{"id":73426,"date":"2026-02-07T16:33:35","date_gmt":"2026-02-07T08:33:35","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/73426.html"},"modified":"2026-02-07T16:33:35","modified_gmt":"2026-02-07T08:33:35","slug":"%e6%95%b0%e6%8d%ae%e6%8c%96%e6%8e%98%e5%9f%ba%e7%a1%80%ef%bc%9a%e7%8e%af%e5%a2%83%e6%90%ad%e5%bb%ba%e4%b8%8ejupyter-notebook%e5%85%a5%e9%97%a8%e6%8c%87%e5%8d%97","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/73426.html","title":{"rendered":"\u6570\u636e\u6316\u6398\u57fa\u7840\uff1a\u73af\u5883\u642d\u5efa\u4e0eJupyter Notebook\u5165\u95e8\u6307\u5357"},"content":{"rendered":"<p>\u6458\u8981: \u672c\u6587\u662f\u6570\u636e\u6316\u6398\u5165\u95e8\u7cfb\u5217\u7684\u7b2c\u4e00\u7bc7&#xff0c;\u65e8\u5728\u5f15\u5bfc\u521d\u5b66\u8005\u5feb\u901f\u642d\u5efa\u4e00\u5957\u5b8c\u6574\u3001\u9ad8\u6548\u7684\u6570\u636e\u6316\u6398\u57fa\u7840\u73af\u5883\u3002\u6211\u4eec\u5c06\u9996\u5148\u4ecb\u7ecd\u5982\u4f55\u5b89\u88c5\u6570\u636e\u79d1\u5b66\u9886\u57df\u7684\u6838\u5fc3Python\u5e93&#xff0c;\u7136\u540e\u8be6\u7ec6\u8bb2\u89e3\u88ab\u8a89\u4e3a\u201c\u6570\u636e\u79d1\u5b66\u795e\u5668\u201d\u7684Jupyter Notebook\u7684\u5b89\u88c5\u3001\u6838\u5fc3\u6982\u5ff5\u53ca\u9ad8\u6548\u4f7f\u7528\u6280\u5de7&#xff0c;\u4e3a\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u3001\u673a\u5668\u5b66\u4e60\u4e4b\u65c5\u6253\u4e0b\u575a\u5b9e\u7684\u57fa\u7840\u3002<\/p>\n<hr \/>\n<h3>\u4e00\u3001\u6570\u636e\u6316\u6398\u57fa\u7840\u73af\u5883\u5b89\u88c5<\/h3>\n<p>\u5728\u5f00\u542f\u6570\u636e\u6316\u6398\u4e4b\u65c5\u524d&#xff0c;\u6240\u8c13\u201c\u5de5\u6b32\u5584\u5176\u4e8b&#xff0c;\u5fc5\u5148\u5229\u5176\u5668\u201d&#xff0c;\u6211\u4eec\u9700\u8981\u5148\u914d\u7f6e\u597d\u6211\u4eec\u7684\u5f00\u53d1\u73af\u5883\u3002Python\u56e0\u5176\u5f3a\u5927\u7684\u751f\u6001\u548c\u7b80\u6d01\u7684\u8bed\u6cd5&#xff0c;\u5df2\u6210\u4e3a\u6570\u636e\u79d1\u5b66\u9886\u57df\u7684\u9996\u9009\u8bed\u8a00\u3002\u4ee5\u4e0b\u662f\u8fdb\u884c\u6570\u636e\u6316\u6398\u6240\u5fc5\u9700\u7684\u6838\u5fc3\u5e93\u3002<\/p>\n<h4>1.1 \u6838\u5fc3\u5e93\u5b89\u88c5<\/h4>\n<p>\u6211\u4eec\u63a8\u8350\u4f7f\u7528pip\u5de5\u5177\u6765\u5b89\u88c5\u8fd9\u4e9b\u5e93\u3002\u4e3a\u4e86\u786e\u4fdd\u9879\u76ee\u73af\u5883\u7684\u7a33\u5b9a\u548c\u53ef\u590d\u73b0\u6027&#xff0c;\u5efa\u8bae\u5728\u865a\u62df\u73af\u5883\u4e2d\u8fdb\u884c\u5b89\u88c5&#xff0c;\u5e76\u6307\u5b9a\u7248\u672c\u53f7\u3002<\/p>\n<p>\u6253\u5f00\u60a8\u7684\u7ec8\u7aef&#xff08;Windows\u7528\u6237\u4f7f\u7528CMD\u6216PowerShell&#xff0c;macOS\/Linux\u7528\u6237\u4f7f\u7528Terminal&#xff09;&#xff0c;\u6267\u884c\u4ee5\u4e0b\u547d\u4ee4&#xff1a;<\/p>\n<p><span