{"id":998471,"date":"2024-12-27T09:33:33","date_gmt":"2024-12-27T01:33:33","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/998471.html"},"modified":"2024-12-27T09:33:35","modified_gmt":"2024-12-27T01:33:35","slug":"python%e5%a6%82%e4%bd%95%e5%88%86%e6%9e%90%e6%95%b0%e6%8d%ae%e7%9a%84","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/998471.html","title":{"rendered":"python\u5982\u4f55\u5206\u6790\u6570\u636e\u7684"},"content":{"rendered":"<p style=\"text-align:center;\" ><img decoding=\"async\" src=\"https:\/\/cdn-kb.worktile.com\/kb\/wp-content\/uploads\/2024\/04\/25073859\/be94b523-0856-468f-aaec-e1d244555a5e.webp\" alt=\"python\u5982\u4f55\u5206\u6790\u6570\u636e\u7684\" \/><\/p>\n<p><p> \u5f00\u5934\u6bb5\u843d\uff1a<br \/><strong>Python\u662f\u4e00\u79cd\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u5176\u5e7f\u6cdb\u5e94\u7528\u4e8e\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u53ef\u89c6\u5316\u3001\u7edf\u8ba1\u5206\u6790\u548c<a href=\"https:\/\/docs.pingcode.com\/ask\/59192.html\" target=\"_blank\">\u673a\u5668\u5b66\u4e60<\/a>\u7b49\u9886\u57df\u3002Python\u7684\u4e30\u5bcc\u5e93\u652f\u6301\u3001\u7b80\u5355\u6613\u5b66\u7684\u8bed\u6cd5\u3001\u5f3a\u5927\u7684\u793e\u533a\u652f\u6301\uff0c\u4f7f\u5176\u6210\u4e3a\u6570\u636e\u5206\u6790\u7684\u9996\u9009\u8bed\u8a00<\/strong>\u3002\u5176\u4e2d\uff0cPandas\u5e93\u7684\u7075\u6d3b\u6027\u548c\u529f\u80fd\u5f3a\u5927\u3001Matplotlib\u548cSeaborn\u7684\u53ef\u89c6\u5316\u80fd\u529b\u3001Scikit-learn\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u652f\u6301\u7b49\u90fd\u662fPython\u5728\u6570\u636e\u5206\u6790\u4e2d\u53d7\u6b22\u8fce\u7684\u539f\u56e0\u3002Pandas\u5e93\u662fPython\u6570\u636e\u5206\u6790\u7684\u6838\u5fc3\u5de5\u5177\u4e4b\u4e00\uff0c\u5b83\u63d0\u4f9b\u4e86\u9ad8\u6548\u3001\u4fbf\u6377\u7684\u6570\u636e\u64cd\u4f5c\u80fd\u529b\uff0c\u4f7f\u5f97\u6570\u636e\u5904\u7406\u5de5\u4f5c\u53d8\u5f97\u7b80\u5355\u76f4\u89c2\u3002\u901a\u8fc7Pandas\uff0c\u6211\u4eec\u53ef\u4ee5\u8f7b\u677e\u5730\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u8f6c\u6362\u548c\u6570\u636e\u805a\u5408\u7b49\u64cd\u4f5c\u3002<\/p>\n<\/p>\n<p><h2>\u6b63\u6587\uff1a<\/h2>\n<\/p>\n<p><h3>\u4e00\u3001PANDAS\u5e93\u5728\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e94\u7528<\/h3>\n<\/p>\n<p><p>Pandas\u662fPython\u4e2d\u7684\u4e00\u4e2a\u6570\u636e\u5206\u6790\u5e93\uff0c\u4e13\u4e3a\u6570\u636e\u64cd\u4f5c\u548c\u5206\u6790\u800c\u8bbe\u8ba1\u3002\u5b83\u63d0\u4f9b\u4e86\u4e24\u4e2a\u91cd\u8981\u7684\u6570\u636e\u7ed3\u6784\uff1aSeries\u548cDataFrame\u3002Series\u662f\u4e00\u7ef4\u6570\u636e\u7ed3\u6784\uff0c\u7c7b\u4f3c\u4e8e\u5217