{"id":1980,"date":"2023-07-24T05:32:17","date_gmt":"2023-07-24T05:32:17","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%b8%a6%e5%a4%8d%e5%88%b6%e8%ad%a6%e5%91%8a%e7%9a%84-pandas-%e8%ae%be%e7%bd%ae\/"},"modified":"2023-07-24T05:32:17","modified_gmt":"2023-07-24T05:32:17","slug":"%e5%b8%a6%e5%a4%8d%e5%88%b6%e8%ad%a6%e5%91%8a%e7%9a%84-pandas-%e8%ae%be%e7%bd%ae","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%b8%a6%e5%a4%8d%e5%88%b6%e8%ad%a6%e5%91%8a%e7%9a%84-pandas-%e8%ae%be%e7%bd%ae\/","title":{"rendered":"\u5982\u4f55\u5728 pandas \u4e2d\u4fee\u590d\uff1asettingwithcopywarning"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u4f7f\u7528 pandas \u65f6\u53ef\u80fd\u9047\u5230\u7684\u4e00\u4e2a\u8b66\u544a\u662f\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5f53 pandas \u9047\u5230\u4e00\u79cd\u79f0\u4e3a\u94fe\u5206\u914d\u7684\u60c5\u51b5\u65f6\uff0c\u5c31\u4f1a\u51fa\u73b0\u6b64\u8b66\u544a &#8211; \u4e00\u6b65\u4e2d\u94fe\u63a5\u548c\u5206\u914d\u7684\u7ec4\u5408\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u9700\u8981\u6ce8\u610f\u7684\u662f\uff0c\u8fd9\u53ea\u662f\u4e00\u4e2a<em>\u8b66\u544a<\/em>\u800c\u4e0d\u662f\u9519\u8bef\u3002\u60a8\u7684\u4ee3\u7801\u5c06\u7ee7\u7eed\u8fd0\u884c\uff0c\u4f46\u7ed3\u679c\u53ef\u80fd\u5e76\u4e0d\u603b\u662f\u60a8\u6240\u671f\u671b\u7684\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6291\u5236\u6b64\u8b66\u544a\u7684\u6700\u7b80\u5355\u65b9\u6cd5\u662f\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>p.d. <span style=\"color: #3366ff;\">options<\/span> . <span style=\"color: #3366ff;\">fashion<\/span> . <span style=\"color: #3366ff;\">chained_assignment<\/span> = <span style=\"color: #008000;\">None<\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u54cd\u5e94\u6b64\u8b66\u544a\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5982\u4f55\u91cd\u73b0\u8b66\u544a<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u521b\u5efa\u4ee5\u4e0b pandas DataFrame\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 style=\"color: #000000;\">df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">A<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">B<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">C<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})<\/span>\n\n#view DataFrame\n<span style=\"color: #000000;\">df<\/span>\n<\/span>\n\tA B C\n0 25 5 11\n1 12 7 8\n2 15 7 10\n3 14 9 6\n4 19 12 6\n5 23 9 5\n6 25 9 9\n7 29 4 12<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u73b0\u5728\u5047\u8bbe\u6211\u4eec\u521b\u5efa\u4e00\u4e2a\u65b0\u7684 DataFrame\uff0c\u5176\u4e2d\u4ec5\u5305\u542b\u539f\u59cb DataFrame \u4e2d\u7684\u201cA\u201d\u5217\uff0c\u5e76\u5c06\u201cA\u201d\u5217\u4e2d\u7684\u6bcf\u4e2a\u503c\u9664\u4ee5 2\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#define new DataFrame\n<\/span>df2 = df[[' <span style=\"color: #ff0000;\">A<\/span> ']]\n\n<\/span>#divide all values in column 'A' by 2\n<span style=\"color: #000000;\">df2[' <span style=\"color: #ff0000;\">A<\/span> '] = df[' <span style=\"color: #ff0000;\">A<\/span> '] \/ 2<\/span>\n\n<span style=\"color: #000000;\">\/srv\/conda\/envs\/notebook\/lib\/python3.7\/site-packages\/ipykernel_launcher.py:2:\nSettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u6536\u5230<strong>SettingWithCopyWarning<\/strong>\u6d88\u606f\u662f\u56e0\u4e3a\u6211\u4eec\u6b63\u5728\u539f\u59cbDataFrame\u7684\u201c\u5207\u7247\u201d\u4e0a\u4e3a\u201cA\u201d\u5217\u8bbe\u7f6e\u65b0\u503c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f46\u662f\uff0c\u5982\u679c\u6211\u4eec\u67e5\u770b\u521b\u5efa\u7684\u65b0 