\u53ef\u89c6\u5316\u5e93\uff0c\u80fd\u591f\u8ba9\u7ed8\u5236\u7684\u56fe\u8868\u66f4\u52a0\u7f8e\u89c2\u3002\u4ee5\u4e0b\u662f\u4f7f\u7528Seaborn\u7f8e\u5316\u4e09\u89d2\u51fd\u6570\u56fe\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5Seaborn\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86Seaborn\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install seaborn<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u5bfc\u5165Seaborn\u5e93<\/h4>\n<\/p>\n<p><p>\u5728\u7ed8\u5236\u56fe\u8868\u4e4b\u524d\uff0c\u9700\u8981\u5bfc\u5165Seaborn\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import seaborn as sns<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u8bbe\u7f6eSeaborn\u6837\u5f0f<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Seaborn\u8bbe\u7f6e\u56fe\u8868\u7684\u6837\u5f0f\uff0c\u4f7f\u5176\u66f4\u52a0\u7f8e\u89c2\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">sns.set(style=&#39;whitegrid&#39;)<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe<\/h4>\n<\/p>\n<p><p>\u4e0e\u4f7f\u7528Matplotlib\u7ed8\u5236\u56fe\u8868\u7684\u6b65\u9aa4\u7c7b\u4f3c\uff0c\u4f46\u56fe\u8868\u4f1a\u66f4\u52a0\u7f8e\u89c2\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">plt.figure(figsize=(10, 6))<\/p>\n<h2><strong>\u7ed8\u5236sin\u51fd\u6570<\/strong><\/h2>\n<p>plt.plot(x, y_sin, label=&#39;sin(x)&#39;, color=&#39;blue&#39;)<\/p>\n<h2><strong>\u7ed8\u5236cos\u51fd\u6570<\/strong><\/h2>\n<p>plt.plot(x, y_cos, label=&#39;cos(x)&#39;, color=&#39;red&#39;)<\/p>\n<h2><strong>\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n<p>plt.title(&#39;Sin and Cos Functions&#39;)<\/p>\n<p>plt.xlabel(&#39;x&#39;)<\/p>\n<p>plt.ylabel(&#39;y&#39;)<\/p>\n<h2><strong>\u6dfb\u52a0\u56fe\u4f8b<\/strong><\/h2>\n<p>plt.legend()<\/p>\n<h2><strong>\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u56db\u3001\u5229\u7528Pandas\u5904\u7406\u6570\u636e<\/h3>\n<\/p>\n<p><p>Pandas\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u6570\u636e\u5904\u7406\u5e93\uff0c\u80fd\u591f\u65b9\u4fbf\u5730\u5904\u7406\u548c\u5206\u6790\u6570\u636e\u3002\u5728\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe\u65f6\uff0c\u4e5f\u53ef\u4ee5\u4f7f\u7528Pandas\u6765\u5904\u7406\u6570\u636e\u3002\u4ee5\u4e0b\u662f\u5229\u7528Pandas\u5904\u7406\u4e09\u89d2\u51fd\u6570\u6570\u636e\u7684\u6b65\u9aa4\uff1a<\/p>\n<\/p>\n<p><h4>1\u3001\u5b89\u88c5Pandas\u5e93<\/h4>\n<\/p>\n<p><p>\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u7ecf\u5b89\u88c5\u4e86Pandas\u5e93\u3002\u53ef\u4ee5\u901a\u8fc7\u4ee5\u4e0b\u547d\u4ee4\u5b89\u88c5\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-bash\">pip install pandas<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>2\u3001\u5bfc\u5165Pandas\u5e93<\/h4>\n<\/p>\n<p><p>\u5728\u5904\u7406\u6570\u636e\u4e4b\u524d\uff0c\u9700\u8981\u5bfc\u5165Pandas\u5e93\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\">import pandas as