\u8868\uff0c\u4f46\u5177\u6709\u6807\u7b7e\uff1bDataFrame\u662f\u4e8c\u7ef4\u6570\u636e\u7ed3\u6784\uff0c\u7c7b\u4f3c\u4e8e\u7535\u5b50\u8868\u683c\u6216SQL\u8868\u3002<\/p>\n<\/p>\n<p><p><strong>Pandas\u7684\u4e3b\u8981\u529f\u80fd\u5305\u62ec\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u8f6c\u6362\u548c\u6570\u636e\u805a\u5408<\/strong>\u3002\u6570\u636e\u6e05\u6d17\u662f\u6307\u5904\u7406\u6570\u636e\u4e2d\u7684\u7f3a\u5931\u503c\u3001\u91cd\u590d\u503c\u548c\u5f02\u5e38\u503c\u3002Pandas\u63d0\u4f9b\u4e86\u591a\u79cd\u65b9\u6cd5\u6765\u8bc6\u522b\u548c\u5904\u7406\u8fd9\u4e9b\u6570\u636e\u95ee\u9898\u3002\u6570\u636e\u8f6c\u6362\u6d89\u53ca\u5c06\u6570\u636e\u4ece\u4e00\u79cd\u683c\u5f0f\u8f6c\u6362\u4e3a\u53e6\u4e00\u79cd\u683c\u5f0f\uff0c\u5982\u4ece\u5b57\u7b26\u4e32\u5230\u6570\u503c\u578b\u3002Pandas\u5141\u8bb8\u7528\u6237\u8f7b\u677e\u5730\u8fdb\u884c\u8fd9\u4e9b\u8f6c\u6362\u64cd\u4f5c\u3002\u6570\u636e\u805a\u5408\u662f\u6307\u901a\u8fc7\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\u548c\u6c47\u603b\uff0c\u63d0\u53d6\u6709\u610f\u4e49\u7684\u4fe1\u606f\u3002Pandas\u63d0\u4f9b\u4e86\u7075\u6d3b\u7684\u5206\u7ec4\u529f\u80fd\uff0c\u53ef\u4ee5\u6839\u636e\u591a\u4e2a\u6761\u4ef6\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u5e94\u7528\u5404\u79cd\u805a\u5408\u51fd\u6570\u3002<\/p>\n<\/p>\n<p><h3>\u4e8c\u3001\u6570\u636e\u53ef\u89c6\u5316\u5de5\u5177MATPLOTLIB\u548cSEABORN<\/h3>\n<\/p>\n<p><p>Matplotlib\u662fPython\u4e2d\u6700\u57fa\u672c\u7684\u7ed8\u56fe\u5e93\uff0c\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u53ef\u89c6\u5316\u529f\u80fd\u3002\u5b83\u53ef\u4ee5\u521b\u5efa\u5404\u79cd\u7c7b\u578b\u7684\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u3001\u6563\u70b9\u56fe\u548c\u76f4\u65b9\u56fe\u3002Matplotlib\u7684\u7075\u6d3b\u6027\u4f7f\u5f97\u5b83\u53ef\u4ee5\u521b\u5efa\u590d\u6742\u7684\u5b9a\u5236\u56fe\u5f62\uff0c\u6ee1\u8db3\u4e0d\u540c\u6570\u636e\u53ef\u89c6\u5316\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><p><strong>Seaborn\u662f\u57fa\u4e8eMatplotlib\u7684\u9ad8\u7ea7\u53ef\u89c6\u5316\u5e93\uff0c\u4e13\u4e3a\u7edf\u8ba1\u56fe\u5f62\u800c\u8bbe\u8ba1<\/strong>\u3002\u5b83\u7b80\u5316\u4e86\u590d\u6742\u56fe\u5f62\u7684\u521b\u5efa\u8fc7\u7a0b\uff0c\u5e76\u63d0\u4f9b\u4e86\u7f8e\u89c2\u7684\u9ed8\u8ba4\u6837\u5f0f\u3002Seaborn\u80fd\u591f\u8f7b\u677e\u521b\u5efa\u5982\u7bb1\u7ebf\u56fe\u3001\u70ed\u56fe\u548c\u5c0f\u63d0\u7434\u56fe\u7b49\u7edf\u8ba1\u56fe\u5f62\uff0c\u5e76\u652f\u6301\u76f4\u63a5\u4e0ePandas\u6570\u636e\u7ed3\u6784\u8fdb\u884c\u4ea4\u4e92\u3002\u901a\u8fc7Seaborn\uff0c\u7528\u6237\u53ef\u4ee5\u5feb\u901f\u3001\u76f4\u89c2\u5730