{"id":2573,"date":"2023-07-21T16:29:32","date_gmt":"2023-07-21T16:29:32","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e7%86%8a%e7%8c%ab%e5%90%88%e5%b9%b6\/"},"modified":"2023-07-21T16:29:32","modified_gmt":"2023-07-21T16:29:32","slug":"%e7%86%8a%e7%8c%ab%e5%90%88%e5%b9%b6","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e7%86%8a%e7%8c%ab%e5%90%88%e5%b9%b6\/","title":{"rendered":"Pandas\uff1a\u5982\u4f55\u5c06\u591a\u5217\u4e2d\u7684\u503c\u5408\u5e76\u4e3a\u4e00\u5217"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u5c06 pandas DataFrame \u7684\u591a\u4e2a\u5217\u4e2d\u7684\u503c\u5206\u7ec4\u4e3a\u5355\u4e2a\u5217\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd5\u4e00\uff1a\u6309\u9ed8\u8ba4\u5217\u987a\u5e8f\u5408\u5e76\u503c<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">coalesce<\/span> '] = df. <span style=\"color: #3366ff;\">bfill<\/span> (axis= <span style=\"color: #008000;\">1<\/span> ). <span style=\"color: #3366ff;\">iloc<\/span> [:, 0]\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u65b9\u6cd52\uff1a\u4f7f\u7528\u7279\u5b9a\u5217\u987a\u5e8f\u5408\u5e76\u503c<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df[' <span style=\"color: #ff0000;\">coalesce<\/span> '] = df[[' <span style=\"color: #ff0000;\">col3<\/span> ', ' <span style=\"color: #ff0000;\">col1<\/span> ', ' <span style=\"color: #ff0000;\">col2<\/span> ']]. <span style=\"color: #3366ff;\">bfill<\/span> (axis= <span style=\"color: #008000;\">1<\/span> ). <span style=\"color: #3366ff;\">iloc<\/span> [:, 0]<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u4ee5\u4e0b pandas DataFrame \u7684\u6bcf\u79cd\u65b9\u6cd5\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><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\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">points<\/span> ': [np.nan, np.nan, 19, np.nan, 14],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [np.nan, 7, 7, 9, np.nan],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [3, 4, np.nan, np.nan, 6]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   points assists rebounds\n0 NaN NaN 3.0\n1 NaN 7.0 4.0\n2 19.0 7.0 NaN\n3 NaN 9.0 NaN\n4 14.0 NaN 6.0\n<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u65b9\u6cd5\u4e00\uff1a\u6309\u9ed8\u8ba4\u5217\u987a\u5e8f\u5408\u5e76\u503c<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u5c06\u5f97\u5206\u3001\u52a9\u653b\u548c\u7bee\u677f\u5217\u4e2d\u7684\u503c\u5408\u5e76\u5230\u5355\u4e2a\u5217\u4e2d\uff0c\u5e76\u4f7f\u7528\u4e09\u5217\u4e2d\u7684\u7b2c\u4e00\u4e2a\u975e\u96f6\u503c\u4f5c\u4e3a\u5408\u5e76\u503c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#create new column that contains first non-null value from three existing columns \n<\/span>df[' <span style=\"color: #ff0000;\">coalesce<\/span> '] = df. <span style=\"color: #3366ff;\">bfill<\/span> (axis= <span style=\"color: #008000;\">1<\/span> ). <span style=\"color: #3366ff;\">iloc<\/span> [:, 0]\n\n<\/span><span style=\"color: #008080;\">#view updated DataFrame\n<\/span><span style=\"color: #000000;\"><span style=\"color: #008000;\">print<\/span> (df)\n\n   points assists rebounds coalesce\n0 NaN NaN 3.0 3.0\n1 NaN 7.0 4.0 7.0\n2 19.0 7.0 NaN 19.0\n3 NaN 9.0 NaN 9.0\n4 14.0 NaN 6.0 14.0\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u9009\u62e9<strong>\u5408\u5e76<\/strong>\u5217\u4e2d\u7684\u503c\u7684\u65b9\u5f0f\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u7b2c\u4e00\u884c\uff1a\u7b2c\u4e00\u4e2a\u975e\u96f6\u503c\u662f<strong>3.0<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c\u4e8c\u884c\uff1a\u7b2c\u4e00\u4e2a\u975e\u96f6\u503c\u662f<strong>7.0<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c\u4e09\u884c\uff1a\u7b2c\u4e00\u4e2a\u975e\u96f6\u503c\u662f<strong>19.0<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c\u56db\u884c\uff1a\u7b2c\u4e00\u4e2a\u975e\u96f6\u503c\u662f<strong>9.0<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7b2c\u4e94\u884c\uff1a\u7b2c\u4e00\u4e2a\u975e\u96f6\u503c\u662f<strong>14.0<\/strong> \u3002<\/span><\/li>\n<\/ul>\n<h3><strong>\u65b9\u6cd52\uff1a<span