{"id":3801,"date":"2023-07-15T11:39:13","date_gmt":"2023-07-15T11:39:13","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e7%ae%80%e5%8e%86%e4%ba%94%e4%bd%8d%e6%95%b0%e5%ad%97\/"},"modified":"2023-07-15T11:39:13","modified_gmt":"2023-07-15T11:39:13","slug":"pandas-%e7%ae%80%e5%8e%86%e4%ba%94%e4%bd%8d%e6%95%b0%e5%ad%97","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e7%ae%80%e5%8e%86%e4%ba%94%e4%bd%8d%e6%95%b0%e5%ad%97\/","title":{"rendered":"\u5982\u4f55\u8ba1\u7b97 pandas \u4e2d\u4e94\u4e2a\u6570\u5b57\u7684\u603b\u548c"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u4e94\u4f4d\u6570\u6c47\u603b<\/strong>\u662f\u4e00\u79cd\u4f7f\u7528\u4ee5\u4e0b\u4e94\u4e2a\u503c\u6c47\u603b\u4e00\u7ec4\u6570\u636e\u7684\u65b9\u6cd5\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u4f4e\u9650\u5ea6<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c\u4e00\u4e2a\u56db\u5206\u4f4d\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\">\u4e2d\u4f4d\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c\u4e09\u4e2a\u56db\u5206\u4f4d\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u5927\u503c<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4e94\u6570\u6c47\u603b\u5f88\u6709\u7528\uff0c\u56e0\u4e3a\u5b83\u63d0\u4f9b\u4e86\u6570\u636e\u5206\u5e03\u7684\u7b80\u660e\u6c47\u603b\uff0c\u5982\u4e0b\u6240\u793a\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5b83\u4f7f\u7528\u4e2d\u4f4d\u6570\u544a\u8bc9\u6211\u4eec <a href=\"https:\/\/statorials.org\/cn\/\u8861\u91cf\u96c6\u4e2d\u8d8b\u52bf\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4e2d\u503c<\/a>\u5728\u54ea\u91cc\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5b83\u4f7f\u7528\u7b2c\u4e00\u548c\u7b2c\u4e09\u56db\u5206\u4f4d\u6570\u544a\u8bc9\u6211\u4eec\u6570\u636e\u7684\u5206\u5e03\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5b83\u4f7f\u7528\u6700\u5c0f\u503c\u548c\u6700\u5927\u503c\u544a\u8bc9\u6211\u4eec\u6570\u636e\u7684\u8303\u56f4\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u8ba1\u7b97 pandas DataFrame \u4e2d\u53d8\u91cf\u7684\u4e94\u6570\u6458\u8981\u7684\u6700\u7b80\u5355\u65b9\u6cd5\u662f\u4f7f\u7528<strong>describe()<\/strong>\u51fd\u6570\uff0c\u5982\u4e0b\u6240\u793a\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df. <span style=\"color: #3366ff;\">describe<\/span> (). <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">min<\/span> ', '25 <span style=\"color: #ff0000;\">%<\/span> ', '50 <span style=\"color: #ff0000;\">%<\/span> ', <span style=\"color: #ff0000;\">'75%<\/span> ', ' <span style=\"color: #ff0000;\">max<\/span> ']]\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6b64\u8bed\u6cd5\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u8ba1\u7b97 Pandas DataFrame \u4e2d\u4e94\u4e2a\u6570\u5b57\u7684\u6c47\u603b<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b pandas DataFrame\uff0c\u5176\u4e2d\u5305\u542b\u6709\u5173\u5404\u79cd\u7bee\u7403\u8fd0\u52a8\u5458\u7684\u4fe1\u606f\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n  team points assists rebounds\n0 A 18 5 11\n1 B 22 7 8\n2 C 19 7 10\n3 D 14 9 6\n4 E 14 12 6\n5 F 11 9 5\n6 G 20 9 9\n7:28 4 12<\/strong><\/span><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u6765\u8ba1\u7b97 DataFrame \u4e2d\u6bcf\u4e2a\u6570\u503c\u53d8\u91cf\u7684\u4e94\u6570\u6458\u8981\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate five number summary for each numeric variable<\/span>\ndf. <span style=\"color: #3366ff;\">describe<\/span> (). <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">min<\/span> ', '25 <span style=\"color: #ff0000;\">%<\/span> ', '50 <span