class=\"token comment\"># \u5efa\u8bae\u9996\u5148\u66f4\u65b0pip<\/span><br \/>\npip install <span class=\"token operator\">&#8211;<\/span><span class=\"token operator\">&#8211;<\/span>upgrade pip<\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5\u6570\u636e\u53ef\u89c6\u5316\u5e93<\/span><br \/>\npip install matplotlib<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">2.2<\/span><span class=\"token number\">.2<\/span><\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5\u79d1\u5b66\u8ba1\u7b97\u57fa\u7840\u5e93<\/span><br \/>\npip install numpy<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">1.14<\/span><span class=\"token number\">.2<\/span><\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5\u6570\u636e\u5206\u6790\u6838\u5fc3\u5e93<\/span><br \/>\npip install pandas<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">0.20<\/span><span class=\"token number\">.3<\/span><\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5\u91d1\u878d\u6280\u672f\u6307\u6807\u5206\u6790\u5e93<\/span><br \/>\n<span class=\"token comment\"># \u6ce8\u610f&#xff1a;TA-Lib\u7684\u5b89\u88c5\u8f83\u4e3a\u7279\u6b8a&#xff0c;\u901a\u5e38\u9700\u8981\u5148\u5728\u7cfb\u7edf\u4e2d\u5b89\u88c5\u5176C&#043;&#043;\u4f9d\u8d56\u5e93\u3002<\/span><br \/>\n<span class=\"token comment\"># Windows\u7528\u6237\u53ef\u4e0b\u8f7d\u5bf9\u5e94Python\u7248\u672c\u7684whl\u6587\u4ef6\u5b89\u88c5\u3002<\/span><br \/>\n<span class=\"token comment\"># Linux\/macOS\u7528\u6237\u53ef\u901a\u8fc7\u5305\u7ba1\u7406\u5668\u5b89\u88c5&#xff08;\u5982: sudo apt-get install libta-lib-dev&#xff09;<\/span><br \/>\npip install TA<span class=\"token operator\">&#8211;<\/span>Lib<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">0.4<\/span><span class=\"token number\">.16<\/span><\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5HDF5\u6587\u4ef6\u8bfb\u5199\u5e93&#xff0c;\u7528\u4e8e\u9ad8\u6548\u5b58\u50a8\u5927\u89c4\u6a21\u6570\u636e<\/span><br \/>\npip install tables<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">3.4<\/span><span class=\"token number\">.2<\/span><\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5Jupyter Notebook\u5e73\u53f0<\/span><br \/>\npip install jupyter<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">1.0<\/span><span class=\"token