\u4ece\u6570\u636e\u4e2d\u53d1\u73b0\u6a21\u5f0f\u548c\u5173\u7cfb\u3002<\/p>\n<\/p>\n<p><h3>\u4e09\u3001\u7edf\u8ba1\u5206\u6790\u548cSCIPY\u5e93<\/h3>\n<\/p>\n<p><p>Scipy\u662f\u4e00\u4e2a\u5f00\u6e90\u7684Python\u5e93\uff0c\u4e13\u4e3a\u79d1\u5b66\u548c\u5de5\u7a0b\u8ba1\u7b97\u800c\u8bbe\u8ba1\u3002\u5b83\u6269\u5c55\u4e86Numpy\u7684\u529f\u80fd\uff0c\u63d0\u4f9b\u4e86\u66f4\u591a\u7684\u6570\u5b66\u3001\u79d1\u5b66\u548c\u5de5\u7a0b\u8ba1\u7b97\u529f\u80fd\u3002Scipy\u5305\u542b\u591a\u79cd\u6a21\u5757\uff0c\u5982\u4f18\u5316\u3001\u7ebf\u6027\u4ee3\u6570\u3001\u79ef\u5206\u548c\u7edf\u8ba1\u7b49\u3002<\/p>\n<\/p>\n<p><p><strong>\u5728\u7edf\u8ba1\u5206\u6790\u4e2d\uff0cScipy\u63d0\u4f9b\u4e86\u591a\u79cd\u7edf\u8ba1\u68c0\u9a8c\u548c\u5206\u5e03\u529f\u80fd<\/strong>\u3002\u7528\u6237\u53ef\u4ee5\u4f7f\u7528Scipy\u8fdb\u884ct\u68c0\u9a8c\u3001\u5361\u65b9\u68c0\u9a8c\u548c\u65b9\u5dee\u5206\u6790\u7b49\u5e38\u7528\u7684\u7edf\u8ba1\u68c0\u9a8c\u3002\u6b64\u5916\uff0cScipy\u652f\u6301\u591a\u79cd\u6982\u7387\u5206\u5e03\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7Scipy\u751f\u6210\u968f\u673a\u6570\u3001\u8ba1\u7b97\u5206\u5e03\u53c2\u6570\u548c\u8fdb\u884c\u5206\u5e03\u62df\u5408\u3002Scipy\u7684\u5f3a\u5927\u529f\u80fd\u4f7f\u5f97\u5b83\u5728\u6570\u636e\u5206\u6790\u4e2d\u626e\u6f14\u7740\u91cd\u8981\u89d2\u8272\uff0c\u5c24\u5176\u662f\u5728\u9700\u8981\u8fdb\u884c\u590d\u6742\u6570\u5b66\u8ba1\u7b97\u7684\u573a\u666f\u4e0b\u3002<\/p>\n<\/p>\n<p><h3>\u56db\u3001\u673a\u5668\u5b66\u4e60\u4e0eSCIKIT-LEARN<\/h3>\n<\/p>\n<p><p>Scikit-learn\u662fPython\u4e2d\u6700\u53d7\u6b22\u8fce\u7684\u673a\u5668\u5b66\u4e60\u5e93\u4e4b\u4e00\uff0c\u63d0\u4f9b\u4e86\u7b80\u5355\u9ad8\u6548\u7684\u5de5\u5177\uff0c\u652f\u6301\u6570\u636e\u6316\u6398\u548c\u6570\u636e\u5206\u6790\u4efb\u52a1\u3002Scikit-learn\u5efa\u7acb\u5728Numpy\u3001Scipy\u548cMatplotlib\u4e4b\u4e0a\uff0c\u5177\u6709\u4e00\u81f4\u7684API\uff0c\u4fbf\u4e8e\u5feb\u901f\u6784\u5efa\u548c\u6d4b\u8bd5\u673a\u5668\u5b66\u4e60\u6a21\u578b\u3002<\/p>\n<\/p>\n<p><p><strong>Scikit-learn\u63d0\u4f9b\u4e86\u4e30\u5bcc\u7684\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\uff0c\u5305\u62ec\u5206\u7c7b\u3001\u56de\u5f52\u3001\u805a\u7c7b\u548c\u964d\u7ef4\u7b49<\/strong>\u3002\u901a\u8fc7Scikit-learn\uff0c\u7528\u6237\u53ef\u4ee5\u8f7b\u677e\u5b9e\u73b0\u673a\u5668\u5b66\u4e60\u6a21\u578b\u7684\u8bad\u7ec3\u3001\u8bc4\u4f30\u548c\u9884\u6d4b\u3002\u6b64\u5916\uff0cScikit-learn\u8fd8\u63d0\u4f9b\u4e86\u591a\u79cd\u9884\u5904\u7406\u5de5\u5177\uff0c\u5982\u6807\u51c6\u5316\u3001\u5f52\u4e00\u5316\u548c\u7f16\u7801\u5668\uff0c\u5e2e\u52a9\u7528\u6237\u51c6\u5907\u548