{"id":2872,"date":"2023-07-20T07:55:51","date_gmt":"2023-07-20T07:55:51","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%82%a8%e6%ad%a3%e5%9c%a8%e5%b0%9d%e8%af%95%e5%90%88%e5%b9%b6-object-%e5%92%8c-int64-%e5%88%97\/"},"modified":"2023-07-20T07:55:51","modified_gmt":"2023-07-20T07:55:51","slug":"%e6%82%a8%e6%ad%a3%e5%9c%a8%e5%b0%9d%e8%af%95%e5%90%88%e5%b9%b6-object-%e5%92%8c-int64-%e5%88%97","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%82%a8%e6%ad%a3%e5%9c%a8%e5%b0%9d%e8%af%95%e5%90%88%e5%b9%b6-object-%e5%92%8c-int64-%e5%88%97\/","title":{"rendered":"\u5982\u4f55\u4fee\u590d\uff1a\u60a8\u6b63\u5728\u5c1d\u8bd5\u5408\u5e76 object \u548c int64 \u5217"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u4f7f\u7528 pandas \u65f6\u53ef\u80fd\u9047\u5230\u7684\u9519\u8bef\u662f\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #ff0000;\">ValueError<\/span> : You are trying to merge on int64 and object columns.\n            If you wish to proceed you should use pd.concat\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5f53\u60a8\u5c1d\u8bd5\u5408\u5e76\u4e24\u4e2a pandas DataFrame \u4f46\u8981\u5408\u5e76\u7684\u5217\u662f\u4e00\u4e2a DataFrame \u4e2d\u7684\u5bf9\u8c61\u548c\u53e6\u4e00\u4e2a DataFrame \u4e2d\u7684\u6574\u6570\u65f6\uff0c\u4f1a\u53d1\u751f\u6b64\u9519\u8bef\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u7ea0\u6b63\u6b64\u9519\u8bef\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5982\u4f55\u91cd\u73b0\u9519\u8bef<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u521b\u5efa\u4ee5\u4e0b\u4e24\u4e2a panda 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<\/span>\ndf1 = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">year<\/span> ': [2015, 2016, 2017, 2018, 2019, 2020, 2021],\n                    ' <span style=\"color: #ff0000;\">sales<\/span> ': [500, 534, 564, 671, 700, 840, 810]})\n\ndf2 = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">year<\/span> ': ['2015', '2016', '2017', '2018', '2019', '2020', '2021'],\n                    ' <span style=\"color: #ff0000;\">refunds<\/span> ': [31, 36, 40, 40, 43, 70, 62]})\n\n<span style=\"color: #008080;\">#view DataFrames\n<\/span><span style=\"color: #008000;\">print<\/span> (df1)\n\n   year sales\n0 2015 500\n1 2016 534\n2 2017 564\n3 2018 671\n4 2019 700\n5,2020 840\n6 2021 810\n\n<span style=\"color: #008000;\">print<\/span> (df2)\n\n   year refunds\n0 2015 31\n1 2016 36\n2 2017 40\n3 2018 40\n4 2019 43\n5 2020 70\n6 2021 62<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u73b0\u5728\u5047\u8bbe\u6211\u4eec\u5c1d\u8bd5\u5408\u5e76\u4e24\u4e2a 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: #008080;\">#attempt to merge two DataFrames\n<\/span>big_df = df1. <span style=\"color: #3366ff;\">merge<\/span> (df2, on=' <span style=\"color: #ff0000;\">year<\/span> ', how=' <span style=\"color: #ff0000;\">left<\/span> ')\n\n<span style=\"color: #ff0000;\">ValueError<\/span> : You are trying to merge on int64 and object columns.