number\">.0<\/span><\/p>\n<h4>1.2 \u5e93\u529f\u80fd\u7b80\u4ecb<\/h4>\n<ul>\n<li>Matplotlib: Python\u7684\u7ed8\u56fe\u5e93&#xff0c;\u7528\u4e8e\u521b\u5efa\u9759\u6001\u3001\u52a8\u6001\u548c\u4ea4\u4e92\u5f0f\u7684\u53ef\u89c6\u5316\u56fe\u8868\u3002<\/li>\n<li>NumPy: \u63d0\u4f9b\u4e86\u5f3a\u5927\u7684N\u7ef4\u6570\u7ec4\u5bf9\u8c61\u548c\u76f8\u5173\u8fd0\u7b97\u51fd\u6570&#xff0c;\u662fPython\u79d1\u5b66\u8ba1\u7b97\u7684\u57fa\u77f3\u3002<\/li>\n<li>Pandas: \u63d0\u4f9b\u4e86\u9ad8\u6027\u80fd\u3001\u6613\u4e8e\u4f7f\u7528\u7684\u6570\u636e\u7ed3\u6784&#xff08;\u5982DataFrame&#xff09;\u548c\u6570\u636e\u5206\u6790\u5de5\u5177\u3002<\/li>\n<li>TA-Lib: \u5e7f\u6cdb\u7528\u4e8e\u91d1\u878d\u5e02\u573a\u5206\u6790&#xff0c;\u63d0\u4f9b\u4e86\u5927\u91cf\u7684\u6280\u672f\u5206\u6790\u6307\u6807&#xff08;\u5982MACD, RSI\u7b49&#xff09;\u3002<\/li>\n<li>Tables (PyTables): \u57fa\u4e8eHDF5\u683c\u5f0f&#xff0c;\u7528\u4e8e\u7ba1\u7406\u548c\u8bbf\u95ee\u5927\u578b\u6570\u636e\u96c6&#xff0c;\u8bfb\u5199\u901f\u5ea6\u5feb&#xff0c;\u7279\u522b\u9002\u5408\u5904\u7406TB\u7ea7\u522b\u7684\u6570\u636e\u3002<\/li>\n<li>Jupyter: \u4e00\u4e2a\u5f3a\u5927\u7684\u4ea4\u4e92\u5f0f\u8ba1\u7b97\u5e73\u53f0&#xff0c;\u662f\u6211\u4eec\u63a5\u4e0b\u6765\u8981\u91cd\u70b9\u4ecb\u7ecd\u7684\u5de5\u5177\u3002<\/li>\n<\/ul>\n<hr \/>\n<h3>1.2 Jupyter Notebook \u5b8c\u5168\u5165\u95e8<\/h3>\n<p>Jupyter Notebook \u662f\u4e00\u4e2a\u5f00\u6e90\u7684Web\u5e94\u7528\u7a0b\u5e8f&#xff0c;\u5141\u8bb8\u7528\u6237\u521b\u5efa\u548c\u5171\u4eab\u5305\u542b\u4ee3\u7801\u3001\u65b9\u7a0b\u5f0f\u3001\u53ef\u89c6\u5316\u548c\u53d9\u8ff0\u6027\u6587\u672c\u7684\u6587\u6863\u3002\u5b83\u5df2\u6210\u4e3a\u6570\u636e\u79d1\u5b66\u5bb6\u3001\u7814\u7a76\u4eba\u5458\u548c\u5de5\u7a0b\u5e08\u8fdb\u884c\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790\u3001\u6a21\u578b\u539f\u578b\u8bbe\u8ba1\u548c\u6559\u5b66\u6f14\u793a\u7684\u9996\u9009\u5de5\u5177\u3002<\/p>\n<h4>1.2.1 Jupyter Notebook \u4ecb\u7ecd<\/h4>\n<ul>\n<li>\n<p>Web\u7248\u7684IPython: \u5b83\u53ef\u4ee5\u770b\u4f5c\u662fIPython shell\u7684\u8d85\u7ea7\u8fdb\u5316\u7248&#xff0c;\u5c06IPython\u7684\u4ea4\u4e92\u5f0f\u8ba1\u7b97\u80fd\u529b\u4e0eWeb\u6280\u672f\u76f8\u7ed3\u5408&#xff0c;\u63d0\u4f9b\u4e86\u66f4\u4e30\u5bcc\u3001\u66f4\u76f4\u89c2\u7684\u7528\u6237\u4f53\u9a8c\u3002<\/p>\n<\/li>\n<li>\n<p>\u540d\u5b57\u7684\u7531\u6765:<\/p>\n<ul>\n<li>Ju: \u4ee3\u8868 Julia \u8bed\u8a00<\/li>\n<li>Py: \u4ee3\u8868 