{"id":1585,"date":"2023-07-25T18:18:37","date_gmt":"2023-07-25T18:18:37","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d1%80%d0%be%d0%b7%d0%bc%d1%96%d1%80-%d0%bc%d0%be%d1%80%d1%81%d1%8c%d0%ba%d0%be%d1%96-%d1%84%d1%96%d0%b3%d1%83%d1%80%d0%b8\/"},"modified":"2023-07-25T18:18:37","modified_gmt":"2023-07-25T18:18:37","slug":"%d1%80%d0%be%d0%b7%d0%bc%d1%96%d1%80-%d0%bc%d0%be%d1%80%d1%81%d1%8c%d0%ba%d0%be%d1%96-%d1%84%d1%96%d0%b3%d1%83%d1%80%d0%b8","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d1%80%d0%be%d0%b7%d0%bc%d1%96%d1%80-%d0%bc%d0%be%d1%80%d1%81%d1%8c%d0%ba%d0%be%d1%96-%d1%84%d1%96%d0%b3%d1%83%d1%80%d0%b8\/","title":{"rendered":"\u042f\u043a \u0432\u0456\u0434\u043a\u043e\u0440\u0438\u0433\u0443\u0432\u0430\u0442\u0438 \u0440\u043e\u0437\u043c\u0456\u0440 \u0444\u0456\u0433\u0443\u0440\u0438 \u0441\u044e\u0436\u0435\u0442\u0443 seaborn"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0406\u0441\u043d\u0443\u0454 \u0434\u0432\u0430 \u0441\u043f\u043e\u0441\u043e\u0431\u0438 \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0440\u043e\u0437\u043c\u0456\u0440 \u0433\u0440\u0430\u0444\u0456\u043a\u0430 \u043c\u043e\u0440\u0441\u044c\u043a\u043e\u0457 \u0434\u0456\u043b\u044f\u043d\u043a\u0438 \u0432 Python.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041f\u0435\u0440\u0448\u0438\u0439 \u043c\u0435\u0442\u043e\u0434 \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0437\u043c\u0456\u043d\u0438 \u0440\u043e\u0437\u043c\u0456\u0440\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0456\u0432 \u00ab\u043d\u0430 \u0440\u0456\u0432\u043d\u0456 \u043e\u0441\u0456\u00bb, \u0442\u0430\u043a\u0438\u0445 \u044f\u043a \u0433\u0440\u0430\u0444\u0456\u043a\u0438 <strong>sns.scatterplot()<\/strong> \u0430\u0431\u043e <strong>sns.boxplot()<\/strong> :<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>sns. <span style=\"color: #3366ff;\">set<\/span> (rc={\" <span style=\"color: #ff0000;\">figure<\/span> . <span style=\"color: #ff0000;\">figsize<\/span> \":( <span style=\"color: #008000;\">3<\/span> , <span style=\"color: #008000;\">4<\/span> )}) <span style=\"color: #008080;\">#width=3, #height=4\n<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0414\u0440\u0443\u0433\u0438\u0439 \u043c\u0435\u0442\u043e\u0434 \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0437\u043c\u0456\u043d\u0438 \u0440\u043e\u0437\u043c\u0456\u0440\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0456\u0432 \u00ab\u0440\u0456\u0432\u043d\u044f \u0444\u0456\u0433\u0443\u0440\u00bb, \u0442\u0430\u043a\u0438\u0445 \u044f\u043a <strong>sns.lmplot()<\/strong> \u0456 <strong>sns.catplot()<\/strong> \u0430\u0431\u043e <strong>sns.jointplot()<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0426\u0435\u0439 \u043c\u0435\u0442\u043e\u0434 \u0432\u0438\u043c\u0430\u0433\u0430\u0454, \u0449\u043e\u0431 \u0432\u0438 \u0432\u043a\u0430\u0437\u0430\u043b\u0438 <strong>\u0432\u0438\u0441\u043e\u0442\u0443<\/strong> \u0442\u0430 <strong>\u0430\u0441\u043f\u0435\u043a\u0442<\/strong> (\u0432\u0456\u0434\u043d\u043e\u0448\u0435\u043d\u043d\u044f \u0448\u0438\u0440\u0438\u043d\u0438 \u0434\u043e \u0432\u0438\u0441\u043e\u0442\u0438) \u0432 \u0430\u0440\u0433\u0443\u043c\u0435\u043d\u0442\u0430\u0445 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0438:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>sns. <span style=\"color: #3366ff;\">lmplot<\/span> (data=df, x=\" <span style=\"color: #ff0000;\">var1<\/span> \", y=\" <span style=\"color: #ff0000;\">var2<\/span> \",\n              height= <span