{"id":3921,"date":"2023-07-14T18:26:54","date_gmt":"2023-07-14T18:26:54","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e4%b8%89%e6%ac%a1%e5%9b%9e%e5%bd%92-python\/"},"modified":"2023-07-14T18:26:54","modified_gmt":"2023-07-14T18:26:54","slug":"%e4%b8%89%e6%ac%a1%e5%9b%9e%e5%bd%92-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e4%b8%89%e6%ac%a1%e5%9b%9e%e5%bd%92-python\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u6267\u884c\u4e09\u6b21\u56de\u5f52"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u4e09\u6b21\u56de\u5f52<\/strong>\u662f\u4e00\u79cd\u56de\u5f52\u7c7b\u578b\uff0c\u5f53\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u662f\u975e\u7ebf\u6027\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5b83\u6765\u91cf\u5316\u9884\u6d4b\u53d8\u91cf\u548c\u54cd\u5e94\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u4e09\u6b21\u56de\u5f52\u3002<\/span><\/p>\n<h2><strong><span style=\"color: #000000;\">\u793a\u4f8b\uff1aPython \u4e2d\u7684\u4e09\u6b21\u56de\u5f52<\/span><\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u4e24\u4e2a\u53d8\u91cf\uff08x \u548c y\uff09\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">x<\/span> ': [6, 9, 12, 16, 22, 28, 33, 40, 47, 51, 55, 60],\n                   ' <span style=\"color: #ff0000;\">y<\/span> ': [14, 28, 50, 64, 67, 57, 55, 57, 68, 74, 88, 110]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n     xy\n0 6 14\n1 9 28\n2 12 50\n3 16 64\n4 22 67\n5 28 57\n6 33 55\n7 40 57\n8 47 68\n9 51 74\n10 55 88\n11 60 110\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5982\u679c\u6211\u4eec\u5bf9\u8fd9\u4e9b\u6570\u636e\u5236\u4f5c\u4e00\u4e2a\u7b80\u5355\u7684\u6563\u70b9\u56fe\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u662f\u975e\u7ebf\u6027\u7684\uff1a<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import <span style=\"color: #000000;\">matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span><\/span> as <span style=\"color: #000000;\">plt<\/span>\n\n<span style=\"color: #000000;\"><span style=\"color: #008080;\">#create scatterplot\n<\/span>plt. <span style=\"color: #3366ff;\">scatter<\/span> (df. <span style=\"color: #3366ff;\">x<\/span> , df. <span style=\"color: #3366ff;\">y<\/span> )<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-31513 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/cubique1.jpg\" alt=\"\" width=\"463\" height=\"341\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u968f\u7740 x \u503c\u7684\u589e\u52a0\uff0cy \u589e\u52a0\u5230\u67d0\u4e2a\u70b9\uff0c\u7136\u540e\u51cf\u5c11\uff0c\u7136\u540e\u518d\u6b21\u589e\u52a0\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u56fe\u4e2d\u5177\u6709\u4e24\u6761\u201c\u66f2\u7ebf\u201d\u7684\u6a21\u5f0f\u8868\u660e\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u5b58\u5728\u7acb\u65b9\u5173\u7cfb\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u610f\u5473\u7740\u4e09\u6b21\u56de\u5f52\u6a21\u578b\u662f\u91cf\u5316\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u5173\u7cfb\u7684\u826f\u597d\u5019\u9009\u6a21\u578b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8981\u6267\u884c\u4e09\u6b21\u56de\u5f52\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528<a href=\"https:\/\/numpy.org\/doc\/stable\/reference\/generated\/numpy.polyfit.html\" target=\"_blank\" rel=\"noopener noreferrer\">numpy.polyfit()<\/a><span style=\"color: #000000;\">\u51fd\u6570<\/span>\u62df\u5408 3 \u6b21\u591a\u9879\u5f0f\u56de\u5f52\u6a21\u578b\uff1a<\/span> <\/p>\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\n<span style=\"color: #008080;\">#fit cubic regression model\n<\/span>model = np. <span style=\"color: #3366ff;\">poly1d<\/span> (np. <span style=\"color: #3366ff;\">polyfit<\/span> (df. <span style=\"color: #3366ff;\">x<\/span> , df. <span style=\"color: #3366ff;\">y<\/span> , <span style=\"color: #000000;\">3))<\/span>\n\n<span style=\"color: #008080;\">#add fitted cubic regression line to scatterplot\n<\/span>polyline = np. <span style=\"color: #3366ff;\">linspace<\/span> (1, 60, 50)\nplt. <span style=\"color: #3366ff;\">scatter<\/span> (df. <span style=\"color: #3366ff;\">x<\/span> , df. <span style=\"color: #3366ff;\">y<\/span> )\nplt. <span style=\"color: #3366ff;\">plot<\/span> (polyline, model(polyline))\n\n<span style=\"color: #008080;\">#add axis labels\n<\/span>plt. <span style=\"color: #3366ff;\">xlabel<\/span> (' <span style=\"color: #ff0000;\">x<\/span> ')\nplt. <span style=\"color: #3366ff;\">ylabel<\/span> (' <span style=\"color: #ff0000;\">y<\/span> ')\n\n<span style=\"color: #008080;\">#displayplot\n<\/span>plt. <span style=\"color: #3366ff;\">show<\/span> ()<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-31514\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/cubique2.jpg\" alt=\"Python \u4e2d\u7684\u4e09\u6b21\u56de\u5f52\" width=\"547\" height=\"404\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u6253\u5370\u6a21\u578b\u7cfb\u6570\u5f97\u5230\u62df\u5408\u7684\u4e09\u6b21\u56de\u5f52\u65b9\u7a0b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">print<\/span> (model)\n\n          3 2\n0.003302x - 0.3214x + 9.832x - 32.01\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u62df\u5408\u7684\u4e09\u6b21\u56de\u5f52\u65b9\u7a0b\u4e3a\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>y = 0.003302(x) <sup>3<\/sup> \u2013 0.3214(x) <sup>2<\/sup> + 9.832x \u2013 30.01<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u8fd9\u4e2a\u65b9\u7a0b\u6839\u636e x \u7684\u503c\u8ba1\u7b97 y \u7684\u671f\u671b\u503c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u5982\u679c x \u4e3a 30\uff0c\u5219 y \u7684\u9884\u671f\u503c\u4e3a 64.844\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\">y = 0.003302(30) <sup>3<\/sup> \u2013 0.3214(30) <sup>2<\/sup> + 9.832(30) \u2013 30.01 = 64.844<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u8fd8\u53ef\u4ee5\u7f16\u5199\u4e00\u4e2a\u7b80\u77ed\u7684\u51fd\u6570\u6765\u83b7\u53d6\u6a21\u578b\u7684 R \u5e73\u65b9\uff0c\u5b83\u662f\u54cd\u5e94\u53d8\u91cf\u4e2d\u53ef\u4ee5\u7531\u9884\u6d4b\u53d8\u91cf\u89e3\u91ca\u7684\u65b9\u5dee\u7684\u6bd4\u4f8b\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define function to calculate r-squared<\/span>\n<span style=\"color: #008000;\">def<\/span> polyfit(x, y, degree):\n    results = {}\n    coeffs = np. <span style=\"color: #3366ff;\">polyfit<\/span> (x, y, degree)\n    p = np. <span style=\"color: #3366ff;\">poly1d<\/span> (coeffs)\n    <span style=\"color: #008080;\">#calculate r-squared<\/span>\n    yhat = p(x)\n    ybar = np. <span style=\"color: #3366ff;\">sum<\/span> (y)\/len(y)\n    ssreg = np. <span style=\"color: #3366ff;\">sum<\/span> ((yhat-ybar) <span style=\"color: #800080;\">**<\/span> 2)\n    sstot = np. <span style=\"color: #3366ff;\">sum<\/span> ((y - ybar) <span style=\"color: #800080;\">**<\/span> 2)\n    results[' <span style=\"color: #ff0000;\">r_squared<\/span> '] = ssreg \/ sstot\n\n    <span style=\"color: #008000;\">return<\/span> results\n\n<span style=\"color: #008080;\">#find r-squared of polynomial model with degree = 3\n<\/span>polyfit(df. <span style=\"color: #3366ff;\">x<\/span> , df. <span style=\"color: #3366ff;\">y<\/span> , 3)\n\n{'r_squared': 0.9632469890057967}\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5728\u6b64\u793a\u4f8b\u4e2d\uff0c\u6a21\u578b\u7684 R \u65b9\u4e3a<strong>0.9632<\/strong> \u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u610f\u5473\u7740\u54cd\u5e94\u53d8\u91cf\u4e2d 96.32% \u7684\u53d8\u5f02\u53ef\u4ee5\u7531\u9884\u6d4b\u53d8\u91cf\u6765\u89e3\u91ca\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7531\u4e8e\u8fd9\u4e2a\u503c\u5982\u6b64\u4e4b\u9ad8\uff0c\u5b83\u544a\u8bc9\u6211\u4eec\u4e09\u6b21\u56de\u5f52\u6a21\u578b\u5f88\u597d\u5730\u91cf\u5316\u4e86\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u76f8\u5173\uff1a<\/strong><a href=\"https:\/\/statorials.org\/cn\/\u826f\u597d\u7684-r-\u5e73\u65b9\u503c\/\" target=\"_blank\" rel=\"noopener\">\u4ec0\u4e48\u662f\u597d\u7684 R \u5e73\u65b9\u503c\uff1f<\/a><\/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-\u4e2d\u7684\u7b80\u5355\u7ebf\u6027\u56de\u5f52\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u7b80\u5355\u7ebf\u6027\u56de\u5f52<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u4e8c\u6b21\u56de\u5f52-python\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u4e8c\u6b21\u56de\u5f52<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u591a\u9879\u5f0f\u56de\u5f52-python\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u591a\u9879\u5f0f\u56de\u5f52<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e09\u6b21\u56de\u5f52\u662f\u4e00\u79cd\u56de\u5f52\u7c7b\u578b\uff0c\u5f53\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u662f\u975e\u7ebf\u6027\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u5b83\u6765\u91cf\u5316\u9884\u6d4b\u53d8\u91cf\u548c\u54cd\u5e94\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002 \u672c\u6559\u7a0b [&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-3921","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\u4e09\u6b21\u56de\u5f52 - Statory<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u4e00\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c\u4e09\u6b21\u56de\u5f52\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\/\u4e09\u6b21\u56de\u5f52-python\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" 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