{"id":3603,"date":"2023-07-16T14:11:02","date_gmt":"2023-07-16T14:11:02","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/"},"modified":"2023-07-16T14:11:02","modified_gmt":"2023-07-16T14:11:02","slug":"%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/","title":{"rendered":"\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 python"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0423 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0446\u0456 <strong>\u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f<\/strong> \u2014 \u0446\u0435 \u0441\u043f\u043e\u0441\u0456\u0431 \u0432\u0456\u0437\u0443\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u0457 \u043f\u043e\u0434\u0456\u0431\u043d\u043e\u0441\u0442\u0456 \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c \u0443 \u043d\u0430\u0431\u043e\u0440\u0456 \u0434\u0430\u043d\u0438\u0445 \u0443 \u0430\u0431\u0441\u0442\u0440\u0430\u043a\u0442\u043d\u043e\u043c\u0443 \u0434\u0435\u043a\u0430\u0440\u0442\u043e\u0432\u043e\u043c\u0443 \u043f\u0440\u043e\u0441\u0442\u043e\u0440\u0456 (\u0437\u0430\u0437\u0432\u0438\u0447\u0430\u0439 2D).<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0439\u043f\u0440\u043e\u0441\u0442\u0456\u0448\u0438\u0439 \u0441\u043f\u043e\u0441\u0456\u0431 \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python \u2014 \u0446\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>MDS()<\/strong> \u043f\u0456\u0434\u043c\u043e\u0434\u0443\u043b\u044f <strong>sklearn.manifold<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u044e \u0444\u0443\u043d\u043a\u0446\u0456\u044e \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434: \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0438\u043f\u0443\u0441\u0442\u0456\u043c\u043e, \u0449\u043e \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 \u0444\u0440\u0435\u0439\u043c \u0434\u0430\u043d\u0438\u0445 pandas, \u044f\u043a\u0438\u0439 \u043c\u0456\u0441\u0442\u0438\u0442\u044c \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u044e \u043f\u0440\u043e \u0440\u0456\u0437\u043d\u0438\u0445 \u0431\u0430\u0441\u043a\u0435\u0442\u0431\u043e\u043b\u0456\u0441\u0442\u0456\u0432:<\/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;\">#create DataFrane\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">player<\/span> ': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K '],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [4, 4, 6, 7, 8, 14, 16, 19, 25, 25, 28],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [3, 2, 2, 5, 4, 8, 7, 6, 8, 10, 11],\n                   ' <span style=\"color: #ff0000;\">blocks<\/span> ': [7, 3, 6, 7, 5, 8, 8, 4, 2, 2, 1],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [4, 5, 5, 6, 5, 8, 10, 4, 3, 2, 2]})\n\n<span style=\"color: #008080;\">#set player column as index column\n<\/span>df = df. <span style=\"color: #3366ff;\">set_index<\/span> (' <span style=\"color: #ff0000;\">player<\/span> ')\n\n<span style=\"color: #008080;\">#view Dataframe\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\n\n        points assists blocks rebounds\nplayer                                   \nA 4 3 7 4\nB 4 2 3 5\nC 6 2 6 5\nD 7 5 7 6\nE 8 4 5 5\nF 14 8 8 8\nG 16 7 8 10\nH 19 6 4 4\nI 25 8 2 3\nD 25 10 2 2\nK 28 11 1 2\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u0434\u043b\u044f \u0432\u0438\u043a\u043e\u043d\u0430\u043d\u043d\u044f \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u043e\u0433\u043e \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u0444\u0443\u043d\u043a\u0446\u0456\u0457 <strong>MDS()<\/strong> \u043c\u043e\u0434\u0443\u043b\u044f <strong>sklearn.manifold<\/strong> :<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">from<\/span> sklearn. <span style=\"color: #3366ff;\">manifold<\/span> <span style=\"color: #008000;\">import<\/span> MDS\n\n<span style=\"color: #008080;\">#perform multi-dimensional scaling\n<\/span>mds = MDS(random_state= <span style=\"color: #008000;\">0<\/span> )\nscaled_df = mds. <span style=\"color: #3366ff;\">fit_transform<\/span> (df)\n\n<span style=\"color: #008080;\">#view results of multi-dimensional scaling\n<\/span><span style=\"color: #008000;\">print<\/span> (scaled_df)\n\n[[ 7.43654469 8.10247222]\n [4.13193821 10.27360901]\n [5.20534681 7.46919526]\n [6.22323046 4.45148627]\n [3.74110999 5.25591459]\n [3.69073384 -2.88017811]\n [3.89092087 -5.19100988]\n [ -3.68593169 -3.0821144 ]\n [ -9.13631889 -6.81016012]\n [ -8.97898385 -8.50414387]\n [-12.51859044 -9.08507097]]<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041a\u043e\u0436\u0435\u043d \u0440\u044f\u0434\u043e\u043a \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u044c\u043d\u043e\u0433\u043e DataFrame \u0431\u0443\u043b\u043e \u0437\u043c\u0435\u043d\u0448\u0435\u043d\u043e \u0434\u043e (x, y) \u043a\u043e\u043e\u0440\u0434\u0438\u043d\u0430\u0442.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u0434\u043b\u044f \u0432\u0456\u0437\u0443\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u0457 \u0446\u0438\u0445 \u043a\u043e\u043e\u0440\u0434\u0438\u043d\u0430\u0442 \u0443 2D-\u043f\u0440\u043e\u0441\u0442\u043e\u0440\u0456:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> matplotlib.pyplot <span style=\"color: #008000;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#create scatterplot\n<\/span>plt. <span style=\"color: #3366ff;\">scatter<\/span> (scaled_df[:,0], scaled_df[:,1])\n\n<span style=\"color: #008080;\">#add axis labels\n<\/span>plt. <span style=\"color: #3366ff;\">xlabel<\/span> (' <span style=\"color: #ff0000;\">Coordinate 1<\/span> ')\nplt. <span style=\"color: #3366ff;\">ylabel<\/span> (' <span style=\"color: #ff0000;\">Coordinate 2<\/span> ')\n\n<span style=\"color: #008080;\">#add lables to each point\n<\/span><span style=\"color: #008000;\">for<\/span> i, txt <span style=\"color: #008000;\">in<\/span> enumerate( <span style=\"color: #3366ff;\">df.index<\/span> ):\n    plt. <span style=\"color: #3366ff;\">annotate<\/span> (txt, (scaled_df[:,0][i]+.3, scaled_df[:,1][i]))\n\n<span style=\"color: #008080;\">#display scatterplot\n<\/span>plt. <span style=\"color: #3366ff;\">show<\/span> ()\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-29710\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mds2.jpg\" alt=\"\u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python\" width=\"596\" height=\"432\" srcset=\"\" sizes=\"\"><\/p>\n<p> <span style=\"color: #000000;\">\u0413\u0440\u0430\u0432\u0446\u0456 \u0432 \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u044c\u043d\u043e\u043c\u0443 DataFrame, \u044f\u043a\u0456 \u043c\u0430\u044e\u0442\u044c \u0441\u0445\u043e\u0436\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0432 \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u044c\u043d\u0438\u0445 \u0447\u043e\u0442\u0438\u0440\u044c\u043e\u0445 \u0441\u0442\u043e\u0432\u043f\u0446\u044f\u0445 (\u043e\u0447\u043a\u0438, \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438\u0432\u043d\u0456 \u043f\u0435\u0440\u0435\u0434\u0430\u0447\u0456, \u0431\u043b\u043e\u043a\u0438 \u0442\u0430 \u043f\u0456\u0434\u0431\u0438\u0440\u0430\u043d\u043d\u044f), \u0440\u043e\u0437\u0442\u0430\u0448\u043e\u0432\u0430\u043d\u0456 \u0431\u043b\u0438\u0437\u044c\u043a\u043e \u043e\u0434\u0438\u043d \u0434\u043e \u043e\u0434\u043d\u043e\u0433\u043e \u043d\u0430 \u0441\u044e\u0436\u0435\u0442\u0456.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u043f\u0440\u0438\u043a\u043b\u0430\u0434, \u0433\u0440\u0430\u0432\u0446\u0456 <strong>F<\/strong> \u0456 <strong>G<\/strong> \u0437\u0430\u043a\u0440\u0438\u0442\u0456 \u043e\u0434\u0438\u043d \u0434\u043e \u043e\u0434\u043d\u043e\u0433\u043e. \u041e\u0441\u044c \u0457\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0437 \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u044c\u043d\u043e\u0433\u043e DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#select rows with index labels 'F' and 'G'\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">F<\/span> ',' <span style=\"color: #ff0000;\">G<\/span> ']]\n\n        points assists blocks rebounds\nplayer\t\t\t\t\nF 14 8 8 8\nG 16 7 8 10\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0407\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0434\u043b\u044f \u043e\u0447\u043e\u043a, \u043f\u0435\u0440\u0435\u0434\u0430\u0447, \u0431\u043b\u043e\u043a\u0456\u0432 \u0456 \u043f\u0456\u0434\u0431\u0438\u0440\u0430\u043d\u044c \u0434\u0443\u0436\u0435 \u0441\u0445\u043e\u0436\u0456, \u0449\u043e \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u0447\u043e\u043c\u0443 \u0432\u043e\u043d\u0438 \u0442\u0430\u043a \u0431\u043b\u0438\u0437\u044c\u043a\u0456 \u043e\u0434\u0438\u043d \u0434\u043e \u043e\u0434\u043d\u043e\u0433\u043e \u043d\u0430 \u0434\u0432\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u043e\u043c\u0443 \u0433\u0440\u0430\u0444\u0456\u043a\u0443.