c\u8f6c\u6362\u6570\u636e\uff0c\u4ee5\u9002\u5e94\u4e0d\u540c\u7684\u6a21\u578b\u9700\u6c42\u3002<\/p>\n<\/p>\n<p><h3>\u4e94\u3001\u6570\u636e\u6e05\u6d17\u548cPREPROCESSING\u6280\u672f<\/h3>\n<\/p>\n<p><p>\u6570\u636e\u6e05\u6d17\u662f\u6570\u636e\u5206\u6790\u8fc7\u7a0b\u4e2d\u81f3\u5173\u91cd\u8981\u7684\u4e00\u6b65\uff0c\u76f4\u63a5\u5f71\u54cd\u5206\u6790\u7ed3\u679c\u7684\u51c6\u786e\u6027\u3002Python\u63d0\u4f9b\u4e86\u591a\u79cd\u5de5\u5177\u548c\u6280\u672f\u6765\u8fdb\u884c\u6570\u636e\u6e05\u6d17\u3002<\/p>\n<\/p>\n<p><p><strong>\u6570\u636e\u6e05\u6d17\u7684\u5173\u952e\u6b65\u9aa4\u5305\u62ec\u5904\u7406\u7f3a\u5931\u503c\u3001\u53bb\u9664\u91cd\u590d\u503c\u548c\u5f02\u5e38\u503c\u68c0\u6d4b<\/strong>\u3002\u5728Pandas\u4e2d\uff0c\u7528\u6237\u53ef\u4ee5\u4f7f\u7528<code>dropna()<\/code>\u65b9\u6cd5\u5220\u9664\u7f3a\u5931\u503c\u6216\u4f7f\u7528<code>fillna()<\/code>\u65b9\u6cd5\u586b\u5145\u7f3a\u5931\u503c\u3002\u5bf9\u4e8e\u91cd\u590d\u503c\uff0cPandas\u63d0\u4f9b\u4e86<code>drop_duplicates()<\/code>\u65b9\u6cd5\u6765\u8bc6\u522b\u548c\u5220\u9664\u3002\u5728\u68c0\u6d4b\u5f02\u5e38\u503c\u65f6\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u7ed8\u5236\u7bb1\u7ebf\u56fe\u6216\u8ba1\u7b97\u5206\u4f4d\u6570\u6765\u8bc6\u522b\u6570\u636e\u4e2d\u7684\u5f02\u5e38\u70b9\u3002<\/p>\n<\/p>\n<p><h3>\u516d\u3001\u6570\u636e\u8f6c\u6362\u4e0eFEATURE ENGINEERING<\/h3>\n<\/p>\n<p><p>\u6570\u636e\u8f6c\u6362\u548c\u7279\u5f81\u5de5\u7a0b\u662f\u63d0\u9ad8\u6a21\u578b\u6027\u80fd\u7684\u91cd\u8981\u6b65\u9aa4\u3002\u7279\u5f81\u5de5\u7a0b\u662f\u6307\u901a\u8fc7\u6570\u636e\u8f6c\u6362\u548c\u7ec4\u5408\u6765\u521b\u5efa\u65b0\u7684\u7279\u5f81\uff0c\u4ee5\u4fbf\u66f4\u597d\u5730\u8868\u793a\u6570\u636e\u3002<\/p>\n<\/p>\n<p><p><strong>\u5e38\u89c1\u7684\u6570\u636e\u8f6c\u6362\u6280\u672f\u5305\u62ec\u6807\u51c6\u5316\u3001\u5f52\u4e00\u5316\u548c\u7f16\u7801<\/strong>\u3002\u6807\u51c6\u5316\u662f\u5c06\u6570\u636e\u8f6c\u6362\u4e3a\u5747\u503c\u4e3a0\u3001\u6807\u51c6\u5dee\u4e3a1\u7684\u5206\u5e03\uff0c\u8fd9\u5bf9\u4e8e\u9700\u8981\u7f29\u653e\u7684\u7b97\u6cd5\uff08\u5982SVM\uff09\u5c24\u4e3a\u91cd\u8981\u3002\u5f52\u4e00\u5316\u662f\u5c06\u6570\u636e\u7f29\u653e\u5230\u7279\u5b9a\u8303\u56f4\uff08\u59820\u52301\uff09\uff0c\u901a\u5e38\u7528\u4e8e\u8ddd\u79bb\u5ea6\u91cf\u7b97\u6cd5\u3002\u7f16\u7801\u662f\u5c06\u5206\u7c7b\u7279\u5f81\u8f6c\u6362\u4e3a\u6570\u503c\u7279\u5f81\uff0c\u5e38\u7528\u7684\u65b9\u6cd5\u6709\u72ec\u70ed\u7f16\u7801\u548c\u6807\u7b7e\u7f16\u7801\u3002<\/p>\n<\/p>\n<p><h3>\u4e03\u3001\u6570\u636e\u805a\u5408\u4e0eGROUPBY\u64cd\u4f5c<\/h3>\n<\/p>\n<p><p>\u6570\u636e\u805a\u5408\u662