style=\"color: #008000;\">6<\/span> , aspect= <span style=\"color: #008000;\">1.5<\/span> ) <span style=\"color: #008080;\">#height=6, width=1.5 times larger than height<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u0456 \u0434\u0432\u0430 \u043c\u0435\u0442\u043e\u0434\u0438 \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 1: \u0437\u043c\u0456\u043d\u0456\u0442\u044c \u0440\u043e\u0437\u043c\u0456\u0440 \u0433\u0440\u0430\u0444\u0456\u043a\u0456\u0432 \u043d\u0430 \u0440\u0456\u0432\u043d\u0456 \u043e\u0441\u0456<\/strong><\/span><\/h3>\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 \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0445\u043c\u0430\u0440\u0443 \u043c\u043e\u0440\u0441\u044c\u043a\u0438\u0445 \u0442\u043e\u0447\u043e\u043a \u0448\u0438\u0440\u0438\u043d\u043e\u044e 8 \u0456 \u0432\u0438\u0441\u043e\u0442\u043e\u044e 4:<\/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<span style=\"color: #008000;\">import<\/span> seaborn <span style=\"color: #008000;\">as<\/span> sns\n\n<span style=\"color: #008080;\">#create data\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({\" <span style=\"color: #ff0000;\">var1<\/span> \": [25, 12, 15, 14, 19, 23, 25, 29],\n                   \" <span style=\"color: #ff0000;\">var2<\/span> \": [5, 7, 7, 9, 12, 9, 9, 4],\n                   \" <span style=\"color: #ff0000;\">var3<\/span> \": [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#define figure size\n<\/span>sns. <span style=\"color: #3366ff;\">set<\/span> (rc={\" <span style=\"color: #ff0000;\">figure<\/span> . <span style=\"color: #ff0000;\">figsize<\/span> \":( <span style=\"color: #008000;\">8<\/span> , <span style=\"color: #008000;\">4<\/span> )}) <span style=\"color: #008080;\">#width=8, height=4<\/span>\n\n<span style=\"color: #008080;\">#display scatterplot\n<\/span>sns. <span style=\"color: #3366ff;\">scatterplot<\/span> (data=df, x=\" <span style=\"color: #ff0000;\">var1<\/span> \", y=\" <span style=\"color: #ff0000;\">var2<\/span> \")<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15807 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/seabornfigtaille1.png\" alt=\"\" width=\"579\" height=\"312\" srcset=\"\" sizes=\"\"><\/p>\n<p> <span style=\"color: #000000;\">\u0410 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u043a\u043e\u0440\u043e\u0431\u0447\u0430\u0442\u0443 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0443 Seaborn \u0456\u0437 \u0448\u0438\u0440\u0438\u043d\u043e\u044e 6 \u0456 \u0432\u0438\u0441\u043e\u0442\u043e\u044e 5:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define figure size\n<\/span>sns. <span style=\"color: #3366ff;\">set<\/span> (rc={\" <span style=\"color: #ff0000;\">figure<\/span> . <span style=\"color: #ff0000;\">figsize<\/span> \":( <span style=\"color: #008000;\">6<\/span> , <span style=\"color: #008000;\">5<\/span> )}) <span style=\"color: #008080;\">#width=6, height=5<\/span>\n\n<span style=\"color: #008080;\">#display scatterplot\n<\/span>sns. <span style=\"color: #3366ff;\">boxplot<\/span> (data=df[\" <span style=\"color: #ff0000;\">var1<\/span> \"])<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15808 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/seabornfigsize2.png\" alt=\"\" width=\"417\" height=\"380\" srcset=\"\" sizes=\"\"><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0421\u043f\u043e\u0441\u0456\u0431 2: \u0437\u043c\u0456\u043d\u0456\u0442\u044c \u0440\u043e\u0437\u043c\u0456\u0440 \u043a\u043e\u043d\u0442\u0443\u0440\u0456\u0432 \u043d\u0430 \u0440\u0456\u0432\u043d\u0456 \u0444\u0456\u0433\u0443\u0440\u0438<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0414\u043b\u044f \u0433\u0440\u0430\u0444\u0456\u043a\u0456\u0432 \u043d\u0430 \u0440\u0456\u0432\u043d\u0456 \u0444\u0456\u0433\u0443\u0440 (\u0442\u0430\u043a\u0438\u0445 \u044f\u043a sns.lmplot, sns.catplot, sns.jointplot \u0442\u043e\u0449\u043e) \u043d\u0435\u043e\u0431\u0445\u0456\u0434\u043d\u043e \u0432\u043a\u0430\u0437\u0430\u0442\u0438 \u0432\u0438\u0441\u043e\u0442\u0443 \u0442\u0430 \u0448\u0438\u0440\u0438\u043d\u0443 \u0432 \u0441\u0430\u043c\u0456\u0439 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\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 \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u043c\u043e\u0440\u0441\u044c\u043a\u0438\u0439 lmplot \u0437 \u0432\u0438\u0441\u043e\u0442\u043e\u044e 5 \u0456 \u0448\u0438\u0440\u0438\u043d\u043e\u044e \u0432 1,5 \u0440\u0430\u0437\u0438 \u0431\u0456\u043b\u044c\u0448\u043e\u044e \u0437\u0430 \u0432\u0438\u0441\u043e\u0442\u0443:<\/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<span style=\"color: #008000;\">import<\/span> seaborn <span style=\"color: #008000;\">as<\/span> sns\n\n<span style=\"color: #008080;\">#createdata\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({\" <span style=\"color: #ff0000;\">var1<\/span> \": [25, 12, 15, 14, 19, 23, 25, 29],\n                   \" <span style=\"color: #ff0000;\">var2<\/span> \": [5, 7, 7, 9, 12, 9, 9, 4],\n                   \" <span style=\"color: #ff0000;\">var3<\/span> \": [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#create lmplot\n<\/span>sns. <span style=\"color: #3366ff;\">lmplot<\/span> (data=df, x=\" <span style=\"color: #ff0000;\">var1<\/span> \", y=\" <span style=\"color: #ff0000;\">var2<\/span> \",\n              height= <span style=\"color: #008000;\">5<\/span> , aspect= <span style=\"color: #008000;\">1.5<\/span> ) <span style=\"color: #008080;\">#height=5, width=1.5 times larger than height<\/span>\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15809 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/seabornfigsize3.png\" alt=\"\" width=\"593\" height=\"397\" srcset=\"\" sizes=\"\"><\/p>\n<p> <span style=\"color: #000000;\">\u0410 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0441\u043f\u0456\u043b\u044c\u043d\u0443 \u043c\u043e\u0440\u0441\u044c\u043a\u0443 \u0434\u0456\u043b\u044f\u043d\u043a\u0443 \u0432\u0438\u0441\u043e\u0442\u043e\u044e 3,5. \u041e\u0441\u043a\u0456\u043b\u044c\u043a\u0438 \u0441\u043f\u0456\u043b\u044c\u043d\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a \u0437\u0430 \u0437\u0430\u043c\u043e\u0432\u0447\u0443\u0432\u0430\u043d\u043d\u044f\u043c \u043a\u0432\u0430\u0434\u0440\u0430\u0442\u043d\u0438\u0439, \u043d\u0430\u043c \u043d\u0435 \u043f\u043e\u0442\u0440\u0456\u0431\u043d\u043e \u0432\u043a\u0430\u0437\u0443\u0432\u0430\u0442\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0430\u0441\u043f\u0435\u043a\u0442\u0443:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>sns. <span style=\"color: #3366ff;\">jointplot<\/span> (data=df, x=\" <span style=\"color: #ff0000;\">var1<\/span> \", y=\" <span style=\"color: #ff0000;\">var2<\/span> \", height= <span style=\"color: #008000;\">3.5<\/span> )<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15810 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/seabornfigtaille4.png\" alt=\"\" width=\"318\" height=\"306\" srcset=\"\" sizes=\"\"><\/p>\n<p> <span style=\"color: #000000;\">\u0414\u0438\u0432\u0456\u0442\u044c\u0441\u044f<a