{"id":2924,"date":"2023-07-20T01:42:49","date_gmt":"2023-07-20T01:42:49","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d0%be%d1%81%d1%82%d0%b0%d0%bb%d0%be%d1%81%d1%8c-%d0%bf%d1%80%d0%b8%d1%81%d0%be%d0%b5%d0%b4%d0%b8%d0%bd%d0%b8%d1%82%d1%8c%d1%81%d1%8f-%d0%ba-%d0%bf%d0%b0%d0%bd%d0%b4%d0%b0%d0%bc\/"},"modified":"2023-07-20T01:42:49","modified_gmt":"2023-07-20T01:42:49","slug":"%d0%be%d1%81%d1%82%d0%b0%d0%bb%d0%be%d1%81%d1%8c-%d0%bf%d1%80%d0%b8%d1%81%d0%be%d0%b5%d0%b4%d0%b8%d0%bd%d0%b8%d1%82%d1%8c%d1%81%d1%8f-%d0%ba-%d0%bf%d0%b0%d0%bd%d0%b4%d0%b0%d0%bc","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d0%be%d1%81%d1%82%d0%b0%d0%bb%d0%be%d1%81%d1%8c-%d0%bf%d1%80%d0%b8%d1%81%d0%be%d0%b5%d0%b4%d0%b8%d0%bd%d0%b8%d1%82%d1%8c%d1%81%d1%8f-%d0%ba-%d0%bf%d0%b0%d0%bd%d0%b4%d0%b0%d0%bc\/","title":{"rendered":"\u041a\u0430\u043a \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u043b\u0435\u0432\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 pandas (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c)"},"content":{"rendered":"

