{"id":1170,"date":"2023-07-27T10:21:17","date_gmt":"2023-07-27T10:21:17","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e4%b8%ad%e7%9a%84%e8%81%9a%e7%b1%bb%e6%8a%bd%e6%a0%b7\/"},"modified":"2023-07-27T10:21:17","modified_gmt":"2023-07-27T10:21:17","slug":"pandas-%e4%b8%ad%e7%9a%84%e8%81%9a%e7%b1%bb%e6%8a%bd%e6%a0%b7","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e4%b8%ad%e7%9a%84%e8%81%9a%e7%b1%bb%e6%8a%bd%e6%a0%b7\/","title":{"rendered":"Pandas \u7684\u805a\u7c7b\u62bd\u6837\uff1a\u4e3e\u4f8b"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u7814\u7a76\u4eba\u5458\u7ecf\u5e38\u4ece\u4eba\u7fa4\u4e2d\u62bd\u53d6<a href=\"https:\/\/statorials.org\/cn\/\u62bd\u6837\u65b9\u6cd5\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u6837\u672c<\/a>\uff0c\u5e76\u5229\u7528\u6837\u672c\u4e2d\u7684\u6570\u636e\u5f97\u51fa\u5173\u4e8e\u6574\u4e2a\u4eba\u7fa4\u7684\u7ed3\u8bba\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5e38\u7528\u7684\u62bd\u6837\u65b9\u6cd5\u662f<strong>\u6574\u7fa4\u62bd\u6837<\/strong>\uff0c\u5176\u4e2d\u5c06\u603b\u4f53\u5206\u4e3a\u591a\u4e2a\u7c07\uff0c\u5e76\u9009\u62e9<em>\u67d0\u4e9b<\/em>\u7c07\u7684\u6240\u6709\u6210\u5458\u5305\u542b\u5728\u6837\u672c\u4e2d\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u5bf9 pandas DataFrame \u6267\u884c\u805a\u7c7b\u91c7\u6837\u3002<\/span><\/p>\n<h2><strong>\u793a\u4f8b\uff1aPandas \u4e2d\u7684\u805a\u7c7b\u91c7\u6837<\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u4e00\u5bb6\u63d0\u4f9b\u57ce\u5e02\u65c5\u6e38\u7684\u516c\u53f8\u60f3\u8981\u5bf9\u5176\u5ba2\u6237\u8fdb\u884c\u8c03\u67e5\u3002\u4ed6\u4eec\u6bcf\u5929\u63d0\u4f9b 10 \u4e2a\u65c5\u884c\u56e2\uff0c\u968f\u673a\u9009\u62e9 4 \u4e2a\u65c5\u884c\u56e2\uff0c\u5e76\u8981\u6c42\u6bcf\u4f4d\u987e\u5ba2\u6309\u7167 1 \u5230 10 \u7684\u7b49\u7ea7\u5bf9\u4ed6\u4eec\u7684\u4f53\u9a8c\u8fdb\u884c\u8bc4\u5206\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u5982\u4f55\u521b\u5efa\u8981\u4f7f\u7528\u7684 pandas DataFrame\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n<span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<\/span>\n#make this example reproducible<\/span>\nn.p. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">seeds<\/span> (0)\n\n<span style=\"color: #008080;\">#createDataFrame<\/span>\ndf = pd.DataFrame({'tour': np. <span style=\"color: #3366ff;\">repeat<\/span> (np. <span style=\"color: #3366ff;\">arange<\/span> (1,11), 20),\n                   'experience': np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">normal<\/span> (loc=7, scale=1, size=200)})\n\n<span style=\"color: #008080;\">#view first six rows of DataFrame<\/span>\ndf. <span style=\"color: #3366ff;\">head<\/span> ()\n\n  tour experience\n1 1 6.373546\n2 1 7.183643\n3 1 6.164371\n4 1 8.595281\n5 1 7.329508\n6 1 6.179532\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u901a\u8fc7\u968f\u673a\u9009\u62e9\u56db\u6b21\u8bbf\u95ee\u5e76\u5c06\u8fd9\u4e9b\u8bbf\u95ee\u4e2d\u7684\u6bcf\u4e2a\u6210\u5458\u90fd\u5305\u542b\u5728\u6837\u672c\u4e2d\u6765\u83b7\u53d6\u5ba2\u6237\u6837\u672c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#randomly choose 4 tour groups out of the 10<\/span>\nclusters = np. <span style=\"color: #3366ff;\">random<\/span> . <span