{"id":96348,"date":"2024-10-20T08:40:17","date_gmt":"2024-10-20T00:40:17","guid":{"rendered":"https:\/\/server.hk\/cnblog\/96348\/"},"modified":"2024-10-20T08:40:17","modified_gmt":"2024-10-20T00:40:17","slug":"pandas-query-%e6%96%b9%e6%b3%95%e6%b7%b1%e5%ba%a6%e7%b8%bd%e7%b5%90%ef%bc%8c%e4%bd%a0%e5%ad%b8%e6%9c%83%e4%ba%86%e5%97%8e%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/server.hk\/cnblog\/96348\/","title":{"rendered":"Pandas Query \u65b9\u6cd5\u6df1\u5ea6\u7e3d\u7d50\uff0c\u4f60\u5b78\u6703\u4e86\u55ce\uff1f"},"content":{"rendered":"<h1 id=\"pandas-query-%e6%96%b9%e6%b3%95%e6%b7%b1%e5%ba%a6%e7%b8%bd%e7%b5%90%ef%bc%8c%e4%bd%a0%e5%ad%b8%e6%9c%83%e4%ba%86%e5%97%8e%ef%bc%9f-yUuqKQRwnQ\">Pandas Query \u65b9\u6cd5\u6df1\u5ea6\u7e3d\u7d50\uff0c\u4f60\u5b78\u6703\u4e86\u55ce\uff1f<\/h1>\n<p>Pandas \u662f\u4e00\u500b\u5f37\u5927\u7684\u6578\u64da\u5206\u6790\u5eab\uff0c\u5ee3\u6cdb\u61c9\u7528\u65bc\u6578\u64da\u79d1\u5b78\u548c\u6a5f\u5668\u5b78\u7fd2\u9818\u57df\u3002\u5176\u63d0\u4f9b\u7684 <code>query()<\/code> \u65b9\u6cd5\uff0c\u8b93\u7528\u6236\u80fd\u5920\u4ee5\u985e\u4f3c SQL \u7684\u8a9e\u6cd5\u4f86\u904e\u6ffe\u548c\u67e5\u8a62\u6578\u64da\uff0c\u9019\u4f7f\u5f97\u6578\u64da\u64cd\u4f5c\u8b8a\u5f97\u66f4\u52a0\u76f4\u89c0\u548c\u9ad8\u6548\u3002\u672c\u6587\u5c07\u6df1\u5165\u63a2\u8a0e Pandas \u7684 <code>query()<\/code> \u65b9\u6cd5\uff0c\u5e6b\u52a9\u4f60\u66f4\u597d\u5730\u7406\u89e3\u548c\u904b\u7528\u9019\u4e00\u529f\u80fd\u3002<\/p>\n<h2 id=\"%e4%bb%80%e9%ba%bc%e6%98%af-pandas-%e7%9a%84-query-%e6%96%b9%e6%b3%95%ef%bc%9f-yUuqKQRwnQ\">\u4ec0\u9ebc\u662f Pandas \u7684 query \u65b9\u6cd5\uff1f<\/h2>\n<p><code>query()<\/code> \u65b9\u6cd5\u5141\u8a31\u7528\u6236\u4f7f\u7528\u5b57\u7b26\u4e32\u8868\u9054\u5f0f\u4f86\u904e\u6ffe DataFrame \u4e2d\u7684\u6578\u64da\u3002\u9019\u7a2e\u65b9\u6cd5\u7684\u512a\u52e2\u5728\u65bc\u5176\u8a9e\u6cd5\u7c21\u6f54\uff0c\u6613\u65bc\u95b1\u8b80\uff0c\u7279\u5225\u9069\u5408\u65bc\u8655\u7406\u5927\u578b\u6578\u64da\u96c6\u3002<\/p>\n<h2 id=\"%e5%9f%ba%e6%9c%ac%e7%94%a8%e6%b3%95-yUuqKQRwnQ\">\u57fa\u672c\u7528\u6cd5<\/h2>\n<p>\u4f7f\u7528 <code>query()<\/code> \u65b9\u6cd5\u7684\u57fa\u672c\u8a9e\u6cd5\u5982\u4e0b\uff1a<\/p>\n<pre><code>DataFrame.query(expr, inplace=False, **kwargs)<\/code><\/pre>\n<p>\u5176\u4e2d\uff0c<code>expr<\/code> \u662f\u4e00\u500b\u5b57\u7b26\u4e32\uff0c\u8868\u793a\u67e5\u8a62\u689d\u4ef6\u3002\u4ee5\u4e0b\u662f\u4e00\u500b\u7c21\u55ae\u7684\u4f8b\u5b50\uff1a<\/p>\n<pre><code>import pandas as