<\/p>\n

\n

\u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043b\u0435\u0432\u043e\u0433\u043e \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u044f \u0432 pandas:<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd\n<\/span>\ndf1. merge<\/span> (df2, on=' column_name<\/span> ', how=' left<\/span> ')\n<\/strong><\/pre>\n
 \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u043e\u0442 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435.<\/span><\/p>\n
 \u041f\u0440\u0438\u043c\u0435\u0440: \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043b\u0435\u0432\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas<\/strong><\/span><\/h2>\n
 \u0414\u043e\u043f\u0443\u0441\u0442\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0435 \u0434\u0432\u0430 \u043a\u0430\u0434\u0440\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u043f\u0430\u043d\u0434\u044b, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0442 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0431\u0430\u0441\u043a\u0435\u0442\u0431\u043e\u043b\u044c\u043d\u044b\u0445 \u043a\u043e\u043c\u0430\u043d\u0434\u0430\u0445:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#createDataFrame\ndf1 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H'],\n                    ' points<\/span> ': [18, 22, 19, 14, 14, 11, 20, 28]})\n\ndf2 = pd. DataFrame<\/span> ({' team<\/span> ': ['A', 'B', 'C', 'D', 'G', 'H'],\n                    ' assists<\/span> ': [4, 9, 14, 13, 10, 8]})\n\n#view DataFrames\n<\/span>print<\/span> (df1)\n\n  team points\n0 to 18\n1 B 22\n2 C 19\n3 D 14\n4 E 14\n5 F 11\n6 G 20\n7:28 a.m.\n\nprint<\/span> (df2)\n\n  team assists\n0 to 4\n1 B 9\n2 C 14\n3 D 13\n4G 10\n5:8 a.m.<\/span><\/span><\/strong><\/pre>\n
 \u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u0434\u043b\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043b\u0435\u0432\u043e\u0433\u043e \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u044f, \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u044f \u0432\u0441\u0435 \u0441\u0442\u0440\u043e\u043a\u0438 \u0438\u0437 \u043f\u0435\u0440\u0432\u043e\u0433\u043e DataFrame \u0438 \u0434\u043e\u0431\u0430\u0432\u043b\u044f\u044f \u0432\u0441\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u044b, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0442 \u0441\u0442\u043e\u043b\u0431\u0446\u0443 \u043a\u043e\u043c\u0430\u043d\u0434\u044b<\/strong> \u0432\u043e \u0432\u0442\u043e\u0440\u043e\u043c DataFrame:<\/span><\/p>\n
 #perform left join\ndf1. merge<\/span> (df2, on=' team<\/span> ', how=' left<\/span> ')\n\n        team points assists\n0 to 18 4.0\n1 B 22 9.0\n2 C 19 14.0\n3 D 14 13.0\n4 E 14 NaN\n5 F 11 NaN\n6G 20 10.0\n7:28 a.m. 8.0\n<\/span><\/span><\/strong><\/pre>\n
 \u041a\u0430\u0436\u0434\u0430\u044f \u043a\u043e\u043c\u0430\u043d\u0434\u0430 \u0432 \u043b\u0435\u0432\u043e\u043c DataFrame ( df1<\/strong> ) \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u0435\u0442\u0441\u044f \u0432 \u043e\u0431\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u043d\u043e\u043c DataFrame, \u0438 \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u044e\u0442\u0441\u044f \u0442\u043e\u043b\u044c\u043a\u043e \u0441\u0442\u0440\u043e\u043a\u0438 \u0432 \u043f\u0440\u0430\u0432\u043e\u043c DataFrame ( df2<\/strong> ), \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0449\u0438\u0435 \u0438\u043c\u0435\u043d\u0438 \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0432 \u043b\u0435\u0432\u043e\u043c DataFrame.<\/span><\/p>\n
 \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0434\u0432\u0435 \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0432 df2<\/strong> (\u043a\u043e\u043c\u0430\u043d\u0434\u044b E \u0438 F), \u043d\u0430\u0437\u0432\u0430\u043d\u0438\u044f \u043a\u043e\u0442\u043e\u0440\u044b\u0445 \u043d\u0435 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u044e\u0442 \u043d\u0430\u0437\u0432\u0430\u043d\u0438\u044e \u043a\u043e\u043c\u0430\u043d\u0434\u044b \u0432 df1<\/strong> , \u043f\u0440\u043e\u0441\u0442\u043e \u0432\u043e\u0437\u0432\u0440\u0430\u0449\u0430\u044e\u0442 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 NaN<\/strong> \u0432 \u0441\u0442\u043e\u043b\u0431\u0446\u0435 \u043f\u0435\u0440\u0435\u0434\u0430\u0447 \u043e\u0431\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u043d\u043e\u0433\u043e DataFrame.<\/span><\/p>\n
 \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0432\u044b \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c pd.merge()<\/strong> \u0441\u043e \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441\u043e\u043c, \u0447\u0442\u043e\u0431\u044b \u0432\u0435\u0440\u043d\u0443\u0442\u044c \u0442\u043e\u0442 \u0436\u0435 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442:<\/span><\/p>\n
 #perform left join\np.d. merge<\/span> (df1, df2, on=' team<\/span> ', how=' left<\/span> ')\n\n\n        team points assists\n0 to 18 4.0\n1 B 22 9.0\n2 C 19 14.0\n3 D 14 13.0\n4 E 14 NaN\n5 F 11 NaN\n6G 20 10.0\n7:28 a.m. 8.0<\/span><\/span><\/strong><\/pre>\n
 \u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u044d\u0442\u043e\u0442 \u043e\u0431\u044a\u0435\u0434\u0438\u043d\u0435\u043d\u043d\u044b\u0439 DataFrame \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443\u0435\u0442 \u043a\u0430\u0434\u0440\u0443 \u0438\u0437 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0435\u0433\u043e \u043f\u0440\u0438\u043c\u0435\u0440\u0430.<\/span><\/p>\n
 \u041f\u0440\u0438\u043c\u0435\u0447\u0430\u043d\u0438\u0435<\/strong> . \u041f\u043e\u043b\u043d\u0443\u044e \u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0438\u044e \u043f\u043e \u0444\u0443\u043d\u043a\u0446\u0438\u0438 \u0441\u043b\u0438\u044f\u043d\u0438\u044f<\/strong> \u043c\u043e\u0436\u043d\u043e \u043d\u0430\u0439\u0442\u0438 \u0437\u0434\u0435\u0441\u044c<\/a> .<\/span><\/p>\n
 \u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0441\u0443\u0440\u0441\u044b<\/strong><\/span><\/h2>\n
 \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0445 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0430\u0445 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u0442\u044c \u0434\u0440\u0443\u0433\u0438\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u043d\u044b\u0435 \u043e\u043f\u0435\u0440\u0430\u0446\u0438\u0438 \u0432 pandas:<\/span><\/p>\n
 \u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u0430\u043d\u0442\u0438-\u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas<\/a>
 \u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u0432\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u0435\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas<\/a>
 \u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043f\u0435\u0440\u0435\u043a\u0440\u0435\u0441\u0442\u043d\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0412\u044b \u043c\u043e\u0436\u0435\u0442\u0435 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u044f \u043b\u0435\u0432\u043e\u0433\u043e \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u044f \u0432 pandas: import pandas as pd df1. merge (df2, on=’ column_name ‘, how=’ left ‘) \u0412 \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0435\u043c \u043f\u0440\u0438\u043c\u0435\u0440\u0435 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u043a\u0430\u043a \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u044d\u0442\u043e\u0442 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435. \u041f\u0440\u0438\u043c\u0435\u0440: \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043b\u0435\u0432\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas \u0414\u043e\u043f\u0443\u0441\u0442\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0435 \u0434\u0432\u0430 \u043a\u0430\u0434\u0440\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u043f\u0430\u043d\u0434\u044b, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0441\u043e\u0434\u0435\u0440\u0436\u0430\u0442 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e […]<\/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-2924","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u041a\u0430\u043a \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u043b\u0435\u0432\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c) \u2013 \u0421\u0442\u0430\u0442\u043e\u0440\u0438\u0430\u043b\u044b<\/title>\n<meta name=\"description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043b\u0435\u0432\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 pandas, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ru\/\u043e\u0441\u0442\u0430\u043b\u043e\u0441\u044c-\u043f\u0440\u0438\u0441\u043e\u0435\u0434\u0438\u043d\u0438\u0442\u044c\u0441\u044f-\u043a-\u043f\u0430\u043d\u0434\u0430\u043c\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u041a\u0430\u043a \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u043b\u0435\u0432\u043e\u0435 \u0441\u043e\u0435\u0434\u0438\u043d\u0435\u043d\u0438\u0435 \u0432 Pandas (\u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u043e\u043c) \u2013 \u0421\u0442\u0430\u0442\u043e\u0440\u0438\u0430\u043b\u044b\" \/>\n<meta property=\"og:description\" content=\"\u0412 \u044d\u0442\u043e\u043c \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f, \u043a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043b\u0435\u0432\u043e\u0435 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