style=\"color: #000000;\">\u4f7f\u7528\u7279\u5b9a\u5217\u987a\u5e8f\u5408\u5e76\u503c<\/span><\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u4e0b\u9762\u7684\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u901a\u8fc7\u6309\u4ee5\u4e0b\u987a\u5e8f\u5206\u6790\u5217\u6765\u5408\u5e76\u4e09\u5217\u4e2d\u7684\u503c\uff1a\u52a9\u653b\u3001\u7bee\u677f\u3001\u5f97\u5206\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#coalesce values in specific column order\n<\/span>df[' <span style=\"color: #ff0000;\">coalesce<\/span> '] = df[[' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ', ' <span style=\"color: #ff0000;\">points<\/span> ']]. <span style=\"color: #3366ff;\">bfill<\/span> (axis= <span style=\"color: #008000;\">1<\/span> ). <span style=\"color: #3366ff;\">iloc<\/span> [:, 0]\n\n<span style=\"color: #008080;\">#view updated DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n   points assists rebounds coalesce\n0 NaN NaN 3.0 3.0\n1 NaN 7.0 4.0 7.0\n2 19.0 7.0 NaN 7.0\n3 NaN 9.0 NaN 9.0\n4 14.0 NaN 6.0 6.0\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u7528\u4e8e\u51b3\u5b9a\u5c06\u54ea\u4e2a\u503c\u653e\u7f6e\u5728<strong>\u5408\u5e76<\/strong>\u5217\u4e2d\u7684\u903b\u8f91\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5982\u679c<strong>\u8f85\u52a9<\/strong>\u5217\u4e2d\u7684\u503c\u4e0d\u4e3a\u96f6\uff0c\u5219\u4f7f\u7528\u8be5\u503c\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5426\u5219\uff0c\u5982\u679c<strong>\u9000\u56de<\/strong>\u5217\u4e2d\u7684\u503c\u4e0d\u4e3a\u96f6\uff0c\u5219\u4f7f\u7528\u8be5\u503c\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5426\u5219\uff0c\u5982\u679c<strong>\u70b9<\/strong>\u5217\u4e2d\u7684\u503c\u4e0d\u4e3a\u96f6\uff0c\u5219\u4f7f\u7528\u8be5\u503c\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u6ce8\u610f<\/strong>\uff1a\u60a8\u53ef\u4ee5<a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.bfill.html\" target=\"_blank\" rel=\"noopener\">\u5728\u6b64\u5904<\/a>\u627e\u5230<strong>bfill()<\/strong>\u51fd\u6570\u7684\u5b8c\u6574\u6587\u6863\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u64cd\u4f5c\uff1a<\/span><\/p>\n<p><a href=\"https:\/\/statorials.org\/cn\/pandas-\u5408\u5e76\u4e24\u5217\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u5408\u5e76\u4e24\u5217<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/pandas-\u7279\u5b9a\u603b\u548c\u5217\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5bf9 Pandas \u4e2d\u7684\u7279\u5b9a\u5217\u6c42\u548c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/pandas-\u6309\u591a\u5217\u6392\u5e8f\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u6309\u591a\u5217\u6392\u5e8f<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u5c06 pandas DataFrame \u7684\u591a\u4e2a\u5217\u4e2d\u7684\u503c\u5206\u7ec4\u4e3a\u5355\u4e2a\u5217\uff1a \u65b9\u6cd5\u4e00\uff1a\u6309\u9ed8\u8ba4\u5217\u987a\u5e8f\u5408\u5e76 [&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-2573","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\uff1a\u5982\u4f55\u5c06\u591a\u5217\u4e2d\u7684\u503c\u5408\u5e76\u4e3a\u4e00\u5217 - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5c06 pandas DataFrame \u7684\u591a\u4e2a\u5217\u4e2d\u7684\u503c\u5408\u5e76\u5230\u5355\u4e2a\u5217\u4e2d\uff0c\u5305\u62ec\u793a\u4f8b\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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