style=\"color: #3366ff;\">choice<\/span> (np. <span style=\"color: #3366ff;\">arange<\/span> (1,11), size=4, replace= <span style=\"color: #008000;\">False<\/span> )\n\n<span style=\"color: #008080;\">#define sample as all members who belong to one of the 4 tour groups<\/span>\ncluster_sample = df[df[' <span style=\"color: #008000;\">tour<\/span> ']. <span style=\"color: #3366ff;\">isin<\/span> (clusters)]\n\n<span style=\"color: #008080;\">#view first six rows of sample\n<\/span>cluster_sample. <span style=\"color: #3366ff;\">head<\/span> ()\n\ntour experience\n40 3 5.951447\n41 3 5.579982\n42 3 5.293730\n43 3 8.950775\n44 3 6.490348 \n\n<span style=\"color: #008080;\">#find how many observations came from each tour group\n<\/span>cluster_sample[' <span style=\"color: #008000;\">tour<\/span> ']. <span style=\"color: #3366ff;\">value_counts<\/span> ()\n\n10 20\n6 20\n5 20\n3 20\nName: tour, dtype: int64<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u6211\u4eec\u53ef\u4ee5\u770b\u51fa\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u6837\u672c\u4e2d\u5305\u62ec\u6765\u81ea 10 \u53f7\u65c5\u884c\u56e2\u7684 20 \u540d\u987e\u5ba2\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6837\u672c\u4e2d\u5305\u62ec\u6765\u81ea 6 \u53f7\u65c5\u6e38\u56e2\u7684 20 \u540d\u987e\u5ba2\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6837\u672c\u4e2d\u5305\u62ec\u6765\u81ea 5 \u53f7\u65c5\u6e38\u56e2\u7684 20 \u540d\u987e\u5ba2\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6837\u672c\u4e2d\u5305\u62ec\u6765\u81ea 3 \u53f7\u65c5\u6e38\u56e2\u7684 20 \u540d\u987e\u5ba2\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u56e0\u6b64\uff0c\u8be5\u6837\u672c\u7531\u6765\u81ea 4 \u4e2a\u4e0d\u540c\u65c5\u6e38\u56e2\u7684 80 \u540d\u987e\u5ba2\u7ec4\u6210\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/cn\/\u62bd\u6837\u65b9\u6cd5\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u4e86\u89e3\u4e0d\u540c\u7c7b\u578b\u7684\u62bd\u6837\u65b9\u6cd5<\/a><br \/> <a href=\"https:\/\/statorials.org\/cn\/\u718a\u732b\u5206\u5c42\u62bd\u6837\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5927\u718a\u732b\u7684\u5206\u5c42\u62bd\u6837<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u5bf9\u5927\u718a\u732b\u8fdb\u884c\u7cfb\u7edf\u62bd\u6837\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5bf9\u5927\u718a\u732b\u8fdb\u884c\u7cfb\u7edf\u91c7\u6837<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7814\u7a76\u4eba\u5458\u7ecf\u5e38\u4ece\u4eba\u7fa4\u4e2d\u62bd\u53d6\u6837\u672c\uff0c\u5e76\u5229\u7528\u6837\u672c\u4e2d\u7684\u6570\u636e\u5f97\u51fa\u5173\u4e8e\u6574\u4e2a\u4eba\u7fa4\u7684\u7ed3\u8bba\u3002 \u5e38\u7528\u7684\u62bd\u6837\u65b9\u6cd5\u662f\u6574\u7fa4\u62bd\u6837\uff0c\u5176\u4e2d\u5c06\u603b\u4f53 [&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-1170","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>Pandas \u7684\u805a\u7c7b\u62bd\u6837\uff1a\u4e3e\u4f8b<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u6267\u884c\u805a\u7c7b\u91c7\u6837\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-\u4e2d\u7684\u805a\u7c7b\u62bd\u6837\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta 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