{"id":855,"date":"2023-07-28T13:03:16","date_gmt":"2023-07-28T13:03:16","guid":{"rendered":"https:\/\/statorials.org\/cn\/python-%e5%8f%8c%e5%90%91%e6%96%b9%e5%b7%ae%e5%88%86%e6%9e%90\/"},"modified":"2023-07-28T13:03:16","modified_gmt":"2023-07-28T13:03:16","slug":"python-%e5%8f%8c%e5%90%91%e6%96%b9%e5%b7%ae%e5%88%86%e6%9e%90","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/python-%e5%8f%8c%e5%90%91%e6%96%b9%e5%b7%ae%e5%88%86%e6%9e%90\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u6267\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/\u53cc\u5411\u65b9\u5dee\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">\u53cc\u5411\u65b9\u5dee\u5206\u6790<\/a>\u7528\u4e8e\u786e\u5b9a\u5df2\u5206\u6210\u4e24\u4e2a\u56e0\u7d20\u7684\u4e09\u4e2a\u6216\u66f4\u591a\u72ec\u7acb\u7ec4\u7684\u5e73\u5747\u503c\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u7edf\u8ba1\u663e\u7740\u5dee\u5f02\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u53cc\u5411\u65b9\u5dee\u5206\u6790\u7684\u76ee\u7684\u662f\u786e\u5b9a\u4e24\u4e2a\u56e0\u7d20\u5bf9\u54cd\u5e94\u53d8\u91cf\u7684\u5f71\u54cd\uff0c\u5e76\u786e\u5b9a\u8fd9\u4e24\u4e2a\u56e0\u7d20\u5bf9\u54cd\u5e94\u53d8\u91cf\u662f\u5426\u5b58\u5728\u4ea4\u4e92\u4f5c\u7528\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1aPython \u4e2d\u7684\u53cc\u5411\u65b9\u5dee\u5206\u6790<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u690d\u7269\u5b66\u5bb6\u60f3\u77e5\u9053\u690d\u7269\u751f\u957f\u662f\u5426\u53d7\u5230\u9633\u5149\u7167\u5c04\u548c\u6d47\u6c34\u9891\u7387\u7684\u5f71\u54cd\u3002\u5979\u79cd\u4e0b\u4e86 30 \u9897\u79cd\u5b50\uff0c\u8ba9\u5b83\u4eec\u5728\u4e0d\u540c\u7684\u9633\u5149\u7167\u5c04\u548c\u6d47\u6c34\u9891\u7387\u6761\u4ef6\u4e0b\u751f\u957f\u4e24\u4e2a\u6708\u3002\u4e24\u4e2a\u6708\u540e\uff0c\u5979\u8bb0\u5f55\u4e86\u6bcf\u682a\u690d\u7269\u7684\u9ad8\u5ea6\uff08\u4ee5\u82f1\u5bf8\u4e3a\u5355\u4f4d\uff09\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f7f\u7528\u4ee5\u4e0b\u6b65\u9aa4\u8fdb\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790\uff0c\u4ee5\u786e\u5b9a\u6d47\u6c34\u9891\u7387\u548c\u9633\u5149\u7167\u5c04\u662f\u5426\u5bf9\u690d\u7269\u751f\u957f\u6709\u663e\u7740\u5f71\u54cd\uff0c\u5e76\u786e\u5b9a\u6d47\u6c34\u9891\u7387\u548c\u9633\u5149\u7167\u5c04\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u4ea4\u4e92\u4f5c\u7528\u3002\u6d47\u6c34\u548c\u66b4\u9732\u5728\u9633\u5149\u4e0b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u7b2c 1 \u6b65\uff1a\u8f93\u5165\u6570\u636e\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u9996\u5148\uff0c\u6211\u4eec\u5c06\u521b\u5efa\u4e00\u4e2a pandas DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u4ee5\u4e0b\u4e09\u4e2a\u53d8\u91cf\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u6c34\uff1a<\/strong>\u6bcf\u682a\u690d\u7269\u6d47\u6c34\u7684\u9891\u7387\uff1a\u6bcf\u5929\u6216\u6bcf\u5468<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u9633\u5149\uff1a<\/strong>\u6bcf\u682a\u690d\u7269\u63a5\u53d7\u7684\u9633\u5149\u7167\u5c04\u91cf\uff1a\u4f4e\u3001\u4e2d\u6216\u9ad8<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>height\uff1a<\/strong>\u4e24\u4e2a\u6708\u540e\u6bcf\u682a\u690d\u7269\u7684\u9ad8\u5ea6\uff08\u82f1\u5bf8\uff09<\/span><\/li>\n<\/ul>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n<span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data<\/span>\ndf = pd.DataFrame({'water': np.repeat(['daily', 'weekly'], 15),\n                   'sun': np.tile(np.repeat(['low', 'med', 'high'], 5), 2),\n                   'height': [6, 6, 6, 5, 6, 5, 5, 6, 4, 5,\n                              6, 6, 7, 8, 7, 3, 4, 4, 4, 5,\n                              4, 4, 4, 4, 4, 5, 6, 6, 7, 8]})\n\n<span style=\"color: #008080;\">#view first ten rows of data<\/span> \ndf[:10]\n\n\twater sun height\n0 daily low 6\n1 daily low 6\n2 daily low 6\n3 daily low 5\n4 daily low 6\n5 daily med 5\n6 daily med 5\n7 daily med 6\n8 daily med 4\n9 daily med 