href=\"https:\/\/seaborn.pydata.org\/tutorial\/function_overview.html\" target=\"_blank\" rel=\"noopener\">\u0434\u043e\u043a\u0443\u043c\u0435\u043d\u0442\u0430\u0446\u0456\u044e Seaborn<\/a> \u0434\u043b\u044f \u0434\u0435\u0442\u0430\u043b\u044c\u043d\u043e\u0433\u043e \u043f\u043e\u044f\u0441\u043d\u0435\u043d\u043d\u044f \u0440\u0456\u0437\u043d\u0438\u0446\u0456 \u043c\u0456\u0436 \u0444\u0443\u043d\u043a\u0446\u0456\u044f\u043c\u0438 \u0440\u0456\u0432\u043d\u044f \u0444\u0456\u0433\u0443\u0440\u0438 \u0442\u0430 \u0440\u0456\u0432\u043d\u044f \u043e\u0441\u0456.<\/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> <a href=\"https:\/\/statorials.org\/uk\/\u043c\u043e\u0440\u0441\u044c\u043a\u0435-\u0437\u0432\u0430\u043d\u043d\u044f\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0434\u043e\u0434\u0430\u0442\u0438 \u043f\u0440\u0430\u0432\u043e \u0432\u043b\u0430\u0441\u043d\u043e\u0441\u0442\u0456 \u043d\u0430 \u0434\u0456\u043b\u044f\u043d\u043a\u0438 Seaborn<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u043c\u0456\u0442\u043a\u0438-\u043c\u043e\u0440\u0441\u044c\u043a\u043e\u0456-\u043e\u0441\u0456\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u043f\u043e\u0437\u043d\u0430\u0447\u043a\u0438 \u043e\u0441\u0435\u0439 \u043d\u0430 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0456 Seaborn<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u043d\u044f-\u043c\u043e\u0440\u0441\u044c\u043a\u043e\u0456-\u043b\u0435\u0433\u0435\u043d\u0434\u0438\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u043f\u043e\u043b\u043e\u0436\u0435\u043d\u043d\u044f \u043b\u0435\u0433\u0435\u043d\u0434\u0438 \u0432 Seaborn<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0406\u0441\u043d\u0443\u0454 \u0434\u0432\u0430 \u0441\u043f\u043e\u0441\u043e\u0431\u0438 \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0440\u043e\u0437\u043c\u0456\u0440 \u0433\u0440\u0430\u0444\u0456\u043a\u0430 \u043c\u043e\u0440\u0441\u044c\u043a\u043e\u0457 \u0434\u0456\u043b\u044f\u043d\u043a\u0438 \u0432 Python. \u041f\u0435\u0440\u0448\u0438\u0439 \u043c\u0435\u0442\u043e\u0434 \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0437\u043c\u0456\u043d\u0438 \u0440\u043e\u0437\u043c\u0456\u0440\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0456\u0432 \u00ab\u043d\u0430 \u0440\u0456\u0432\u043d\u0456 \u043e\u0441\u0456\u00bb, \u0442\u0430\u043a\u0438\u0445 \u044f\u043a \u0433\u0440\u0430\u0444\u0456\u043a\u0438 sns.scatterplot() \u0430\u0431\u043e sns.boxplot() : sns. set (rc={&#8221; figure . figsize &#8220;:( 3 , 4 )}) #width=3, #height=4 \u0414\u0440\u0443\u0433\u0438\u0439 \u043c\u0435\u0442\u043e\u0434 \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0437\u043c\u0456\u043d\u0438 \u0440\u043e\u0437\u043c\u0456\u0440\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0456\u0432 \u00ab\u0440\u0456\u0432\u043d\u044f \u0444\u0456\u0433\u0443\u0440\u00bb, \u0442\u0430\u043a\u0438\u0445 \u044f\u043a sns.lmplot() \u0456 [&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 \u0432\u0456\u0434\u0440\u0435\u0433\u0443\u043b\u044e\u0432\u0430\u0442\u0438 \u0440\u043e\u0437\u043c\u0456\u0440 \u0444\u0456\u0433\u0443\u0440\u0438 \u0441\u044e\u0436\u0435\u0442\u0443 Seaborn - 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 \u0437\u043c\u0456\u043d\u0438\u0442\u0438 \u0440\u043e\u0437\u043c\u0456\u0440 \u0444\u0456\u0433\u0443\u0440\u0438 \u0434\u0456\u0430\u0433\u0440\u0430\u043c\u0438 Seaborn \u0443 Python, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 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