f\u63d0\u53d6\u6709\u610f\u4e49\u7684\u4fe1\u606f\u548c\u89c1\u89e3\u7684\u5173\u952e\u6b65\u9aa4\u3002\u5728Python\u4e2d\uff0cPandas\u7684<code>groupby()<\/code>\u51fd\u6570\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u805a\u5408\u529f\u80fd\u3002<\/p>\n<\/p>\n<p><p><strong>\u901a\u8fc7<code>groupby()<\/code>\u51fd\u6570\uff0c\u7528\u6237\u53ef\u4ee5\u6839\u636e\u4e00\u4e2a\u6216\u591a\u4e2a\u6761\u4ef6\u5bf9\u6570\u636e\u8fdb\u884c\u5206\u7ec4\uff0c\u5e76\u5e94\u7528\u5404\u79cd\u805a\u5408\u51fd\u6570<\/strong>\u3002\u5e38\u7528\u7684\u805a\u5408\u51fd\u6570\u5305\u62ec\u6c42\u548c\u3001\u8ba1\u6570\u3001\u5e73\u5747\u503c\u548c\u6700\u5927\u503c\u7b49\u3002Pandas\u8fd8\u652f\u6301\u81ea\u5b9a\u4e49\u805a\u5408\u51fd\u6570\uff0c\u4f7f\u5f97\u6570\u636e\u805a\u5408\u66f4\u52a0\u7075\u6d3b\u3002\u6b64\u5916\uff0c\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u591a\u7ea7\u7d22\u5f15\u8fdb\u884c\u591a\u5c42\u6b21\u7684\u6570\u636e\u5206\u7ec4\u548c\u805a\u5408\uff0c\u9002\u7528\u4e8e\u590d\u6742\u7684\u6570\u636e\u5206\u6790\u4efb\u52a1\u3002<\/p>\n<\/p>\n<p><h3>\u516b\u3001\u65f6\u95f4\u5e8f\u5217\u5206\u6790\u4e0eSTATS MODELS<\/h3>\n<\/p>\n<p><p>\u65f6\u95f4\u5e8f\u5217\u5206\u6790\u662f\u6307\u5bf9\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u8fdb\u884c\u5efa\u6a21\u548c\u9884\u6d4b\u3002\u5728Python\u4e2d\uff0cStatsmodels\u662f\u4e00\u4e2a\u5f3a\u5927\u7684\u65f6\u95f4\u5e8f\u5217\u5206\u6790\u5e93\u3002<\/p>\n<\/p>\n<p><p><strong>Statsmodels\u63d0\u4f9b\u4e86\u591a\u79cd\u65f6\u95f4\u5e8f\u5217\u6a21\u578b\uff0c\u5982ARIMA\u3001SARIMA\u548cVAR<\/strong>\u3002\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u8fd9\u4e9b\u6a21\u578b\u5bf9\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u8fdb\u884c\u5efa\u6a21\u548c\u9884\u6d4b\u3002\u6b64\u5916\uff0cStatsmodels\u652f\u6301\u65f6\u95f4\u5e8f\u5217\u6570\u636e\u7684\u5e73\u7a33\u6027\u68c0\u6d4b\u548c\u81ea\u76f8\u5173\u5206\u6790\uff0c\u5e2e\u52a9\u7528\u6237\u9009\u62e9\u5408\u9002\u7684\u6a21\u578b\u548c\u53c2\u6570\u3002\u65f6\u95f4\u5e8f\u5217\u5206\u6790\u5728\u91d1\u878d\u5e02\u573a\u5206\u6790\u3001\u7ecf\u6d4e\u9884\u6d4b\u548c\u4f20\u611f\u5668\u6570\u636e\u5206\u6790\u7b49\u9886\u57df\u5177\u6709\u91cd\u8981\u5e94\u7528\u3002<\/p>\n<\/p>\n<p><h3>\u4e5d\u3001\u6570\u636e\u53ef\u89c6\u5316\u9ad8\u7ea7\u6280\u5de7<\/h3>\n<\/p>\n<p><p>\u5728\u6570\u636e\u5206\u6790\u4e2d\uff0c\u6570\u636e\u53ef\u89c6\u5316\u662f\u5448\u73b0\u6570\u636e\u548c\u53d1\u73b0\u6a21\u5f0f\u7684\u5173\u952e\u6b65\u9aa4\u3002\u901a\u8fc7\u9ad8\u7ea7\u53ef\u89c6\u5316\u6280\u5de7\uff0c\u7528\u6237\u53ef\u4ee5\u521b\u5efa\u66f4\u5177\u6d1e\u5bdf\u529b\u7684\u56fe\u5f62\u3002<\/p>\n<\/p>\n<p><p><strong>\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u7ed3\u5408\u4f7f\u7528Matplotlib\u548cSeaborn\u5b9e\u73b0\u9ad8\u7ea7\u6570\u636e\u53ef\u89c6\u5316<\/strong>\u3002\u4f8b\u5982\uff0c\u4f7f\u7528FacetGrid\u521b\u5efa\u591a\u7ef4\u6570\u636e\u7684\u7f51\u683c\u56fe\uff0c\u4f7f\u7528P<a