DataFrame\uff0c\u6211\u4eec\u5c06\u770b\u5230\u6bcf\u4e2a\u503c\u5b9e\u9645\u4e0a\u5df2\u6210\u529f\u9664\u4ee5 2\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#view new DataFrame\n<\/span>df2\n\n     HAS\n0 12.5\n1 6.0\n2 7.5\n3 7.0\n4 9.5\n5 11.5\n6 12.5\n7 14.5\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5c3d\u7ba1\u6211\u4eec\u6536\u5230\u4e86\u8b66\u544a\u4fe1\u606f\uff0c\u4f46\u718a\u732b\u4ecd\u7136\u505a\u4e86\u6211\u4eec\u8ba4\u4e3a\u5b83\u4eec\u4f1a\u505a\u7684\u4e8b\u60c5\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5982\u4f55\u907f\u514d\u8b66\u544a<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4e3a\u4e86\u907f\u514d\u6b64\u8b66\u544a\uff0c\u5efa\u8bae\u4f7f\u7528<strong>.loc[row indexer, col indexer]<\/strong>\u8bed\u6cd5\uff0c\u5982\u4e0b\u6240\u793a\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#define new DataFrame\n<\/span>df2 = df. <span style=\"color: #3366ff;\">loc<\/span> [:,[' <span style=\"color: #ff0000;\">A<\/span> ']]\n\n<span style=\"color: #008080;\">#divide each value in column 'A' by 2\n<\/span>df2[' <span style=\"color: #ff0000;\">A<\/span> '] = df[' <span style=\"color: #ff0000;\">A<\/span> '] \/ 2\n\n<span style=\"color: #008080;\">#view result\n<\/span>df2\n\n     HAS\n0 12.5\n1 6.0\n2 7.5\n3 7.0\n4 9.5\n5 11.5\n6 12.5\n7 14.5\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u65b0\u7684DataFrame\u5305\u542b\u539f\u59cbDataFrame\u4e2d\u201cA\u201d\u5217\u7684\u6240\u6709\u503c\uff0c\u9664\u4ee5\u4e8c\uff0c\u5e76\u4e14\u4e0d\u4f1a\u51fa\u73b0\u8b66\u544a\u6d88\u606f\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u6211\u4eec\u60f3\u963b\u6b62\u663e\u793a\u8b66\u544a\u6d88\u606f\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e0b\u9762\u7684\u4ee3\u7801\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#prevent SettingWithCopyWarning message from appearing\n<\/span>p.d. <span style=\"color: #3366ff;\">options<\/span> . <span style=\"color: #3366ff;\">fashion<\/span> . <span style=\"color: #3366ff;\">chained_assignment<\/span> = <span style=\"color: #008000;\">None<\/span>\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6709\u5173\u4e3a\u4ec0\u4e48\u5e94\u907f\u514d\u94fe\u5206\u914d\u7684\u8be6\u7ec6\u8bf4\u660e\uff0c\u8bf7\u53c2\u9605<a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/version\/0.22\/indexing.html\" target=\"_blank\" rel=\"noopener\">\u5728\u7ebf pandas \u6587\u6863<\/a>\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\/\u6ca1\u6709\u540d\u4e3a-pandas-\u7684\u6a21\u5757\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u4fee\u590d\uff1a\u6ca1\u6709\u540d\u4e3a pandas \u7684\u6a21\u5757<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u6ca1\u6709\u540d\u4e3a-numpy-\u7684\u6a21\u5757\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u4fee\u590d\uff1a\u6ca1\u6709\u540d\u4e3a numpy \u7684\u6a21\u5757<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u5217\u91cd\u53e0\u4f46\u672a\u6307\u5b9a\u540e\u7f00\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u4fee\u590d\uff1a\u5217\u91cd\u53e0\u4f46\u672a\u6307\u5b9a\u540e\u7f00<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4f7f\u7528 pandas \u65f6\u53ef\u80fd\u9047\u5230\u7684\u4e00\u4e2a\u8b66\u544a\u662f\uff1a SettingWithCopyWarning: A value  [&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-1980","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\u4fee\u590d 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