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430 \u043f\u0440\u043e\u0442\u0438\u0432\u0430\u0433\u0443 \u0446\u044c\u043e\u043c\u0443 \u0440\u043e\u0437\u0433\u043b\u044f\u043d\u0435\u043c\u043e \u0433\u0440\u0430\u0432\u0446\u0456\u0432 <strong>B<\/strong> \u0456 <strong>K<\/strong> , \u044f\u043a\u0456 \u0437\u043d\u0430\u0445\u043e\u0434\u044f\u0442\u044c\u0441\u044f \u0434\u0430\u043b\u0435\u043a\u043e \u043e\u0434\u0438\u043d \u0432\u0456\u0434 \u043e\u0434\u043d\u043e\u0433\u043e \u0432 \u0441\u044e\u0436\u0435\u0442\u0456.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u042f\u043a\u0449\u043e \u043c\u0438 \u0437\u0432\u0435\u0440\u043d\u0435\u043c\u043e\u0441\u044f \u0434\u043e \u0457\u0445\u043d\u0456\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0432 \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u044c\u043d\u043e\u043c\u0443 DataFrame, \u0442\u043e \u043f\u043e\u0431\u0430\u0447\u0438\u043c\u043e, \u0449\u043e \u0432\u043e\u043d\u0438 \u0434\u043e\u0441\u0438\u0442\u044c \u0440\u0456\u0437\u043d\u0456:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#select rows with index labels 'B' and 'K'\n<span style=\"color: #000000;\">df. <span style=\"color: #3366ff;\">loc<\/span> [[' <span style=\"color: #ff0000;\">B<\/span> ',' <span style=\"color: #ff0000;\">K<\/span> ']]<\/span><\/span>\n\n        points assists blocks rebounds\nplayer\t\t\t\t\nB 4 2 3 5\nK 28 11 1 2<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0422\u0430\u043a\u0438\u043c \u0447\u0438\u043d\u043e\u043c, \u0434\u0432\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0438\u0439 \u0433\u0440\u0430\u0444\u0456\u043a \u0454 \u0445\u043e\u0440\u043e\u0448\u0438\u043c \u0441\u043f\u043e\u0441\u043e\u0431\u043e\u043c \u0432\u0456\u0437\u0443\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u0457 \u0442\u043e\u0433\u043e, \u043d\u0430\u0441\u043a\u0456\u043b\u044c\u043a\u0438 \u0441\u0445\u043e\u0436\u0438\u0439 \u043a\u043e\u0436\u0435\u043d \u0433\u0440\u0430\u0432\u0435\u0446\u044c \u0437\u0430 \u0432\u0441\u0456\u043c\u0430 \u0437\u043c\u0456\u043d\u043d\u0438\u043c\u0438 \u0432 DataFframe.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0413\u0440\u0430\u0432\u0446\u0456 \u0437\u0456 \u0441\u0445\u043e\u0436\u043e\u044e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u043e\u044e \u0437\u0433\u0440\u0443\u043f\u043e\u0432\u0430\u043d\u0456 \u0431\u043b\u0438\u0437\u044c\u043a\u043e \u043e\u0434\u0438\u043d \u0434\u043e \u043e\u0434\u043d\u043e\u0433\u043e, \u0442\u043e\u0434\u0456 \u044f\u043a \u0433\u0440\u0430\u0432\u0446\u0456 \u0437 \u0434\u0443\u0436\u0435 \u0440\u0456\u0437\u043d\u043e\u044e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u043e\u044e \u0440\u043e\u0437\u0442\u0430\u0448\u043e\u0432\u0430\u043d\u0456 \u0434\u0430\u043b\u0456 \u043e\u0434\u0438\u043d \u0432\u0456\u0434 \u043e\u0434\u043d\u043e\u0433\u043e \u0432 \u0441\u044e\u0436\u0435\u0442\u0456.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h2>\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 \u0437\u0430\u0432\u0434\u0430\u043d\u043d\u044f \u0432 Python:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/uk\/\u043d\u043e\u0440\u043c\u0430\u043b\u0456\u0437\u0443\u0432\u0430\u0442\u0438-\u0434\u0430\u043d\u0456-\u0432-python\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u043d\u043e\u0440\u043c\u0430\u043b\u0456\u0437\u0443\u0432\u0430\u0442\u0438 \u0434\u0430\u043d\u0456 \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0432\u0438\u0434\u0430\u043b\u0438\u0442\u0438-\u0432\u0438\u043a\u0438\u0434\u0438-python\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0432\u0438\u0434\u0430\u043b\u0438\u0442\u0438 \u0432\u0438\u043a\u0438\u0434\u0438 \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0442\u0435\u0441\u0442-\u043d\u043e\u0440\u043c\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u0456-python\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u043f\u0435\u0440\u0435\u0432\u0456\u0440\u0438\u0442\u0438 \u043d\u043e\u0440\u043c\u0430\u043b\u044c\u043d\u0456\u0441\u0442\u044c \u0443 Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0423 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0446\u0456 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u2014 \u0446\u0435 \u0441\u043f\u043e\u0441\u0456\u0431 \u0432\u0456\u0437\u0443\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u0457 \u043f\u043e\u0434\u0456\u0431\u043d\u043e\u0441\u0442\u0456 \u0441\u043f\u043e\u0441\u0442\u0435\u0440\u0435\u0436\u0435\u043d\u044c \u0443 \u043d\u0430\u0431\u043e\u0440\u0456 \u0434\u0430\u043d\u0438\u0445 \u0443 \u0430\u0431\u0441\u0442\u0440\u0430\u043a\u0442\u043d\u043e\u043c\u0443 \u0434\u0435\u043a\u0430\u0440\u0442\u043e\u0432\u043e\u043c\u0443 \u043f\u0440\u043e\u0441\u0442\u043e\u0440\u0456 (\u0437\u0430\u0437\u0432\u0438\u0447\u0430\u0439 2D). \u041d\u0430\u0439\u043f\u0440\u043e\u0441\u0442\u0456\u0448\u0438\u0439 \u0441\u043f\u043e\u0441\u0456\u0431 \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python \u2014 \u0446\u0435 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e MDS() \u043f\u0456\u0434\u043c\u043e\u0434\u0443\u043b\u044f sklearn.manifold . \u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u043e\u043c\u0443 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u044e \u0444\u0443\u043d\u043a\u0446\u0456\u044e \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456. \u041f\u0440\u0438\u043a\u043b\u0430\u0434: \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python \u041f\u0440\u0438\u043f\u0443\u0441\u0442\u0456\u043c\u043e, \u0449\u043e \u0443 \u043d\u0430\u0441 \u0454 \u0442\u0430\u043a\u0438\u0439 [&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 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python - Statology<\/title>\n<meta name=\"description\" content=\"\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a\u0443 \u043d\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python.\" \/>\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\/uk\/\u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435-\u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f-\u0432-python\/\" \/>\n<meta property=\"og:locale\" content=\"uk_UA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python - Statology\" \/>\n<meta property=\"og:description\" content=\"\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a\u0443 \u043d\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/uk\/\u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435-\u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f-\u0432-python\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-16T14:11:02+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mds2.jpg\" \/>\n<meta name=\"author\" content=\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u041f\u0440\u0438\u0431\u043b. \u0447\u0430\u0441 \u0447\u0438\u0442\u0430\u043d\u043d\u044f\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 \u0445\u0432\u0438\u043b\u0438\u043d\u0430\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/\",\"url\":\"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/\",\"name\":\"\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python - Statology\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/uk\/#website\"},\"datePublished\":\"2023-07-16T14:11:02+00:00\",\"dateModified\":\"2023-07-16T14:11:02+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/uk\/#\/schema\/person\/2affa1a5da08a4b61ab4becd078c191a\"},\"description\":\"\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a\u0443 \u043d\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/#breadcrumb\"},\"inLanguage\":\"uk\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u0434\u043e\u0434\u043e\u043c\u0443\",\"item\":\"https:\/\/statorials.org\/uk\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 python\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/uk\/#website\",\"url\":\"https:\/\/statorials.org\/uk\/\",\"name\":\"Statorials\",\"description\":\"\u0412\u0430\u0448 \u043f\u0443\u0442\u0456\u0432\u043d\u0438\u043a \u0434\u043e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u043e\u0457 \u043a\u043e\u043c\u043f\u0435\u0442\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0456!