5\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 2\uff1a\u6267\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u4f7f\u7528 statsmodels \u5e93\u4e2d\u7684<a href=\"https:\/\/www.statsmodels.org\/dev\/generated\/statsmodels.stats.anova.anova_lm.html\" target=\"_blank\" rel=\"noopener\">anova_lm() \u51fd\u6570<\/a>\u6267\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> statsmodels.api <span style=\"color: #107d3f;\">as<\/span> sm\n<span style=\"color: #107d3f;\">from<\/span> statsmodels.formula.api <span style=\"color: #107d3f;\">import<\/span> ols\n\n<span style=\"color: #008080;\">#perform two-way ANOVA<\/span>\nmodel = ols('height ~ C(water) + C(sun) + C(water):C(sun)', data=df).fit()\nsm.stats.anova_lm(model, typ=2)\n\n\t           sum_sq df F PR(&gt;F)\nC(water) 8.533333 1.0 16.0000 0.000527\nC(sun) 24.866667 2.0 23.3125 0.000002\nC(water):C(sun) 2.466667 2.0 2.3125 0.120667\nResidual 12.800000 24.0 NaN NaN\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u7b2c 3 \u6b65\uff1a\u89e3\u91ca\u7ed3\u679c\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u8868\u4e2d\u6bcf\u4e2a\u56e0\u7d20\u7684\u4ee5\u4e0b p \u503c\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u6c34\uff1a<\/strong> p \u503c = 0.000527<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u592a\u9633\uff1a<\/strong> p \u503c = 0.0000002<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u6c34*\u9633\u5149\uff1a<\/strong> p \u503c = 0.120667<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u6c34\u548c\u9633\u5149\u7684 p \u503c\u5747\u5c0f\u4e8e 0.05\uff0c\u8fd9\u610f\u5473\u7740\u8fd9\u4e24\u4e2a\u56e0\u7d20\u5bf9\u690d\u7269\u9ad8\u5ea6\u90fd\u6709\u7edf\u8ba1\u4e0a\u663e\u7740\u7684\u5f71\u54cd\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u4ea4\u4e92\u6548\u5e94\u7684 p \u503c (0.120667) \u4e0d\u5c0f\u4e8e 0.05\uff0c\u8fd9\u544a\u8bc9\u6211\u4eec\uff0c\u66b4\u9732\u5728\u9633\u5149\u4e0b\u548c\u6d47\u6c34\u9891\u7387\u4e4b\u95f4\u4e0d\u5b58\u5728\u663e\u7740\u7684\u4ea4\u4e92\u6548\u5e94\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6ce8\u610f\uff1a<\/strong>\u867d\u7136\u65b9\u5dee\u5206\u6790\u7ed3\u679c\u544a\u8bc9\u6211\u4eec\uff0c\u6d47\u6c34\u9891\u7387\u548c\u9633\u5149\u7167\u5c04\u5bf9\u690d\u7269\u9ad8\u5ea6\u6709\u7edf\u8ba1\u5b66\u4e0a\u7684\u663e\u7740\u5f71\u54cd\uff0c\u4f46\u6211\u4eec\u9700\u8981\u8fdb\u884c<a href=\"https:\/\/statorials.org\/cn\/\u4e8b\u540e\u65b9\u5dee\u5206\u6790\u68c0\u9a8c\/\" target=\"_blank\" rel=\"noopener\">\u4e8b\u540e\u6d4b\u8bd5<\/a>\uff0c\u4ee5\u786e\u5b9a\u4e0d\u540c\u6c34\u5e73\u7684\u6c34\u548c\u9633\u5149\u5982\u4f55\u5f71\u54cd\u690d\u7269\u9ad8\u5ea6\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u4efb\u52a1\uff1a<\/span><\/p>\n<p><a href=\"https:\/\/statorials.org\/cn\/python-\u5355\u5411\u65b9\u5dee\u5206\u6790\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u5355\u5411\u65b9\u5dee\u5206\u6790<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u4e09\u8def\u65b9\u5dee\u5206\u6790python\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u4e09\u5411\u65b9\u5dee\u5206\u6790<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u53cc\u5411\u65b9\u5dee\u5206\u6790\u7528\u4e8e\u786e\u5b9a\u5df2\u5206\u6210\u4e24\u4e2a\u56e0\u7d20\u7684\u4e09\u4e2a\u6216\u66f4\u591a\u72ec\u7acb\u7ec4\u7684\u5e73\u5747\u503c\u4e4b\u95f4\u662f\u5426\u5b58\u5728\u7edf\u8ba1\u663e\u7740\u5dee\u5f02\u3002 \u53cc\u5411\u65b9\u5dee\u5206\u6790\u7684\u76ee\u7684\u662f\u786e [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-855","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790 - Statorials<\/title>\n<meta name=\"description\" content=\"\u5173\u4e8e\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u53cc\u5411\u65b9\u5dee\u5206\u6790\u7684\u7b80\u5355\u8bf4\u660e\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/cn\/python-\u53cc\u5411\u65b9\u5dee\u5206\u6790\/\" \/>\n<meta property=\"og:locale\" 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