pd\n\n# \u5275\u5efa\u4e00\u500b\u793a\u4f8b DataFrame\ndata = {'name': ['Alice', 'Bob', 'Charlie', 'David'],\n        'age': [24, 30, 22, 35],\n        'salary': [50000, 60000, 45000, 70000]}\ndf = pd.DataFrame(data)\n\n# \u4f7f\u7528 query \u65b9\u6cd5\u904e\u6ffe\u5e74\u9f61\u5927\u65bc 25 \u7684\u54e1\u5de5\nresult = df.query('age &gt; 25')\nprint(result)<\/code><\/pre>\n<p>\u5728\u9019\u500b\u4f8b\u5b50\u4e2d\uff0c\u6211\u5011\u5275\u5efa\u4e86\u4e00\u500b\u5305\u542b\u59d3\u540d\u3001\u5e74\u9f61\u548c\u85aa\u6c34\u7684 DataFrame\uff0c\u7136\u5f8c\u4f7f\u7528 <code>query()<\/code> \u65b9\u6cd5\u904e\u6ffe\u51fa\u5e74\u9f61\u5927\u65bc 25 \u7684\u54e1\u5de5\u3002<\/p>\n<h2 id=\"%e4%bd%bf%e7%94%a8%e8%ae%8a%e9%87%8f-yUuqKQRwnQ\">\u4f7f\u7528\u8b8a\u91cf<\/h2>\n<p>\u5728\u67e5\u8a62\u4e2d\u4f7f\u7528\u8b8a\u91cf\u4e5f\u662f <code>query()<\/code> \u65b9\u6cd5\u7684\u4e00\u500b\u91cd\u8981\u7279\u6027\u3002\u53ef\u4ee5\u4f7f\u7528 <code>@<\/code> \u7b26\u865f\u4f86\u5f15\u7528\u5916\u90e8\u8b8a\u91cf\u3002\u4f8b\u5982\uff1a<\/p>\n<pre><code>age_limit = 25\nresult = df.query('age &gt; @age_limit')\nprint(result)<\/code><\/pre>\n<p>\u9019\u6a23\uff0c\u6211\u5011\u5c31\u53ef\u4ee5\u9748\u6d3b\u5730\u4f7f\u7528\u8b8a\u91cf\u4f86\u9032\u884c\u67e5\u8a62\uff0c\u589e\u5f37\u4e86\u4ee3\u78bc\u7684\u53ef\u8b80\u6027\u548c\u53ef\u7dad\u8b77\u6027\u3002<\/p>\n<h2 id=\"%e5%a4%9a%e6%a2%9d%e4%bb%b6%e6%9f%a5%e8%a9%a2-yUuqKQRwnQ\">\u591a\u689d\u4ef6\u67e5\u8a62<\/h2>\n<p>\u4f7f\u7528 <code>query()<\/code> \u65b9\u6cd5\u9032\u884c\u591a\u689d\u4ef6\u67e5\u8a62\u4e5f\u975e\u5e38\u7c21\u55ae\u3002\u53ef\u4ee5\u4f7f\u7528\u908f\u8f2f\u904b\u7b97\u7b26 <code>and<\/code>\u3001<code>or<\/code> \u548c <code>not<\/code> \u4f86\u7d44\u5408\u591a\u500b\u689d\u4ef6\u3002\u4f8b\u5982\uff1a<\/p>\n<pre><code>result = df.query('age &gt; 25 and salary &gt; 55000')\nprint(result)<\/code><\/pre>\n<p>\u9019\u6bb5\u4ee3\u78bc\u5c07\u8fd4\u56de\u5e74\u9f61\u5927\u65bc 25 \u4e14\u85aa\u6c34\u5927\u65bc 55000 \u7684\u54e1\u5de5\u3002<\/p>\n<h2 id=\"%e6%b3%a8%e6%84%8f%e4%ba%8b%e9%a0%85-yUuqKQRwnQ\">\u6ce8\u610f\u4e8b\u9805<\/h2>\n<p>\u5728\u4f7f\u7528 <code>query()<\/code> \u65b9\u6cd5\u6642\uff0c\u6709\u5e7e\u9ede\u9700\u8981\u6ce8\u610f\uff1a<\/p>\n<ul>\n<li>\u67e5\u8a62\u8868\u9054\u5f0f\u4e2d\u7684\u8b8a\u91cf\u5fc5\u9808\u4ee5 <code>@<\/code> \u958b\u982d\u3002<\/li>\n<li>\u67e5\u8a62\u689d\u4ef6\u4e2d\u7684\u5217\u540d\u5982\u679c\u5305\u542b\u7a7a\u683c\u6216\u7279\u6b8a\u5b57\u7b26\uff0c\u9700\u4f7f\u7528\u53cd\u5f15\u865f <code>`<\/code> \u5305\u88f9\u3002<\/li>\n<li>\u5728\u67e5\u8a62\u4e2d\u4f7f\u7528\u7684\u904b\u7b97\u7b26\u5fc5\u9808\u662f Python \u8a9e\u6cd5\u4e2d\u7684\u904b\u7b97\u7b26\u3002<\/li>\n<\/ul>\n<h2 id=\"%e7%b8%bd%e7%b5%90-yUuqKQRwnQ\">\u7e3d\u7d50<\/h2>\n<p>Pandas \u7684 <code>query()<\/code> \u65b9\u6cd5\u63d0\u4f9b\u4e86\u4e00\u7a2e\u7c21\u6f54\u800c\u5f37\u5927\u7684\u65b9\u5f0f\u4f86\u904e\u6ffe\u548c\u67e5\u8a62\u6578\u64da\u3002\u901a\u904e\u4f7f\u7528\u5b57\u7b26\u4e32\u8868\u9054\u5f0f\uff0c\u4f7f\u7528\u8005\u53ef\u4ee5\u8f15\u9b06\u5730\u9032\u884c\u5404\u7a2e\u8907\u96dc\u7684\u67e5\u8a62\uff0c\u4e26\u4e14\u80fd\u5920\u63d0\u9ad8\u4ee3\u78bc\u7684\u53ef\u8b80\u6027\u548c\u53ef\u7dad\u8b77\u6027\u3002\u7121\u8ad6\u662f\u6578\u64da\u5206\u6790\u9084\u662f\u6578\u64da\u8655\u7406\uff0c\u638c\u63e1 <code>query()<\/code> \u65b9\u6cd5\u90fd\u5c07\u5c0d\u4f60\u7684\u5de5\u4f5c\u5927\u6709\u88e8\u76ca\u3002<\/p>\n<p>\u5982\u679c\u4f60\u5c0d\u6578\u64da\u8655\u7406\u548c\u5206\u6790\u6709\u66f4\u9ad8\u7684\u9700\u6c42\uff0c\u8003\u616e\u4f7f\u7528 <a href=\"https:\/\/server.hk\">\u9999\u6e2f VPS<\/a> \u4f86\u642d\u5efa\u4f60\u7684\u6578\u64da\u5206\u6790\u74b0\u5883\uff0c\u4eab\u53d7\u66f4\u9ad8\u6548\u7684\u8a08\u7b97\u8cc7\u6e90\u548c\u9748\u6d3b\u7684\u914d\u7f6e\u9078\u64c7\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6df1\u5165\u63a2\u8a0e Pandas Query \u65b9\u6cd5\uff0c\u638c\u63e1\u6578\u64da\u7be9\u9078\u8207\u64cd\u4f5c\u6280\u5de7\uff0c\u63d0\u5347\u4f60\u7684\u6578\u64da\u5206\u6790\u80fd\u529b\uff0c\u4f60\u5b78\u6703\u4e86\u55ce\uff1f<\/p>\n","protected":false},"author":0,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[101],"tags":[],"class_list":["post-96348","post","type-post","status-publish","format-standard","hentry","category-database"],"_links":{"self":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/96348","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/types\/post"}],"replies":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/comments?post=96348"}],"version-history":[{"count":1,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/96348\/revisions"}],"predecessor-version":[{"id":96349,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/96348\/revisions\/96349"}],"wp:attachment":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/media?parent=96348"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/categories?post=96348"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/tags?post=96348"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}