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/uk\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"uk\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/uk\/#\/schema\/person\/2affa1a5da08a4b61ab4becd078c191a\",\"name\":\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"uk\",\"@id\":\"https:\/\/statorials.org\/uk\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/uk\/wp-content\/uploads\/2023\/11\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/uk\/wp-content\/uploads\/2023\/11\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\"},\"description\":\"\u041f\u0440\u0438\u0432\u0456\u0442, \u044f \u0411\u0435\u043d\u0434\u0436\u0430\u043c\u0456\u043d, \u043f\u0440\u043e\u0444\u0435\u0441\u043e\u0440 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438 \u043d\u0430 \u043f\u0435\u043d\u0441\u0456\u0457, \u044f\u043a\u0438\u0439 \u0441\u0442\u0430\u0432 \u0432\u0438\u043a\u043b\u0430\u0434\u0430\u0447\u0435\u043c \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438. \u041c\u0430\u044e\u0447\u0438 \u0432\u0435\u043b\u0438\u043a\u0438\u0439 \u0434\u043e\u0441\u0432\u0456\u0434 \u0456 \u0437\u043d\u0430\u043d\u043d\u044f \u0432 \u0433\u0430\u043b\u0443\u0437\u0456 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438, \u044f \u0433\u043e\u0442\u043e\u0432\u0438\u0439 \u043f\u043e\u0434\u0456\u043b\u0438\u0442\u0438\u0441\u044f \u0441\u0432\u043e\u0457\u043c\u0438 \u0437\u043d\u0430\u043d\u043d\u044f\u043c\u0438, \u0449\u043e\u0431 \u0440\u043e\u0437\u0448\u0438\u0440\u0438\u0442\u0438 \u043c\u043e\u0436\u043b\u0438\u0432\u043e\u0441\u0442\u0456 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u0456\u0432 \u0447\u0435\u0440\u0435\u0437 Statorials. \u0414\u0456\u0437\u043d\u0430\u0439\u0442\u0435\u0441\u044f \u0431\u0456\u043b\u044c\u0448\u0435\",\"sameAs\":[\"http:\/\/statorials.org\/uk\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python - Statology","description":"\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a\u0443 \u043d\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/statorials.org\/uk\/\u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435-\u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f-\u0432-python\/","og_locale":"uk_UA","og_type":"article","og_title":"\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python - Statology","og_description":"\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a\u0443 \u043d\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python.","og_url":"https:\/\/statorials.org\/uk\/\u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435-\u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f-\u0432-python\/","og_site_name":"Statorials","article_published_time":"2023-07-16T14:11:02+00:00","og_image":[{"url":"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mds2.jpg"}],"author":"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f","twitter_card":"summary_large_image","twitter_misc":{"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e":"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f","\u041f\u0440\u0438\u0431\u043b. \u0447\u0430\u0441 \u0447\u0438\u0442\u0430\u043d\u043d\u044f":"1 \u0445\u0432\u0438\u043b\u0438\u043d\u0430"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/","url":"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/","name":"\u042f\u043a \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python - Statology","isPartOf":{"@id":"https:\/\/statorials.org\/uk\/#website"},"datePublished":"2023-07-16T14:11:02+00:00","dateModified":"2023-07-16T14:11:02+00:00","author":{"@id":"https:\/\/statorials.org\/uk\/#\/schema\/person\/2affa1a5da08a4b61ab4becd078c191a"},"description":"\u0423 \u0446\u044c\u043e\u043c\u0443 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a\u0443 \u043d\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0456 \u043f\u043e\u044f\u0441\u043d\u044e\u0454\u0442\u044c\u0441\u044f, \u044f\u043a \u0432\u0438\u043a\u043e\u043d\u0443\u0432\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 Python.","breadcrumb":{"@id":"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/#breadcrumb"},"inLanguage":"uk","potentialAction":[{"@type":"ReadAction","target":["https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/statorials.org\/uk\/%d0%b1%d0%b0%d0%b3%d0%b0%d1%82%d0%be%d0%b2%d0%b8%d0%bc%d1%96%d1%80%d0%bd%d0%b5-%d0%bc%d0%b0%d1%81%d1%88%d1%82%d0%b0%d0%b1%d1%83%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%b2-python\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u0434\u043e\u0434\u043e\u043c\u0443","item":"https:\/\/statorials.org\/uk\/"},{"@type":"ListItem","position":2,"name":"\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0431\u0430\u0433\u0430\u0442\u043e\u0432\u0438\u043c\u0456\u0440\u043d\u0435 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0443\u0432\u0430\u043d\u043d\u044f \u0432 python"}]},{"@type":"WebSite","@id":"https:\/\/statorials.org\/uk\/#website","url":"https:\/\/statorials.org\/uk\/","name":"Statorials","description":"\u0412\u0430\u0448 \u043f\u0443\u0442\u0456\u0432\u043d\u0438\u043a \u0434\u043e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u043e\u0457 \u043a\u043e\u043c\u043f\u0435\u0442\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0456!","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/statorials.org\/uk\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"uk"},{"@type":"Person","@id":"https:\/\/statorials.org\/uk\/#\/schema\/person\/2affa1a5da08a4b61ab4becd078c191a","name":"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f","image":{"@type":"ImageObject","inLanguage":"uk","@id":"https:\/\/statorials.org\/uk\/#\/schema\/person\/image\/","url":"https:\/\/statorials.org\/uk\/wp-content\/uploads\/2023\/11\/Dr.-Benjamin-Anderson-96x96.jpg","contentUrl":"https:\/\/statorials.org\/uk\/wp-content\/uploads\/2023\/11\/Dr.-Benjamin-Anderson-96x96.jpg","caption":"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f"},"description":"\u041f\u0440\u0438\u0432\u0456\u0442, \u044f \u0411\u0435\u043d\u0434\u0436\u0430\u043c\u0456\u043d, \u043f\u0440\u043e\u0444\u0435\u0441\u043e\u0440 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438 \u043d\u0430 \u043f\u0435\u043d\u0441\u0456\u0457, \u044f\u043a\u0438\u0439 \u0441\u0442\u0430\u0432 \u0432\u0438\u043a\u043b\u0430\u0434\u0430\u0447\u0435\u043c \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438. \u041c\u0430\u044e\u0447\u0438 \u0432\u0435\u043b\u0438\u043a\u0438\u0439 \u0434\u043e\u0441\u0432\u0456\u0434 \u0456 \u0437\u043d\u0430\u043d\u043d\u044f \u0432 \u0433\u0430\u043b\u0443\u0437\u0456 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438, \u044f \u0433\u043e\u0442\u043e\u0432\u0438\u0439 \u043f\u043e\u0434\u0456\u043b\u0438\u0442\u0438\u0441\u044f \u0441\u0432\u043e\u0457\u043c\u0438 \u0437\u043d\u0430\u043d\u043d\u044f\u043c\u0438, \u0449\u043e\u0431 \u0440\u043e\u0437\u0448\u0438\u0440\u0438\u0442\u0438 \u043c\u043e\u0436\u043b\u0438\u0432\u043e\u0441\u0442\u0456 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u0456\u0432 \u0447\u0435\u0440\u0435\u0437 Statorials. \u0414\u0456\u0437\u043d\u0430\u0439\u0442\u0435\u0441\u044f \u0431\u0456\u043b\u044c\u0448\u0435","sameAs":["http:\/\/statorials.org\/uk"]}]}},"yoast_meta":{"yoast_wpseo_title":"","yoast_wpseo_metadesc":"","yoast_wpseo_canonical":""},"_links":{"self":[{"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/posts\/3603"}],"collection":[{"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/comments?post=3603"}],"version-history":[{"count":0,"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/posts\/3603\/revisions"}],"wp:attachment":[{"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/media?parent=3603"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/categories?post=3603"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statorials.org\/uk\/wp-json\/wp\/v2\/tags?post=3603"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}