{"id":2028,"date":"2023-07-24T00:23:35","date_gmt":"2023-07-24T00:23:35","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%bf%d0%be%d1%88%d1%83%d0%ba-%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8\/"},"modified":"2023-07-24T00:23:35","modified_gmt":"2023-07-24T00:23:35","slug":"%d0%bf%d0%be%d1%88%d1%83%d0%ba-%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%bf%d0%be%d1%88%d1%83%d0%ba-%d0%bf%d0%b0%d0%bd%d0%b4%d0%b8\/","title":{"rendered":"\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 vlookup \u0432 pandas"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0432\u0438\u043a\u043e\u043d\u0430\u043d\u043d\u044f VLOOKUP (\u0441\u0445\u043e\u0436\u043e\u0433\u043e \u043d\u0430 Excel) \u0443 pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>p.d. <span style=\"color: #3366ff;\">merge<\/span> (df1,\n         df2,\n         on = ' <span style=\"color: #ff0000;\">column_name<\/span> ',\n         how = ' <span style=\"color: #ff0000;\">left<\/span> ')\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u0435\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 1: \u0421\u0442\u0432\u043e\u0440\u0456\u0442\u044c \u0434\u0432\u0430 DataFrames<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0421\u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0434\u0430\u0432\u0430\u0439\u0442\u0435 \u0456\u043c\u043f\u043e\u0440\u0442\u0443\u0454\u043c\u043e pandas \u0456 \u0441\u0442\u0432\u043e\u0440\u0438\u043c\u043e \u0434\u0432\u0430 pandas DataFrames:<\/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;\">#define first DataFrame\n<\/span>df1 = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">player<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F'],\n                    ' <span style=\"color: #ff0000;\">team<\/span> ': ['Mavs', 'Mavs', 'Mavs', 'Mavs', 'Nets', 'Nets']})\n\n<span style=\"color: #008080;\">#define second DataFrame\n<\/span>df2 = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">player<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F'],\n                    ' <span style=\"color: #ff0000;\">points<\/span> ': [22, 29, 34, 20, 15, 19]})\n\n<span style=\"color: #008080;\">#view df1\n<\/span><span style=\"color: #008000;\">print<\/span> (df1)\n\n  player team\n0 A Mavs\n1 B Mavs\n2C Mavs\n3 D Mavs\n4 E Nets\n5 F Nets\n\n<span style=\"color: #008080;\">#view df2\n<\/span><span style=\"color: #008000;\">print<\/span> (df2)\n\n  player points\n0 to 22\n1 B 29\n2 C 34\n3 D 20\n4 E 15\n5 F 19\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041a\u0440\u043e\u043a 2. \u0417\u0430\u043f\u0443\u0441\u0442\u0456\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0456\u044e VLOOKUP<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0424\u0443\u043d\u043a\u0446\u0456\u044f <strong>VLOOKUP<\/strong> \u0432 Excel \u0434\u043e\u0437\u0432\u043e\u043b\u044f\u0454 \u0437\u043d\u0430\u0439\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 \u0442\u0430\u0431\u043b\u0438\u0446\u0456, \u0437\u0456\u0441\u0442\u0430\u0432\u0438\u0432\u0448\u0438 \u0439\u043e\u0433\u043e \u0432 \u0441\u0442\u043e\u0432\u043f\u0446\u0456.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0437\u043d\u0430\u0439\u0442\u0438 \u043a\u043e\u043c\u0430\u043d\u0434\u0443 \u0433\u0440\u0430\u0432\u0446\u044f \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e <strong>pd.merge()<\/strong> , \u0449\u043e\u0431 \u0437\u0456\u0441\u0442\u0430\u0432\u0438\u0442\u0438 \u0456\u043c\u0435\u043d\u0430 \u0433\u0440\u0430\u0432\u0446\u0456\u0432 \u043c\u0456\u0436 \u0434\u0432\u043e\u043c\u0430 \u0442\u0430\u0431\u043b\u0438\u0446\u044f\u043c\u0438 \u0442\u0430 \u043f\u043e\u0432\u0435\u0440\u043d\u0443\u0442\u0438 \u043a\u043e\u043c\u0430\u043d\u0434\u0443 \u0433\u0440\u0430\u0432\u0446\u044f:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#perform VLOOKUP<\/span>\njoined_df = pd. <span style=\"color: #3366ff;\">merge<\/span> (df1,\n                     df2,\n                     we = ' <span style=\"color: #ff0000;\">player<\/span> ',\n                     how = ' <span style=\"color: #ff0000;\">left<\/span> ')\n\n<span style=\"color: #008080;\">#view results\n<\/span>joined_df\n\n\tplayer team points\n0 A Mavs 22\n1 B Mavs 29\n2 C Mavs 34\n3D Mavs 20\n4 E Nets 15\n5 F Nets 19<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0443\u044e\u0447\u0438\u0439 DataFrame pandas \u043c\u0456\u0441\u0442\u0438\u0442\u044c \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u044e \u043f\u0440\u043e \u0433\u0440\u0430\u0432\u0446\u044f, \u0439\u043e\u0433\u043e \u043a\u043e\u043c\u0430\u043d\u0434\u0443 \u0442\u0430 \u043d\u0430\u0431\u0440\u0430\u043d\u0456 \u043e\u0447\u043a\u0438.<\/span><\/p>\n<p> <span style=\"joined_df = pd.merge(df1, df2, on ='player', how ='left') joined_dfcolor: #000000;\">\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0437\u043d\u0430\u0439\u0442\u0438 \u043f\u043e\u0432\u043d\u0443 \u043e\u043d\u043b\u0430\u0439\u043d-\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0456\u044e \u0444\u0443\u043d\u043a\u0446\u0456\u0457 pandas <strong>merge()<\/strong> <a href=\"https:\/\/pandas.pydata.org\/docs\/reference\/api\/pandas.DataFrame.merge.html\" target=\"_blank\" rel=\"noopener\">\u0442\u0443\u0442<\/a> .<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0445 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0430\u0445 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0456\u043d\u0448\u0456 \u0442\u0438\u043f\u043e\u0432\u0456 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 \u0432 Python:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0437\u0432\u0435\u0434\u0435\u043d\u0456 \u0442\u0430\u0431\u043b\u0438\u0446\u0456 \u043d\u0430 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u043a\u043e\u0440\u0435\u043b\u044f\u0446\u0456\u044f-\u0432-python\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0440\u043e\u0437\u0440\u0430\u0445\u0443\u0432\u0430\u0442\u0438 \u043a\u043e\u0440\u0435\u043b\u044f\u0446\u0456\u044e \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u043f\u0440\u043e\u0446\u0435\u043d\u0442\u0438\u043b\u0456-\u0432-python\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 \u043f\u0440\u043e\u0446\u0435\u043d\u0442\u0438\u043b\u0438 \u0432 Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0412\u0438 \u043c\u043e\u0436\u0435\u0442\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0432\u0438\u043a\u043e\u043d\u0430\u043d\u043d\u044f VLOOKUP (\u0441\u0445\u043e\u0436\u043e\u0433\u043e \u043d\u0430 Excel) \u0443 pandas: p.d. merge (df1, df2, on = &#8216; column_name &#8216;, how = &#8216; left &#8216;) \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u0435\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456. \u041a\u0440\u043e\u043a 1: \u0421\u0442\u0432\u043e\u0440\u0456\u0442\u044c \u0434\u0432\u0430 DataFrames \u0421\u043f\u043e\u0447\u0430\u0442\u043a\u0443 \u0434\u0430\u0432\u0430\u0439\u0442\u0435 \u0456\u043c\u043f\u043e\u0440\u0442\u0443\u0454\u043c\u043e pandas \u0456 \u0441\u0442\u0432\u043e\u0440\u0438\u043c\u043e \u0434\u0432\u0430 pandas DataFrames: import pandas as [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 VLOOKUP \u0443 Pandas - Statorials<\/title>\n<meta name=\"description\" content=\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e VLOOKUP (\u0441\u0445\u043e\u0436\u0443 \u043d\u0430 Excel) \u0443 pandas \u0456\u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, 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