href=\"https:\/\/docs.pingcode.com\/blog\/59162.html\" target=\"_blank\">AI<\/a>rPlot\u7ed8\u5236\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u77e9\u9635\uff0c\u6216\u4f7f\u7528Heatmap\u663e\u793a\u76f8\u5173\u6027\u77e9\u9635\u3002\u6b64\u5916\uff0c\u7528\u6237\u53ef\u4ee5\u81ea\u5b9a\u4e49\u56fe\u5f62\u6837\u5f0f\u3001\u989c\u8272\u548c\u6ce8\u91ca\uff0c\u4ee5\u63d0\u9ad8\u56fe\u5f62\u7684\u53ef\u8bfb\u6027\u548c\u7f8e\u89c2\u5ea6\u3002<\/p>\n<\/p>\n<p><h3>\u5341\u3001\u6570\u636e\u5206\u6790\u9879\u76ee\u7684\u5b9e\u9645\u5e94\u7528<\/h3>\n<\/p>\n<p><p>\u6570\u636e\u5206\u6790\u5728\u5404\u4e2a\u884c\u4e1a\u548c\u9886\u57df\u90fd\u6709\u5e7f\u6cdb\u5e94\u7528\u3002\u901a\u8fc7Python\u8fdb\u884c\u6570\u636e\u5206\u6790\uff0c\u7528\u6237\u53ef\u4ee5\u89e3\u51b3\u5404\u79cd\u5b9e\u9645\u95ee\u9898\u3002<\/p>\n<\/p>\n<p><p><strong>\u5728\u5546\u4e1a\u9886\u57df\uff0c\u6570\u636e\u5206\u6790\u53ef\u4ee5\u7528\u4e8e\u5ba2\u6237\u7ec6\u5206\u3001\u5e02\u573a\u8d8b\u52bf\u5206\u6790\u548c\u9500\u552e\u9884\u6d4b<\/strong>\u3002\u901a\u8fc7\u5206\u6790\u5ba2\u6237\u884c\u4e3a\u6570\u636e\uff0c\u4f01\u4e1a\u53ef\u4ee5\u5236\u5b9a\u7cbe\u51c6\u7684\u5e02\u573a\u7b56\u7565\uff0c\u63d0\u9ad8\u5ba2\u6237\u6ee1\u610f\u5ea6\u548c\u5fe0\u8bda\u5ea6\u3002\u5728\u533b\u7597\u9886\u57df\uff0c\u6570\u636e\u5206\u6790\u53ef\u4ee5\u7528\u4e8e\u75be\u75c5\u9884\u6d4b\u3001\u533b\u7597\u8bca\u65ad\u548c\u4e2a\u6027\u5316\u6cbb\u7597\u65b9\u6848\u7684\u5236\u5b9a\u3002\u901a\u8fc7\u5206\u6790\u60a3\u8005\u7684\u5065\u5eb7\u6570\u636e\uff0c\u533b\u751f\u53ef\u4ee5\u63d0\u4f9b\u66f4\u7cbe\u51c6\u7684\u8bca\u65ad\u548c\u6cbb\u7597\u5efa\u8bae\u3002<\/p>\n<\/p>\n<p><h3>\u5341\u4e00\u3001\u6570\u636e\u5206\u6790\u4e2d\u7684\u6311\u6218\u4e0e\u89e3\u51b3\u65b9\u6848<\/h3>\n<\/p>\n<p><p>\u5c3d\u7ba1Python\u63d0\u4f9b\u4e86\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u4f46\u6570\u636e\u5206\u6790\u8fc7\u7a0b\u4e2d\u4ecd\u7136\u9762\u4e34\u8bb8\u591a\u6311\u6218\u3002<\/p>\n<\/p>\n<p><p><strong>\u6570\u636e\u8d28\u91cf\u95ee\u9898\u662f\u6570\u636e\u5206\u6790\u4e2d\u7684\u5e38\u89c1\u6311\u6218\uff0c\u5305\u62ec\u7f3a\u5931\u503c\u3001\u566a\u58f0\u548c\u4e0d\u4e00\u81f4\u6570\u636e<\/strong>\u3002\u4e3a\u4e86\u5e94\u5bf9\u8fd9\u4e9b\u95ee\u9898\uff0c\u6570\u636e\u6e05\u6d17\u548c\u9884\u5904\u7406\u662f\u5fc5\u4e0d\u53ef\u5c11\u7684\u6b65\u9aa4\u3002\u6b64\u5916\uff0c\u6570\u636e\u5206\u6790\u5e08\u8fd8\u9700\u8981\u5177\u5907\u6570\u636e\u53ef\u89c6\u5316\u548c\u7edf\u8ba1\u5206\u6790\u7684\u6280\u80fd\uff0c\u4ee5\u4fbf\u4ece\u6570\u636e\u4e2d\u63d0\u53d6\u6709\u610f\u4e49\u7684\u4fe1\u606f\u3002<\/p>\n<\/p>\n<p><h3>\u5341\u4e8c\u3001\u672a\u6765\u6570\u636e\u5206\u6790\u7684\u53d1\u5c55\u8d8b\u52bf<\/h3>\n<\/p>\n<p><p>\u968f\u7740\u5927\u6570\u636e\u548c<a href=\"https:\/\/docs.pingcode.com\/tag\/AI\" target=\"_blank\">\u4eba\u5de5\u667a\u80fd<\/a>\u6280\u672f\u7684\u53d1\u5c55\uff0c\u6570\u636e\u5206\u6790\u7684\u672a\u6765\u5145\u6ee1\u4e86\u673a\u9047\u548c\u6311\u6218\u3002<\/p>\n<\/p>\n<p><p><strong>\u6570\u636e\u5206\u6790\u5c06\u8d8a\u6765\u8d8a\u591a\u5730\u4e0e\u673a\u5668\u5b66\u4e60\u548c\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u7ed3\u5408<\/strong>\u3002\u8fd9\u5c06\u63d0\u9ad8\u6570\u636e\u5206\u6790\u7684\u81ea\u52a8\u5316\u6c34\u5e73\uff0c\u589e\u5f3a\u5206\u6790\u80fd\u529b\u3002\u6b64\u5916\uff0c\u6570\u636e\u9690\u79c1\u548c\u5b89\u5168\u95ee\u9898\u4e5f\u5c06\u6210\u4e3a\u672a\u6765\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u8bfe\u9898\u3002\u4f01\u4e1a\u9700\u8981\u5728\u6570\u636e\u5206\u6790\u8fc7\u7a0b\u4e2d\u4fdd\u62a4\u7528\u6237\u9690\u79c1\uff0c\u9075\u5faa\u76f8\u5173\u6cd5\u5f8b\u6cd5\u89c4\u3002<\/p>\n<\/p>\n<p><p>\u901a\u8fc7\u4e0d\u65ad\u5b66\u4e60\u548c\u5b9e\u8df5\uff0c\u6570\u636e\u5206\u6790\u5e08\u53ef\u4ee5\u63d0\u5347\u81ea\u5df1\u7684\u6280\u80fd\uff0c\u5e94\u5bf9\u672a\u6765\u7684\u6570\u636e\u5206\u6790\u6311\u6218\u3002Python\u4f5c\u4e3a\u6570\u636e\u5206\u6790\u7684\u91cd\u8981\u5de5\u5177\uff0c\u5c06\u7ee7\u7eed\u5728\u6570\u636e\u79d1\u5b66\u9886\u57df\u53d1\u6325\u91cd\u8981\u4f5c\u7528\u3002<\/p>\n<\/p>\n<h2><strong>\u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n<p> <strong>\u5982\u4f55\u5728Python\u4e2d\u5bfc\u5165\u6570\u636e\u8fdb\u884c\u5206\u6790\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u6570\u636e\u5206\u6790\u7684\u7b2c\u4e00\u6b65\u901a\u5e38\u662f\u5bfc\u5165\u6570\u636e\u3002\u5e38\u7528\u7684\u5e93\u5982Pandas\u53ef\u4ee5\u8f7b\u677e\u8bfb\u53d6\u591a\u79cd\u683c\u5f0f\u7684\u6570\u636e\uff0c\u5982CSV\u3001Excel\u548cSQL\u6570\u636e\u5e93\u3002\u4f7f\u7528<code>pd.read_csv()<\/code>\u51fd\u6570\u53ef\u4ee5\u5bfc\u5165CSV\u6587\u4ef6\uff0c\u800c<code>pd.read_excel()<\/code>\u5219\u9002\u7528\u4e8eExcel\u6587\u4ef6\u3002\u786e\u4fdd\u5728\u5bfc\u5165\u4e4b\u524d\u5b89\u88c5\u6240\u9700\u7684\u5e93\uff0c\u4f8b\u5982\u901a\u8fc7<code>pip install pandas<\/code>\u3002<\/p>\n<p><strong>Python\u4e2d\u6709\u54ea\u4e9b\u5e38\u7528\u7684\u6570\u636e\u5206\u6790\u5e93\uff1f<\/strong><br \/>\u8fdb\u884c\u6570\u636e\u5206\u6790\u65f6\uff0cPython\u6709\u51e0\u4e2a\u5f3a\u5927\u7684\u5e93\u53ef\u4f9b\u9009\u62e9\u3002Pandas\u662f\u5904\u7406\u6570\u636e\u8868\u683c\u7684\u9996\u9009\u5de5\u5177\uff0cNumPy\u63d0\u4f9b\u4e86\u5bf9\u5927\u89c4\u6a21\u6570\u7ec4\u548c\u77e9\u9635\u7684\u652f\u6301\uff0cMatplotlib\u548cSeaborn\u5219\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u5e2e\u52a9\u7528\u6237\u7406\u89e3\u6570\u636e\u7684\u5206\u5e03\u548c\u8d8b\u52bf\u3002\u6b64\u5916\uff0cScikit-learn\u7528\u4e8e\u673a\u5668\u5b66\u4e60\u4efb\u52a1\uff0c\u53ef\u4ee5\u7528\u4e8e\u6570\u636e\u5efa\u6a21\u548c\u9884\u6d4b\u3002<\/p>\n<p><strong>\u5982\u4f55\u4f7f\u7528Python\u8fdb\u884c\u6570\u636e\u53ef\u89c6\u5316\uff1f<\/strong><br \/>\u5728Python\u4e2d\uff0c\u6570\u636e\u53ef\u89c6\u5316\u53ef\u4ee5\u901a\u8fc7Matplotlib\u6216Seaborn\u7b49\u5e93\u6765\u5b9e\u73b0\u3002Matplotlib\u63d0\u4f9b\u4e86\u57fa\u672c\u7684\u7ed8\u56fe\u529f\u80fd\uff0c\u5141\u8bb8\u7528\u6237\u521b\u5efa\u5404\u79cd\u56fe\u8868\uff0c\u5982\u6298\u7ebf\u56fe\u3001\u67f1\u72b6\u56fe\u548c\u6563\u70b9\u56fe\u3002Seaborn\u5728\u6b64\u57fa\u7840\u4e0a\u63d0\u4f9b\u4e86\u66f4\u9ad8\u7ea7\u7684\u63a5\u53e3\u548c\u7f8e\u89c2\u7684\u9ed8\u8ba4\u6837\u5f0f\uff0c\u4f7f\u5f97\u7ed8\u5236\u590d\u6742\u7684\u7edf\u8ba1\u56fe\u5f62\u53d8\u5f97\u66f4\u52a0\u7b80\u4fbf\u3002\u7528\u6237\u53ef\u4ee5\u901a\u8fc7\u8c03\u7528\u76f8\u5173\u51fd\u6570\uff0c\u4f20\u5165\u6570\u636e\u96c6\u6765\u751f\u6210\u6240\u9700\u7684\u56fe\u8868\uff0c\u4ece\u800c\u66f4\u597d\u5730\u7406\u89e3\u6570\u636e\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u5f00\u5934\u6bb5\u843d\uff1aPython\u662f\u4e00\u79cd\u5f3a\u5927\u7684\u6570\u636e\u5206\u6790\u5de5\u5177\uff0c\u5176\u5e7f\u6cdb\u5e94\u7528\u4e8e\u6570\u636e\u6e05\u6d17\u3001\u6570\u636e\u53ef\u89c6\u5316\u3001\u7edf\u8ba1\u5206\u6790\u548c\u673a\u5668\u5b66\u4e60\u7b49\u9886\u57df\u3002P [&hellip;]","protected":false},"author":3,"featured_media":998482,"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\/998471"}],"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=998471"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/998471\/revisions"}],"predecessor-version":[{"id":998483,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/998471\/revisions\/998483"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/998482"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=998471"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=998471"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=998471"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}