style=\"color: #ff0000;\">%<\/span> ', <span style=\"color: #ff0000;\">'75%<\/span> ', ' <span style=\"color: #ff0000;\">max<\/span> ']]\n\n      points assists rebounds\nmin 11.0 4.0 5.00\n25% 14.0 6.5 6.00\n50% 18.5 8.0 8.50\n75% 20.5 9.0 10.25\nmax 28.0 12.0 12.00\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u5982\u4f55\u89e3\u91ca<strong>point<\/strong>\u53d8\u91cf\u7684\u7ed3\u679c\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6700\u5c0f\u503c\u4e3a<strong>11<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c 25 \u4e2a\u767e\u5206\u4f4d\u6570\u7684\u503c\u4e3a<strong>14<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c 50 \u4e2a\u767e\u5206\u4f4d\u6570\u503c\u4e3a<strong>18.5<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c 75 \u4e2a\u767e\u5206\u4f4d\u6570\u503c\u4e3a<strong>20.5<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u5927\u503c\u4e3a<strong>28<\/strong> \u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u7528\u540c\u6837\u7684\u65b9\u5f0f\u89e3\u91ca<strong>help<\/strong>\u548c<strong>relief<\/strong>\u53d8\u91cf\u7684\u503c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u53ea\u60f3\u8ba1\u7b97DataFrame\u4e2d\u7279\u5b9a\u53d8\u91cf\u7684\u4e94\u6570\u6c47\u603b\uff0c\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#calculate five number summary for the points variable<\/span>\ndf[' <span style=\"color: #ff0000;\">points<\/span> ']. <span style=\"color: #3366ff;\">describe<\/span> (). <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">min<\/span> ', '25 <span style=\"color: #ff0000;\">%<\/span> ', '50 <span style=\"color: #ff0000;\">%<\/span> ', <span style=\"color: #ff0000;\">'75%<\/span> ', ' <span style=\"color: #ff0000;\">max<\/span> ']]\n\nmin 11.0\n25% 14.0\n50% 18.5\n75% 20.5\nmax 28.0\nName: points, dtype: float64\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8f93\u51fa\u73b0\u5728\u4ec5\u663e\u793a<strong>\u70b9<\/strong>\u53d8\u91cf\u7684\u4e94\u4f4d\u6458\u8981\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\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u7684 panda \u4efb\u52a1\uff1a<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/cn\/\u718a\u732b\u9891\u7387\u8ba1\u6570\/\" target=\"_blank\" rel=\"noopener\">Pandas\uff1a\u5982\u4f55\u83b7\u53d6\u5217\u4e2d\u503c\u7684\u9891\u7387\u8ba1\u6570<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u6bcf\u7ec4\u4e2d\u578b\u5927\u718a\u732b\/\" target=\"_blank\" rel=\"noopener\">Pandas\uff1a\u5982\u4f55\u8ba1\u7b97\u6bcf\u7ec4\u7684\u5e73\u5747\u503c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u6bcf\u7ec4\u718a\u732b\u6570\u91cf\u4e2d\u4f4d\u6570\/\" target=\"_blank\" rel=\"noopener\">Pandas\uff1a\u5982\u4f55\u6309\u7ec4\u8ba1\u7b97\u4e2d\u4f4d\u6570<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4e94\u4f4d\u6570\u6c47\u603b\u662f\u4e00\u79cd\u4f7f\u7528\u4ee5\u4e0b\u4e94\u4e2a\u503c\u6c47\u603b\u4e00\u7ec4\u6570\u636e\u7684\u65b9\u6cd5\uff1a \u6700\u4f4e\u9650\u5ea6 \u7b2c\u4e00\u4e2a\u56db\u5206\u4f4d\u6570 \u4e2d\u4f4d\u6570 \u7b2c\u4e09\u4e2a\u56db\u5206\u4f4d\u6570 \u6700\u5927\u503c  [&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-3801","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\u8ba1\u7b97 pandas \u4e2d\u4e94\u4e2a\u6570\u5b57\u7684\u603b\u548c - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u4e00\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u8ba1\u7b97\u4e94\u4e2a\u6570\u5b57\u7684\u6c47\u603b\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\/pandas-\u7b80\u5386\u4e94\u4f4d\u6570\u5b57\/\" 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