Python \u8bed\u8a00<\/li>\n<li>ter: \u4ee3\u8868 R \u8bed\u8a00<\/li>\n<li>\u8fd9\u4e2a\u540d\u5b57\u4f53\u73b0\u4e86\u5176\u652f\u6301\u591a\u79cd\u7f16\u7a0b\u8bed\u8a00\u7684\u6838\u5fc3\u8bbe\u8ba1\u7406\u5ff5\u3002\u540c\u65f6&#xff0c;Jupyter\u7684\u53d1\u97f3\u4e0e\u6728\u661f&#xff08;Jupiter&#xff09;\u76f8\u4f3c&#xff0c;\u4e5f\u5bd3\u610f\u5176\u5728\u6570\u636e\u79d1\u5b66\u9886\u57df\u7684\u4e2d\u5fc3\u5730\u4f4d&#xff0c;\u5982\u540c\u592a\u9633\u7cfb\u4e2d\u7684\u6728\u661f\u4e00\u6837\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>\u6838\u5fc3\u529f\u80fd: \u5b83\u5b8c\u7f8e\u878d\u5408\u4e86\u7f16\u7a0b\u3001\u5199\u6587\u6863\u3001\u8bb0\u7b14\u8bb0\u3001\u505a\u5c55\u793a\u56db\u5927\u529f\u80fd\u3002\u4f60\u53ef\u4ee5\u5c06\u4ee3\u7801\u3001\u4ee3\u7801\u7684\u8fd0\u884c\u7ed3\u679c\u3001Markdown\u683c\u5f0f\u7684\u89e3\u91ca\u6027\u6587\u672c\u3001\u6570\u5b66\u516c\u5f0f\u3001\u56fe\u7247\u7b49\u5185\u5bb9\u7ec4\u5408\u5728\u4e00\u4e2a\u6587\u6863\u4e2d\u3002<\/p>\n<\/li>\n<li>\n<p>\u6587\u4ef6\u683c\u5f0f: Jupyter Notebook\u7684\u6587\u4ef6\u4ee5.ipynb&#xff08;IPython Notebook&#xff09;\u4e3a\u540e\u7f00\u3002\u8fd9\u662f\u4e00\u4e2aJSON\u683c\u5f0f\u7684\u6587\u4ef6&#xff0c;\u7ed3\u6784\u5316\u5730\u5b58\u50a8\u4e86\u6587\u6863\u4e2d\u7684\u6240\u6709\u5185\u5bb9&#xff0c;\u4fbf\u4e8e\u7248\u672c\u63a7\u5236\u548c\u5206\u4eab\u3002<\/p>\n<\/li>\n<\/ul>\n<h4>1.2.2 \u4e3a\u4ec0\u4e48\u6570\u636e\u6316\u6398\u8981\u7528Jupyter Notebook?<\/h4>\n<ul>\n<li>\n<p>\u65e0\u4e0e\u4f26\u6bd4\u7684\u753b\u56fe\u4f18\u52bf:<\/p>\n<ul>\n<li>\u5185\u8054\u663e\u793a (Inline Plotting): \u4ee3\u7801\u5355\u5143\u683c\u4e0b\u65b9\u53ef\u4ee5\u76f4\u63a5\u6e32\u67d3\u51fa\u7531Matplotlib\u3001Seaborn\u7b49\u5e93\u751f\u6210\u7684\u56fe\u50cf\u3002\u8fd9\u79cd\u201c\u4ee3\u7801-\u7ed3\u679c\u201d\u7d27\u5bc6\u7ed3\u5408\u7684\u65b9\u5f0f&#xff0c;\u6781\u5927\u5730\u63d0\u5347\u4e86\u63a2\u7d22\u6027\u6570\u636e\u5206\u6790&#xff08;EDA&#xff09;\u7684\u6548\u7387\u3002\u4f60\u53ef\u4ee5\u968f\u65f6\u4fee\u6539\u4ee3\u7801&#xff0c;\u7acb\u5373\u770b\u5230\u56fe\u8868\u7684\u53d8\u5316&#xff0c;\u65e0\u9700\u5728\u4e0d\u540c\u7a97\u53e3\u95f4\u5207\u6362\u3002<\/li>\n<li>\u4ea4\u4e92\u5f0f\u53ef\u89c6\u5316: \u652f\u6301\u591a\u79cd\u4ea4\u4e92\u5f0f\u7ed8\u56fe\u540e\u7aef&#xff0c;\u53ef\u4ee5\u751f\u6210\u53ef\u7f29\u653e\u3001\u53ef\u62d6\u52a8\u7684\u56fe\u8868&#xff0c;\u4fbf\u4e8e\u6df1\u5165\u63a2\u7d22\u6570\u636e\u7ec6\u8282\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>\u6781\u81f4\u7684\u6570\u636e\u5c55\u793a\u4f18\u52bf:<\/p>\n<ul>\n<li>\u4f18\u96c5\u7684\u8868\u683c: Pandas\u7684DataFrame\u6216Series\u5bf9\u8c61\u5728Jupyter\u4e2d\u4f1a\u81ea\u52a8\u6e32\u67d3\u6210\u683c\u5f0f\u7cbe\u7f8e\u7684HTML\u8868\u683c&#xff0c;\u6e05\u6670\u6613\u8bfb&#xff0c;\u8fdc\u80dc\u4e8e\u5728\u7ec8\u7aef\u6253\u5370\u51fa\u7684\u7eaf\u6587\u672c\u3002<\/li>\n<li>\u5bcc\u6587\u672c\u96c6\u6210: \u4f60\u53ef\u4ee5\u5728\u4ee3\u7801\u4e4b\u95f4\u63d2\u5165\u683c\u5f0f\u4e30\u5bcc\u7684Markdown\u6587\u672c&#xff0c;\u8be6\u7ec6\u89e3\u91ca\u4f60\u7684\u5206\u6790\u601d\u8def\u3001\u6570\u636e\u5904\u7406\u6b65\u9aa4\u548c\u7ed3\u8bba&#xff0c;\u4f7f\u5f97\u6574\u4e2a\u5206\u6790\u6d41\u7a0b\u903b\u8f91\u6e05\u6670&#xff0c;\u6613\u4e8e\u7406\u89e3\u548c\u590d\u73b0\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h4>1.2.3 Jupyter Notebook \u4f7f\u7528\u5165\u95e8 &#8211; Hello World<\/h4>\n<h5>1. \u754c\u9762\u542f\u52a8\u4e0e\u6587\u4ef6\u521b\u5efa<\/h5>\n<p>\u5728\u7ec8\u7aef\u4e2d\u8f93\u5165\u4ee5\u4e0b\u4efb\u4e00\u547d\u4ee4&#xff0c;\u5373\u53ef\u542f\u52a8Jupyter Notebook\u670d\u52a1&#xff1a;<\/p>\n<p>jupyter notebook<br \/>\n<span class=\"token comment\"># \u6216\u8005\u65e7\u7248\u7684\u547d\u4ee4<\/span><br \/>\nipython notebook<\/p>\n<p>\u6267\u884c\u540e&#xff0c;\u4f60\u7684\u9ed8\u8ba4\u6d4f\u89c8\u5668\u4f1a\u81ea\u52a8\u6253\u5f00\u4e00\u4e2a\u65b0\u6807\u7b7e\u9875&#xff0c;\u663e\u793aJupyter\u7684\u6587\u4ef6\u6d4f\u89c8\u5668\u754c\u9762&#xff08;Dashboard&#xff09;&#xff0c;\u901a\u5e38\u5730\u5740\u4e3ahttp:\/\/localhost:8888\/\u3002<\/p>\n<ul>\n<li>\u521b\u5efa\u6587\u4ef6: \u5728\u9875\u9762\u53f3\u4e0a\u89d2\u70b9\u51fb New -&gt; Python 3 (\u6216\u5176\u4ed6\u4f60\u5b89\u88c5\u7684\u5185\u6838)&#xff0c;\u5373\u53ef\u521b\u5efa\u4e00\u4e2a\u65b0\u7684Notebook\u6587\u4ef6\u3002<\/li>\n<\/ul>\n<h5>2. Cell (\u5355\u5143\u683c) \u7684\u6838\u5fc3\u64cd\u4f5c<\/h5>\n<p>Notebook\u7531\u4e00\u7cfb\u5217\u7684 Cell \u7ec4\u6210\u3002\u4e00\u4e2aCell\u662f\u4ee3\u7801\u6216\u6587\u672c\u7684\u57fa\u672c\u5355\u4f4d&#xff0c;\u4e00\u5bf9In [&#8230;] (\u8f93\u5165) \u548c Out [&#8230;] (\u8f93\u51fa) \u7684\u4f1a\u8bdd\u88ab\u89c6\u4e3a\u4e00\u4e2a\u4ee3\u7801\u5355\u5143\u3002<\/p>\n<p>\u4e24\u79cd\u6a21\u5f0f:<\/p>\n<ul>\n<li>\u7f16\u8f91\u6a21\u5f0f (Edit