pd<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>3\u3001\u521b\u5efaDataFrame<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Pandas\u521b\u5efa\u4e00\u4e2a\u5305\u542bx\u8f74\u6570\u636e\u548c\u5bf9\u5e94\u4e09\u89d2\u51fd\u6570\u6570\u636e\u7684DataFrame\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u521b\u5efa\u5305\u542bx\u8f74\u6570\u636e\u7684DataFrame<\/p>\n<p>df = pd.DataFrame({&#39;x&#39;: np.arange(0, 2 * np.pi, 0.01)})<\/p>\n<h2><strong>\u6dfb\u52a0sin\u548ccos\u51fd\u6570\u6570\u636e<\/strong><\/h2>\n<p>df[&#39;sin&#39;] = np.sin(df[&#39;x&#39;])<\/p>\n<p>df[&#39;cos&#39;] = np.cos(df[&#39;x&#39;])<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h4>4\u3001\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe<\/h4>\n<\/p>\n<p><p>\u4f7f\u7528Pandas\u7684plot\u51fd\u6570\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe\uff1a<\/p>\n<\/p>\n<p><pre><code class=\"language-python\"># \u8bbe\u7f6eSeaborn\u6837\u5f0f<\/p>\n<p>sns.set(style=&#39;whitegrid&#39;)<\/p>\n<h2><strong>\u7ed8\u5236sin\u548ccos\u51fd\u6570\u56fe<\/strong><\/h2>\n<p>df.plot(x=&#39;x&#39;, y=[&#39;sin&#39;, &#39;cos&#39;], figsize=(10, 6), color=[&#39;blue&#39;, &#39;red&#39;])<\/p>\n<h2><strong>\u6dfb\u52a0\u6807\u9898\u548c\u6807\u7b7e<\/strong><\/h2>\n<p>plt.title(&#39;Sin and Cos Functions&#39;)<\/p>\n<p>plt.xlabel(&#39;x&#39;)<\/p>\n<p>plt.ylabel(&#39;y&#39;)<\/p>\n<h2><strong>\u663e\u793a\u56fe\u8868<\/strong><\/h2>\n<p>plt.show()<\/p>\n<p><\/code><\/pre>\n<\/p>\n<p><h3>\u4e94\u3001\u603b\u7ed3<\/h3>\n<\/p>\n<p><p>\u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528Python\u4e2d\u7684Matplotlib\u3001Numpy\u3001Seaborn\u548cPandas\u5e93\u7ed8\u5236\u7f8e\u89c2\u4e14\u51c6\u786e\u7684\u4e09\u89d2\u51fd\u6570\u56fe\u3002<strong>Matplotlib\u5e93\u662f\u6700\u5e38\u7528\u7684\u7ed8\u56fe\u5e93\uff0cNumpy\u5e93\u7528\u4e8e\u751f\u6210\u6570\u636e\uff0cSeaborn\u5e93\u7528\u4e8e\u7f8e\u5316\u56fe\u8868\uff0cPandas\u5e93\u7528\u4e8e\u5904\u7406\u6570\u636e\u3002<\/strong> \u8fd9\u4e9b\u5e93\u7684\u7ed3\u5408\u4f7f\u7528\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u9ad8\u6548\u5730\u7ed8\u5236\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u6ee1\u8db3\u4e0d\u540c\u7684\u9700\u6c42\u3002\u65e0\u8bba\u662f\u8fdb\u884c\u6570\u636e\u5206\u6790\u8fd8\u662f\u5c55\u793a\u7ed3\u679c\uff0cPython\u4e2d\u7684\u8fd9\u4e9b\u5e93\u90fd\u662f\u975e\u5e38\u6709\u7528\u7684\u5de5\u5177\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe\u5f62\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Matplotlib\u5e93\u6765\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u56fe\u5f62\u3002\u9996\u5148\uff0c\u786e\u4fdd\u5df2\u5b89\u88c5Matplotlib\u5e93\uff0c\u901a\u8fc7\u547d\u4ee4<code>pip install matplotlib<\/code>\u8fdb\u884c\u5b89\u88c5\u3002\u7136\u540e\uff0c\u53ef\u4ee5\u4f7f\u7528NumPy\u5e93\u751f\u6210\u6570\u636e\u70b9\uff0c\u5e76\u5229\u7528Matplotlib\u7684<code>plot<\/code>\u51fd\u6570\u7ed8\u5236\u56fe\u5f62\u3002\u4f8b\u5982\uff0c\u7ed8\u5236\u6b63\u5f26\u548c\u4f59\u5f26\u51fd\u6570\u7684\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<pre><code class=\"language-python\">import numpy as np\nimport matplotlib.pyplot as plt\n\nx = np.linspace(-2 * np.pi, 2 * np.pi, 1000)\ny1 = np.sin(x)\ny2 = np.cos(x)\n\nplt.plot(x, y1, label=&#39;sin(x)&#39;)\nplt.plot(x, y2, label=&#39;cos(x)&#39;)\nplt.title(&#39;Sine and Cosine Functions&#39;)\nplt.xlabel(&#39;x values (radians)&#39;)\nplt.ylabel(&#39;Function values&#39;)\nplt.axhline(0, color=&#39;black&#39;,linewidth=0.5, ls=&#39;--&#39;)\nplt.axvline(0, color=&#39;black&#39;,linewidth=0.5, ls=&#39;--&#39;)\nplt.grid()\nplt.legend()\nplt.show()\n<\/code><\/pre>\n<p><strong>\u5728Python\u4e2d\u5982\u4f55\u81ea\u5b9a\u4e49\u4e09\u89d2\u51fd\u6570\u7684\u989c\u8272\u548c\u6837\u5f0f\uff1f<\/strong><br \/>\u5728\u4f7f\u7528Matplotlib\u7ed8\u5236\u4e09\u89d2\u51fd\u6570\u65f6\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bbe\u7f6e\u7ebf\u6761\u989c\u8272\u3001\u6837\u5f0f\u548c\u5bbd\u5ea6\u6765\u8fdb\u884c\u81ea\u5b9a\u4e49\u3002\u53ef\u4ee5\u5728<code>plot<\/code>\u51fd\u6570\u4e2d\u4f7f\u7528\u53c2\u6570<code>color<\/code>\u3001<code>linestyle<\/code>\u548c<code>linewidth<\/code>\u6765\u5b9e\u73b0\u3002\u4f8b\u5982\uff0c<code>plt.plot(x, y1, color=&#39;red&#39;, linestyle=&#39;--&#39;, linewidth=2)<\/code>\u53ef\u4ee5\u5c06\u6b63\u5f26\u51fd\u6570\u7ed8\u5236\u4e3a\u7ea2\u8272\u865a\u7ebf\uff0c\u5bbd\u5ea6\u4e3a2\u3002<\/p>\n<p><strong>\u5982\u4f55\u5728Python\u4e2d\u6dfb\u52a0\u4e09\u89d2\u51fd\u6570\u7684\u6ce8\u91ca\u548c\u6807\u7b7e\uff1f<\/strong><br \/>\u4e3a\u4e86\u4f7f\u56fe\u5f62\u66f4\u52a0\u76f4\u89c2\uff0c\u53ef\u4ee5\u5728Matplotlib\u4e2d\u6dfb\u52a0\u6ce8\u91ca\u548c\u6807\u7b7e\u3002\u4f7f\u7528<code>plt.annotate<\/code>\u51fd\u6570\u53ef\u4ee5\u5728\u7279\u5b9a\u7684\u70b9\u4e0a\u6dfb\u52a0\u6587\u672c\u8bf4\u660e\u3002\u6bd4\u5982\uff0c\u53ef\u4ee5\u5728\u6b63\u5f26\u51fd\u6570\u7684\u6700\u5927\u503c\u5904\u6dfb\u52a0\u6ce8\u91ca\uff0c\u4ee3\u7801\u5982\u4e0b\uff1a<\/p>\n<pre><code class=\"language-python\">plt.annotate(&#39;Max Value&#39;, xy=(np.pi\/2, 1), xytext=(np.pi\/2, 1.1),\n             arrowprops=dict(facecolor=&#39;black&#39;, shrink=0.05))\n<\/code><\/pre>\n<p>\u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0c\u56fe\u5f62\u5c06\u66f4\u52a0\u6613\u4e8e\u7406\u89e3\u548c\u751f\u52a8\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"PYTHON\u5982\u4f55\u753b\u51fa\u4e09\u89d2\u51fd\u6570 Python\u753b\u51fa\u4e09\u89d2\u51fd\u6570\u7684\u65b9\u6cd5\u5305\u62ec\uff1a\u4f7f\u7528Matplotlib\u5e93\u3001\u4f7f\u7528Numpy\u751f [&hellip;]","protected":false},"author":3,"featured_media":1092789,"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\/1092779"}],"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=1092779"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1092779\/revisions"}],"predecessor-version":[{"id":1092790,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1092779\/revisions\/1092790"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1092789"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1092779"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1092779"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1092779"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}