{"id":1821,"date":"2023-07-24T20:30:21","date_gmt":"2023-07-24T20:30:21","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d1%81%d1%82%d0%b0%d0%bd%d0%b4%d0%b0%d1%80%d1%82%d0%b8%d0%b7%d0%b8%d1%80%d0%be%d0%b2%d0%b0%d1%82%d1%8c-%d0%b4%d0%b0%d0%bd%d0%bd%d1%8b%d0%b5-python\/"},"modified":"2023-07-24T20:30:21","modified_gmt":"2023-07-24T20:30:21","slug":"%d1%81%d1%82%d0%b0%d0%bd%d0%b4%d0%b0%d1%80%d1%82%d0%b8%d0%b7%d0%b8%d1%80%d0%be%d0%b2%d0%b0%d1%82%d1%8c-%d0%b4%d0%b0%d0%bd%d0%bd%d1%8b%d0%b5-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d1%81%d1%82%d0%b0%d0%bd%d0%b4%d0%b0%d1%80%d1%82%d0%b8%d0%b7%d0%b8%d1%80%d0%be%d0%b2%d0%b0%d1%82%d1%8c-%d0%b4%d0%b0%d0%bd%d0%bd%d1%8b%d0%b5-python\/","title":{"rendered":"\u041a\u0430\u043a \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0435 \u0432 python: \u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u0421\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0430\u0446\u0438\u044f<\/strong> \u043d\u0430\u0431\u043e\u0440\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0432\u0441\u0435\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043d\u0430\u0431\u043e\u0440\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0442\u0430\u043a\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c, \u0447\u0442\u043e\u0431\u044b \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0431\u044b\u043b\u043e \u0440\u0430\u0432\u043d\u043e 0, \u0430 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0435 \u043e\u0442\u043a\u043b\u043e\u043d\u0435\u043d\u0438\u0435 \u2014 1.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0443\u044e \u0444\u043e\u0440\u043c\u0443\u043b\u0443 \u0434\u043b\u044f \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043d\u0430\u0431\u043e\u0440\u0435 \u0434\u0430\u043d\u043d\u044b\u0445:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>x <sub>\u043d\u043e\u0432\u044b\u0439<\/sub> = (x <sub>i<\/sub> \u2013 <span style=\"text-decoration: overline;\">x<\/span> ) \/ \u0441<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0417\u043e\u043b\u043e\u0442\u043e:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>x <sub>i<\/sub><\/strong> : <sup>i-\u0435<\/sup> \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043d\u0430\u0431\u043e\u0440\u0430 \u0434\u0430\u043d\u043d\u044b\u0445<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong><span style=\"text-decoration: overline;\">x<\/span><\/strong> : \u041e\u0431\u0440\u0430\u0437\u0435\u0446 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>s<\/strong> : \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0435 \u043e\u0442\u043a\u043b\u043e\u043d\u0435\u043d\u0438\u0435 \u0432\u044b\u0431\u043e\u0440\u043a\u0438<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\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 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0434\u043b\u044f \u0431\u044b\u0441\u0442\u0440\u043e\u0439 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0432\u0441\u0435\u0445 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 DataFrame pandas \u0432 Python:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>(df- <span style=\"color: #3366ff;\">df.mean<\/span> ())\/df. <span style=\"color: #3366ff;\">std<\/span> ()\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0435 \u043f\u0440\u0438\u043c\u0435\u0440\u044b \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u044e\u0442, \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<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 1: \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0432\u0441\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u044b DataFrame<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u043a\u0430\u043a \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0432\u0441\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u0432 DataFrame pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">y<\/span> ': [8, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">x1<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">x2<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12],\n                   ' <span style=\"color: #ff0000;\">x3<\/span> ': [2, 2, 3, 2, 5, 5, 7, 9]})\n\n<span style=\"color: #008080;\">#view data frame\n<\/span>df\n\n\ty x1 x2 x3\n0 8 5 11 2\n1 12 7 8 2\n2 15 7 10 3\n3 14 9 6 2\n4 19 12 6 5\n5 23 9 5 5\n6 25 9 9 7\n7 29 4 12 9\n\n<span style=\"color: #008080;\">#standardize the values in each column\n<\/span>df_new = (df- <span style=\"color: #3366ff;\">df.mean<\/span> ())\/df. <span style=\"color: #3366ff;\">std<\/span> ()\n\n<span style=\"color: #008080;\">#view new data frame\n<\/span>df_new\n\n\t        y x1 x2 x3\n0 -1.418032 -1.078639 1.025393 -0.908151\n1 -0.857822 -0.294174 -0.146485 -0.908151\n2 -0.437664 -0.294174 0.634767 -0.525772\n3 -0.577717 0.490290 -0.927736 -0.908151\n4 0.122546 1.666987 -0.927736 0.238987\n5 0.682756 0.490290 -1.318362 0.238987\n6 0.962861 0.490290 0.244141 1.003746\n7 1.523071 -1.470871 1.416019 1.768505<\/b><\/pre>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0443\u0431\u0435\u0434\u0438\u0442\u044c\u0441\u044f, \u0447\u0442\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0438 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0435 \u043e\u0442\u043a\u043b\u043e\u043d\u0435\u043d\u0438\u0435 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0430 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0435\u043d\u043d\u043e \u0440\u0430\u0432\u043d\u044b 0 \u0438 1:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008080;\">#view mean of each column\n<\/span>df_new. <span style=\"color: #3366ff;\">mean<\/span> ()\n\ny 0.000000e+00\nx1 2.775558e-17\nx2 -4.163336e-17\nx3 5.551115e-17\ndtype:float64\n\n<span style=\"color: #008080;\">#view standard deviation of each column\n<\/span>df_new. <span style=\"color: #3366ff;\">std<\/span> ()\n\ny 1.0\nx1 1.0\nx2 1.0\nx3 1.0\ndtype:float64\n<\/b><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440 2. \u041d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0445 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 DataFrame<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0418\u043d\u043e\u0433\u0434\u0430 \u0432\u0430\u043c \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u0442\u043e\u043b\u044c\u043a\u043e \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u0432 DataFrame.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0434\u043b\u044f \u043c\u043d\u043e\u0433\u0438\u0445 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u043e\u0432 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0432\u0430\u043c \u043c\u043e\u0436\u0435\u0442 \u043f\u043e\u0442\u0440\u0435\u0431\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0442\u043e\u043b\u044c\u043a\u043e \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0435-\u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u044b, \u043f\u0440\u0435\u0436\u0434\u0435 \u0447\u0435\u043c \u043f\u043e\u0434\u0433\u043e\u043d\u044f\u0442\u044c \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u0443\u044e \u043c\u043e\u0434\u0435\u043b\u044c \u043a \u0434\u0430\u043d\u043d\u044b\u043c.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442, \u043a\u0430\u043a \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u044b\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u0432 DataFrame pandas:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">y<\/span> ': [8, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">x1<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">x2<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12],\n                   ' <span style=\"color: #ff0000;\">x3<\/span> ': [2, 2, 3, 2, 5, 5, 7, 9]})\n\n<span style=\"color: #008080;\">#view data frame\n<\/span>df\n\n\ty x1 x2 x3\n0 8 5 11 2\n1 12 7 8 2\n2 15 7 10 3\n3 14 9 6 2\n4 19 12 6 5\n5 23 9 5 5\n6 25 9 9 7\n7 29 4 12 9\n\n<span style=\"color: #008080;\">#define predictor variable columns<\/span>\ndf_x = df[[' <span style=\"color: #ff0000;\">x1<\/span> ', ' <span style=\"color: #ff0000;\">x2<\/span> ', ' <span style=\"color: #ff0000;\">x3<\/span> ']]\n\n<span style=\"color: #008080;\">#standardize the values for each predictor variable\n<\/span>df[[' <span style=\"color: #ff0000;\">x1<\/span> ',' <span style=\"color: #ff0000;\">x2<\/span> ',' <span style=\"color: #ff0000;\">x3<\/span> ']] = (df_x- <span style=\"color: #3366ff;\">df_x.mean<\/span> ())\/df_x. <span style=\"color: #3366ff;\">std<\/span> ()\n\n<span style=\"color: #008080;\">#view new data frame\n<\/span>df\n\n         y x1 x2 x3\n0 8 -1.078639 1.025393 -0.908151\n1 12 -0.294174 -0.146485 -0.908151\n2 15 -0.294174 0.634767 -0.525772\n3 14 0.490290 -0.927736 -0.908151\n4 19 1.666987 -0.927736 0.238987\n5 23 0.490290 -1.318362 0.238987\n6 25 0.490290 0.244141 1.003746\n7 29 -1.470871 1.416019 1.768505<\/b><\/pre>\n<p> <span style=\"color: #000000;\">\u041e\u0431\u0440\u0430\u0442\u0438\u0442\u0435 \u0432\u043d\u0438\u043c\u0430\u043d\u0438\u0435, \u0447\u0442\u043e \u0441\u0442\u043e\u043b\u0431\u0435\u0446 \u00aby\u00bb \u043e\u0441\u0442\u0430\u0435\u0442\u0441\u044f \u043d\u0435\u0438\u0437\u043c\u0435\u043d\u043d\u044b\u043c, \u043d\u043e \u0432\u0441\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u00abx1\u00bb, \u00abx2\u00bb \u0438 \u00abx3\u00bb \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u044b.