\n            If you wish to proceed you should use pd.concat\n<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u6536\u5230\u4e00\u4e2a<strong>ValueError<\/strong> \uff0c\u56e0\u4e3a\u7b2c\u4e00\u4e2a DataFrame \u4e2d\u7684<strong>\u5e74\u4efd<\/strong>\u53d8\u91cf\u662f\u6574\u6570\uff0c\u4f46\u7b2c\u4e8c\u4e2a DataFrame \u4e2d\u7684<strong>\u5e74\u4efd<\/strong>\u53d8\u91cf\u662f\u4e00\u4e2a\u5bf9\u8c61\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5982\u4f55\u4fee\u590d\u9519\u8bef<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4fee\u590d\u6b64\u9519\u8bef\u7684\u6700\u7b80\u5355\u65b9\u6cd5\u662f\u5c06\u7b2c\u4e8c\u4e2a DataFrame \u7684<strong>\u5e74\u4efd<\/strong>\u53d8\u91cf\u8f6c\u6362\u4e3a\u6574\u6570\uff0c\u7136\u540e\u8fdb\u884c\u5408\u5e76\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u8bed\u6cd5\u663e\u793a\u4e86\u5982\u4f55\u6267\u884c\u6b64\u64cd\u4f5c\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;\">#convert year variable in df2 to integer\n<\/span>df2[' <span style=\"color: #ff0000;\">year<\/span> ']=df2[' <span style=\"color: #ff0000;\">year<\/span> ']. <span style=\"color: #3366ff;\">astype<\/span> (int)\n\n<span style=\"color: #008080;\">#merge two DataFrames\n<\/span>big_df = df1. <span style=\"color: #3366ff;\">merge<\/span> (df2, on=' <span style=\"color: #ff0000;\">year<\/span> ', how=' <span style=\"color: #ff0000;\">left<\/span> ')\n\n<span style=\"color: #008080;\">#view merged DataFrame\n<\/span>big_df\n\n\tyear sales refunds\n0 2015 500 31\n1 2016 534 36\n2 2017 564 40\n3 2018 671 40\n4 2019 700 43\n5 2020 840 70\n6 2021 810 62<\/span><\/span><\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u6211\u4eec\u6ca1\u6709\u6536\u5230\u4efb\u4f55<strong>ValueError<\/strong> \uff0c\u5e76\u4e14\u6211\u4eec\u6210\u529f\u5730\u5c06\u4e24\u4e2a DataFrame \u5408\u5e76\u4e3a\u4e00\u4e2a\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\u4fee\u590d Python \u4e2d\u7684\u5176\u4ed6\u5e38\u89c1\u9519\u8bef\uff1a<\/span><\/p>\n<p><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><br \/><a href=\"https:\/\/statorials.org\/cn\/numpy-ndarray-\u5bf9\u8c61\u6ca1\u6709\u5c5e\u6027\u8ffd\u52a0\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u4fee\u590d\uff1a\u5bf9\u8c61\u201cnumpy.ndarray\u201d\u6ca1\u6709\u201cappend\u201d\u5c5e\u6027<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u5982\u679c\u4f7f\u7528\u60a8\u9700\u8981\u4f20\u9012\u7d22\u5f15\u7684\u6240\u6709\u6807\u91cf\u503c\uff0c\u5219\u4f1a\u51fa\u73b0\u503c\u9519\u8bef\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u4fee\u590d\uff1a\u5982\u679c\u4f7f\u7528\u6240\u6709\u6807\u91cf\u503c\uff0c\u5219\u9700\u8981\u4f20\u9012\u7d22\u5f15<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u4f7f\u7528 pandas \u65f6\u53ef\u80fd\u9047\u5230\u7684\u9519\u8bef\u662f\uff1a ValueError : You are trying to mer [&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-2872","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\uff1a\u60a8\u6b63\u5728\u5c1d\u8bd5\u5408\u5e76 object \u548c int64 \u5217 - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u4fee\u590d pandas \u4e2d\u7684\u4ee5\u4e0b\u9519\u8bef\uff1a\u201c\u60a8\u6b63\u5728\u5c1d\u8bd5\u5408\u5e76\u5bf9\u8c61\u548c int64 \u5217\u201d\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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