Mode): \u5f53\u4f60\u770b\u5230Cell\u7684\u8fb9\u6846\u662f\u7eff\u8272\u65f6&#xff0c;\u4f60\u6b63\u5904\u4e8e\u6b64\u6a21\u5f0f\u3002\u6b64\u65f6\u53ef\u4ee5\u50cf\u5728\u6587\u672c\u7f16\u8f91\u5668\u4e2d\u4e00\u6837\u8f93\u5165\u4ee3\u7801\u6216\u6587\u672c\u3002\n<ul>\n<li>\u8fdb\u5165\u65b9\u5f0f: \u6309 Enter \u952e\u6216\u7528\u9f20\u6807\u76f4\u63a5\u70b9\u51fbCell\u5185\u90e8\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u547d\u4ee4\u6a21\u5f0f (Command Mode): \u5f53Cell\u7684\u8fb9\u6846\u662f\u84dd\u8272\u65f6&#xff0c;\u4f60\u5904\u4e8e\u6b64\u6a21\u5f0f\u3002\u6b64\u6a21\u5f0f\u4e0b&#xff0c;\u952e\u76d8\u8f93\u5165\u4f1a\u88ab\u89e3\u91ca\u4e3a\u5bf9Notebook\u8fdb\u884c\u64cd\u4f5c\u7684\u547d\u4ee4&#xff08;\u5982\u521b\u5efa\u3001\u5220\u9664\u3001\u79fb\u52a8Cell&#xff09;\u3002\n<ul>\n<li>\u8fdb\u5165\u65b9\u5f0f: \u6309 Esc \u952e\u6216\u7528\u9f20\u6807\u70b9\u51fbCell\u7684\u8fb9\u6846\u5916\u90e8\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\u6838\u5fc3\u5feb\u6377\u952e: \u719f\u7ec3\u4f7f\u7528\u5feb\u6377\u952e\u662f\u63d0\u5347\u6548\u7387\u7684\u5173\u952e&#xff01;<\/p>\n<ul>\n<li>\n<p>\u8fd0\u884c\u4ee3\u7801: Shift &#043; Enter (\u8fd0\u884c\u5f53\u524dcell&#xff0c;\u5e76\u81ea\u52a8\u9009\u4e2d\u4e0b\u4e00\u4e2acell)<\/p>\n<ul>\n<li>Ctrl &#043; Enter: \u8fd0\u884c\u5f53\u524dcell&#xff0c;\u4f46\u4e0d\u79fb\u52a8\u7126\u70b9\u3002<\/li>\n<li>Alt &#043; Enter: \u8fd0\u884c\u5f53\u524dcell&#xff0c;\u5e76\u5728\u4e0b\u65b9\u63d2\u5165\u4e00\u4e2a\u65b0\u7684cell\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>\u547d\u4ee4\u6a21\u5f0f (\u84dd\u8272\u8fb9\u6846) \u5feb\u6377\u952e:<\/p>\n<ul>\n<li>A: \u5728\u5f53\u524dcell\u7684 Above (\u4e0a\u65b9) \u6dfb\u52a0\u4e00\u4e2a\u65b0cell\u3002<\/li>\n<li>B: \u5728\u5f53\u524dcell\u7684 Below (\u4e0b\u65b9) \u6dfb\u52a0\u4e00\u4e2a\u65b0cell\u3002<\/li>\n<li>D, D (\u53cc\u51fbD): Delete (\u5220\u9664) \u5f53\u524dcell\u3002<\/li>\n<li>M: \u5c06\u5f53\u524dcell\u7684\u7c7b\u578b\u8f6c\u6362\u4e3a Markdown\u3002<\/li>\n<li>Y: \u5c06\u5f53\u524dcell\u7684\u7c7b\u578b\u8f6c\u6362\u4e3a\u4ee3\u7801 (Code)\u3002<\/li>\n<li>Z: \u64a4\u9500\u5220\u9664\u64cd\u4f5c\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\n<p>\u7f16\u8f91\u6a21\u5f0f (\u7eff\u8272\u8fb9\u6846) \u5feb\u6377\u952e:<\/p>\n<ul>\n<li>Ctrl &#043; \/ (Mac: Cmd &#043; \/): \u4e3a\u4e00\u884c\u6216\u591a\u884c\u4ee3\u7801\u6dfb\u52a0\/\u53d6\u6d88\u6ce8\u91ca\u3002<\/li>\n<li>Tab: \u8865\u5168\u4ee3\u7801&#xff08;\u53d8\u91cf\u540d\u3001\u65b9\u6cd5\u540d\u7b49&#xff09;\u6216\u8fdb\u884c\u7f29\u8fdb\u3002<\/li>\n<li>Shift &#043; Tab: \u663e\u793a\u51fd\u6570\u7684\u6587\u6863\u5b57\u7b26\u4e32&#xff08;docstring&#xff09;\u6216\u63d0\u793a\u4fe1\u606f\u3002<\/li>\n<li>Ctrl &#043; Z (Mac: Cmd &#043; Z): \u56de\u9000\u64a4\u9500\u64cd\u4f5c\u3002<\/li>\n<li>Ctrl &#043; \u9f20\u6807\u70b9\u51fb (Mac: CMD &#043; \u9f20\u6807\u70b9\u51fb): \u542f\u7528\u591a\u5149\u6807\u7f16\u8f91&#xff0c;\u540c\u65f6\u5728\u591a\u4e2a\u4f4d\u7f6e\u8fdb\u884c\u4fee\u6539\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h5>3. Markdown \u6f14\u793a<\/h5>\n<p>Jupyter\u4e2d\u7684Markdown Cell\u529f\u80fd\u975e\u5e38\u5f3a\u5927&#xff0c;\u4ee5\u4e0b\u662f\u4e00\u4e9b\u5e38\u7528\u8bed\u6cd5\u793a\u4f8b\u3002\u5c06\u4e00\u4e2aCell\u7684\u7c7b\u578b\u5207\u6362\u4e3aMarkdown (Esc -&gt; M)&#xff0c;\u7136\u540e\u8f93\u5165\u4ee5\u4e0b\u5185\u5bb9\u5e76\u6309Shift &#043; Enter\u8fd0\u884c&#xff0c;\u5373\u53ef\u770b\u5230\u6e32\u67d3\u6548\u679c\u3002<\/p>\n<hr \/>\n<p>\u70b9\u51fb\u8fd9\u91cc\u67e5\u770b\u66f4\u591a\u5173\u4e8eMarkdown\u7684\u8bed\u6cd5<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6458\u8981: \u672c\u6587\u662f\u6570\u636e\u6316\u6398\u5165\u95e8\u7cfb\u5217\u7684\u7b2c\u4e00\u7bc7&#xff0c;\u65e8\u5728\u5f15\u5bfc\u521d\u5b66\u8005\u5feb\u901f\u642d\u5efa\u4e00\u5957\u5b8c\u6574\u3001\u9ad8\u6548\u7684\u6570\u636e\u6316\u6398\u57fa\u7840\u73af\u5883\u3002\u6211\u4eec\u5c06\u9996\u5148\u4ecb\u7ecd\u5982\u4f55\u5b89\u88c5\u6570\u636e\u79d1\u5b66\u9886\u57df\u7684\u6838\u5fc3Python\u5e93&#xff0c;\u7136\u540e\u8be6\u7ec6\u8bb2\u89e3\u88ab\u8a89\u4e3a\u201c\u6570\u636e\u79d1\u5b66\u795e\u5668\u201d\u7684Jupyter Notebook\u7684\u5b89\u88c5\u3001\u6838\u5fc3\u6982\u5ff5\u53ca\u9ad8\u6548\u4f7f\u7528\u6280\u5de7&#xff0c;\u4e3a\u540e\u7eed\u7684\u6570\u636e\u5206\u6790\u3001\u673a\u5668\u5b66\u4e60\u4e4b\u65c5\u6253\u4e0b\u575a\u5b9e\u7684\u57fa\u7840\u3002 \u4e00\u3001\u6570\u636e\u6316\u6398\u57fa\u7840\u73af\u5883\u5b89\u88c5<br \/>\n\u5728\u5f00\u542f\u6570\u636e\u6316\u6398\u4e4b\u65c5\u524d&#xff0c;\u6240\u8c13\u201c\u5de5\u6b32\u5584\u5176\u4e8b&#xff0c;\u5fc5\u5148\u5229\u5176\u5668\u201d&#xff0c;\u6211\u4eec\u9700\u8981\u5148\u914d\u7f6e<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[542,81,62],"topic":[],"class_list":["post-73426","post","type-post","status-publish","format-standard","hentry","category-server","tag-jupyter","tag-python","tag-62"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.3 - 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