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u043c\u043e\u0436\u0435\u043c \u0443\u0431\u0435\u0434\u0438\u0442\u044c\u0441\u044f, \u0447\u0442\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0438 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0435 \u043e\u0442\u043a\u043b\u043e\u043d\u0435\u043d\u0438\u0435 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0430 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445-\u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u043e\u0432 \u0440\u0430\u0432\u043d\u044b 0 \u0438 1 \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0435\u043d\u043d\u043e:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <b><span style=\"color: #008080;\">#view mean of each predictor variable column\n<\/span>df[[' <span style=\"color: #ff0000;\">x1<\/span> ', ' <span style=\"color: #ff0000;\">x2<\/span> ', ' <span style=\"color: #ff0000;\">x3<\/span> ']]. <span style=\"color: #3366ff;\">mean<\/span> ()\n\nx1 2.775558e-17\nx2 -4.163336e-17\nx3 5.551115e-17\ndtype:float64\n\n<span style=\"color: #008080;\">#view standard deviation of each predictor variable column\n<\/span>df[[' <span style=\"color: #ff0000;\">x1<\/span> ', ' <span style=\"color: #ff0000;\">x2<\/span> ', ' <span style=\"color: #ff0000;\">x3<\/span> ']]. <span style=\"color: #3366ff;\">std<\/span> ()\n\nx1 1.0\nx2 1.0\nx3 1.0\ndtype:float64<\/b><\/pre>\n<h3> <strong><span style=\"color: #000000;\">\u0414\u043e\u043f\u043e\u043b\u043d\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0441\u0443\u0440\u0441\u044b<\/span><\/strong><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c-\u0441\u0442\u043e\u043b\u0431\u0446\u044b-\u0444\u0440\u0435\u0438\u043c\u0430-\u0434\u0430\u043d\u043d\u044b\u0445-pandas\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u0442\u044c \u0441\u0442\u043e\u043b\u0431\u0446\u044b \u0432 DataFrame Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0443\u0434\u0430\u043b\u0438\u0442\u044c-\u0432\u044b\u0431\u0440\u043e\u0441\u044b-python\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0443\u0434\u0430\u043b\u0438\u0442\u044c \u0432\u044b\u0431\u0440\u043e\u0441\u044b \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0430\u0446\u0438\u044f-\u043f\u0440\u043e\u0442\u0438\u0432-\u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438\/\" target=\"_blank\" rel=\"noopener\">\u0421\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0430\u0446\u0438\u044f \u0438\u043b\u0438 \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u044f: \u0432 \u0447\u0435\u043c \u0440\u0430\u0437\u043d\u0438\u0446\u0430?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0421\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0430\u0446\u0438\u044f \u043d\u0430\u0431\u043e\u0440\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 \u043c\u0430\u0441\u0448\u0442\u0430\u0431\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0432\u0441\u0435\u0445 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043d\u0430\u0431\u043e\u0440\u0435 \u0434\u0430\u043d\u043d\u044b\u0445 \u0442\u0430\u043a\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c, \u0447\u0442\u043e\u0431\u044b \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0431\u044b\u043b\u043e \u0440\u0430\u0432\u043d\u043e 0, \u0430 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u043d\u043e\u0435 \u043e\u0442\u043a\u043b\u043e\u043d\u0435\u043d\u0438\u0435 \u2014 1. \u041c\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0443\u044e \u0444\u043e\u0440\u043c\u0443\u043b\u0443 \u0434\u043b\u044f \u043d\u043e\u0440\u043c\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 \u043d\u0430\u0431\u043e\u0440\u0435 \u0434\u0430\u043d\u043d\u044b\u0445: x \u043d\u043e\u0432\u044b\u0439 = (x i \u2013 x ) \/ \u0441 \u0417\u043e\u043b\u043e\u0442\u043e: x i : i-\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u043d\u0430\u0431\u043e\u0440\u0430 \u0434\u0430\u043d\u043d\u044b\u0445 x : \u041e\u0431\u0440\u0430\u0437\u0435\u0446 \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442 [&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-1821","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>\u041a\u0430\u043a \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0435 \u0432 Python: \u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438<\/title>\n<meta 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content=\"\u041a\u0430\u043a \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0435 \u0432 Python: \u0441 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438\" \/>\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 \u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0434\u0430\u043d\u043d\u044b\u0435 \u0432 Python, \u0441 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c\u0438 \u043f\u0440\u0438\u043c\u0435\u0440\u0430\u043c\u0438.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ru\/\u0441\u0442\u0430\u043d\u0434\u0430\u0440\u0442\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c-\u0434\u0430\u043d\u043d\u044b\u0435-python\/\" 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