{"id":2866,"date":"2023-07-20T08:32:04","date_gmt":"2023-07-20T08:32:04","guid":{"rendered":"https:\/\/statorials.org\/cn\/pandas-%e7%94%a8-nan-%e6%9b%bf%e6%8d%a2%e7%a9%ba%e5%ad%97%e7%ac%a6%e4%b8%b2\/"},"modified":"2023-07-20T08:32:04","modified_gmt":"2023-07-20T08:32:04","slug":"pandas-%e7%94%a8-nan-%e6%9b%bf%e6%8d%a2%e7%a9%ba%e5%ad%97%e7%ac%a6%e4%b8%b2","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/pandas-%e7%94%a8-nan-%e6%9b%bf%e6%8d%a2%e7%a9%ba%e5%ad%97%e7%ac%a6%e4%b8%b2\/","title":{"rendered":"Pandas\uff1a\u5982\u4f55\u7528 nan \u66ff\u6362\u7a7a\u5b57\u7b26\u4e32"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u5c06 pandas \u4e2d\u7684\u7a7a\u5b57\u7b26\u4e32\u66ff\u6362\u4e3a NaN \u503c\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>df = df. <span style=\"color: #3366ff;\">replace<\/span> ( <span style=\"color: #ff0000;\">r'^\\s*$'<\/span> , np. <span style=\"color: #3366ff;\">nan<\/span> , regex= <span style=\"color: #008000;\">True<\/span> )<\/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<p><span style=\"color: #000000;\"><strong>\u76f8\u5173\uff1a<\/strong> <a href=\"https:\/\/statorials.org\/cn\/pandas-\u7528\u4e01\u5b57\u88e4\u4ee3\u66ff-nan\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 Pandas \u4e2d\u7528\u5b57\u7b26\u4e32\u66ff\u6362 NaN \u503c<\/a><\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u7528 NaN \u66ff\u6362\u7a7a\u5b57\u7b26\u4e32<\/strong><\/span><\/h3>\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;\"> <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', ' ', 'D', 'E', ' ', 'G', 'H'],\n                   ' <span style=\"color: #ff0000;\">position<\/span> ': [' ', 'G', 'G', 'F', 'F', ' ', 'C', 'C'],\n                   ' <span style=\"color: #ff0000;\">points<\/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>df\n\n\tteam position points rebounds\n0 to 5 11\n1 B G 7 8\n2 G 7 10\n3 D F 9 6\n4 E F 12 6\n5 9 5\n6 G C 9 9\n7 H C 4 12<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c<strong>\u56e2\u961f<\/strong>\u548c<strong>\u4f4d\u7f6e<\/strong>\u5217\u4e2d\u6709\u51e0\u4e2a\u7a7a\u5b57\u7b26\u4e32\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u5c06\u8fd9\u4e9b\u7a7a\u5b57\u7b26\u4e32\u66ff\u6362\u4e3a NaN \u503c\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> numpy <span style=\"color: #008000;\">as<\/span> np<\/span>\n\n<span style=\"color: #000000;\"><span style=\"color: #008080;\">#replace empty values with NaN\n<\/span>df = df. <span style=\"color: #3366ff;\">replace<\/span> ( <span style=\"color: #ff0000;\">r'^\\s*$'<\/span> , np. <span style=\"color: #3366ff;\">nan<\/span> , regex= <span style=\"color: #008000;\">True<\/span> )\n<\/span>\n#view updated DataFrame\n<span style=\"color: #000000;\">df\n<\/span>\n<span style=\"color: #000000;\">team position<\/span> <span style=\"color: #000000;\">points rebounds\n0 A NaN<\/span> <span style=\"color: #000000;\">5 11\n1 B G<\/span> <span style=\"color: #000000;\">7 8\n2 NaN G<\/span> <span style=\"color: #000000;\">7 10\n3 D F<\/span> <span style=\"color: #000000;\">9 6\n4 E F<\/span> <span style=\"color: #000000;\">12 6\n5 NaN NaN<\/span> <span style=\"color: #000000;\">9 5\n6 G C<\/span> <span style=\"color: #000000;\">9 9\n7 H C<\/span> <span style=\"color: #000000;\">4 127<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u6bcf\u4e2a\u7a7a\u5b57\u7b26\u4e32\u90fd\u5df2\u66ff\u6362\u4e3a NaN\u3002<\/span><\/span><\/p>\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.replace.html\" target=\"_blank\" rel=\"noopener\">\u5728\u6b64\u5904<\/a>\u627e\u5230 pandas \u4e2d<strong>\u66ff\u6362<\/strong>\u529f\u80fd\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\u4efb\u52a1\uff1a<\/span><\/p>\n<p><a href=\"https:\/\/statorials.org\/cn\/pandas-\u4f30\u7b97\u7f3a\u5931\u503c\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u4f30\u7b97 pandas \u4e2d\u7684\u7f3a\u5931\u503c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/pandas-\u8ba1\u7b97\u7f3a\u5931\u503c\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u7edf\u8ba1pandas\u4e2d\u7684\u7f3a\u5931\u503c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u718a\u732b-fillna-\u4e0e\u5e73\u5747\u503c\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728 pandas \u4e2d\u7528\u5747\u503c\u586b\u5145 NaN \u503c<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u60a8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u5c06 pandas \u4e2d\u7684\u7a7a\u5b57\u7b26\u4e32\u66ff\u6362\u4e3a NaN \u503c\uff1a df = df. replace ( r [&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-2866","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\u7528 NaN \u66ff\u6362\u7a7a\u5b57\u7b26\u4e32 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u901a\u8fc7\u51e0\u4e2a\u793a\u4f8b\u89e3\u91ca\u4e86\u5982\u4f55\u5728 pandas \u4e2d\u7528 NaN \u66ff\u6362\u7a7a\u5b57\u7b26\u4e32\u3002\" \/>\n<meta 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