{"id":3570,"date":"2023-07-16T18:41:15","date_gmt":"2023-07-16T18:41:15","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d1%81%d1%82%d0%b0%d1%82%d0%b8%d1%81%d1%82%d0%b8%d1%87%d0%b5%d1%81%d0%ba%d0%b8%d0%b5-%d0%bc%d0%be%d0%b4%d0%b5%d0%bb%d0%b8-%d0%bf%d1%80%d0%be%d0%b3%d0%bd%d0%be%d0%b7%d0%b8%d1%80%d1%83%d1%8e%d1%82\/"},"modified":"2023-07-16T18:41:15","modified_gmt":"2023-07-16T18:41:15","slug":"%d1%81%d1%82%d0%b0%d1%82%d0%b8%d1%81%d1%82%d0%b8%d1%87%d0%b5%d1%81%d0%ba%d0%b8%d0%b5-%d0%bc%d0%be%d0%b4%d0%b5%d0%bb%d0%b8-%d0%bf%d1%80%d0%be%d0%b3%d0%bd%d0%be%d0%b7%d0%b8%d1%80%d1%83%d1%8e%d1%82","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d1%81%d1%82%d0%b0%d1%82%d0%b8%d1%81%d1%82%d0%b8%d1%87%d0%b5%d1%81%d0%ba%d0%b8%d0%b5-%d0%bc%d0%be%d0%b4%d0%b5%d0%bb%d0%b8-%d0%bf%d1%80%d0%be%d0%b3%d0%bd%d0%be%d0%b7%d0%b8%d1%80%d1%83%d1%8e%d1%82\/","title":{"rendered":"\u041a\u0430\u043a \u0434\u0435\u043b\u0430\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u044b \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0432 statsmodels"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\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, \u0447\u0442\u043e\u0431\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u043e\u0434\u0433\u043e\u043d\u043a\u0443 \u043c\u043e\u0434\u0435\u043b\u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043c\u043e\u0434\u0443\u043b\u044f <a href=\"https:\/\/www.statsmodels.org\/stable\/index.html\" target=\"_blank\" rel=\"noopener\">statsmodels<\/a> \u0432 Python \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u043e\u0432\u044b\u0445 \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>model. <span style=\"color: #3366ff;\">predict<\/span> (df_new)\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u042d\u0442\u043e\u0442 \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0431\u0443\u0434\u0435\u0442 \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u044b\u0432\u0430\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043e\u0442\u0432\u0435\u0442\u0430 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0441\u0442\u0440\u043e\u043a\u0438 \u043d\u043e\u0432\u043e\u0433\u043e DataFrame \u0441 \u0438\u043c\u0435\u043d\u0435\u043c <strong>df_new<\/strong> , \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u043c\u043e\u0434\u0435\u043b\u044c \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0449\u0443\u044e \u0434\u043b\u044f \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439, \u043d\u0430\u0437\u044b\u0432\u0430\u0435\u043c\u0443\u044e <strong>model<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\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<h2> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043c\u0435\u0440. \u0421\u043e\u0437\u0434\u0430\u043d\u0438\u0435 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043e\u0432 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0432 Statsmodels.<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\u041f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0443 \u043d\u0430\u0441 \u0435\u0441\u0442\u044c \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 DataFrame pandas, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e\u0431 \u0443\u0447\u0435\u0431\u043d\u044b\u0445 \u0447\u0430\u0441\u0430\u0445, \u0441\u0434\u0430\u043d\u043d\u044b\u0445 \u043f\u043e\u0434\u0433\u043e\u0442\u043e\u0432\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u044d\u043a\u0437\u0430\u043c\u0435\u043d\u0430\u0445 \u0438 \u0438\u0442\u043e\u0433\u043e\u0432\u043e\u0439 \u043e\u0446\u0435\u043d\u043a\u0435, \u043f\u043e\u043b\u0443\u0447\u0435\u043d\u043d\u043e\u0439 \u0443\u0447\u0430\u0449\u0438\u043c\u0438\u0441\u044f \u043e\u043f\u0440\u0435\u0434\u0435\u043b\u0435\u043d\u043d\u043e\u0433\u043e \u043a\u043b\u0430\u0441\u0441\u0430:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">hours<\/span> ': [1, 2, 2, 4, 2, 1, 5, 4, 2, 4, 4, 3, 6],\n                   ' <span style=\"color: #ff0000;\">exams<\/span> ': [1, 3, 3, 5, 2, 2, 1, 1, 0, 3, 4, 3, 2],\n                   ' <span style=\"color: #ff0000;\">score<\/span> ': [76, 78, 85, 88, 72, 69, 94, 94, 88, 92, 90, 75, 96]})\n\n<span style=\"color: #008080;\">#view head of DataFrame\n<\/span>df. <span style=\"color: #3366ff;\">head<\/span> ()\n\n\thours exam score\n0 1 1 76\n1 2 3 78\n2 2 3 85\n3 4 5 88\n4 2 2 72<\/strong><\/pre>\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 \u0444\u0443\u043d\u043a\u0446\u0438\u044e <strong>OLS()<\/strong> \u043c\u043e\u0434\u0443\u043b\u044f statsmodels, \u0447\u0442\u043e\u0431\u044b \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u043e\u0432\u0430\u0442\u044c <a href=\"https:\/\/statorials.org\/ru\/\u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u0430\u044f-\u043b\u0438\u043d\u0435\u0438\u043d\u0430\u044f-\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f\/\" target=\"_blank\" rel=\"noopener\">\u043c\u043e\u0434\u0435\u043b\u0438 \u043c\u043d\u043e\u0436\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0439 \u043b\u0438\u043d\u0435\u0439\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438<\/a> , \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u00ab\u0447\u0430\u0441\u044b\u00bb \u0438 \u00ab\u044d\u043a\u0437\u0430\u043c\u0435\u043d\u044b\u00bb \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445-\u043f\u0440\u0435\u0434\u0441\u043a\u0430\u0437\u0430\u0442\u0435\u043b\u0435\u0439 \u0438 \u00ab\u043e\u0446\u0435\u043d\u043a\u0443\u00bb \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u0439 \u043e\u0442\u0432\u0435\u0442\u0430:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> statsmodels. <span style=\"color: #3366ff;\">api<\/span> <span style=\"color: #107d3f;\">as<\/span> sm\n\n<span style=\"color: #008080;\">#define predictor and response variables\n<\/span>y = df[' <span style=\"color: #ff0000;\">score<\/span> ']\nx = df[[' <span style=\"color: #ff0000;\">hours<\/span> ', ' <span style=\"color: #ff0000;\">exams<\/span> ']]\n\n<span style=\"color: #008080;\">#add constant to predictor variables\n<\/span>x = sm. <span style=\"color: #3366ff;\">add_constant<\/span> (x)\n\n<span style=\"color: #008080;\">#fit linear regression model\n<\/span>model = sm. <span style=\"color: #3366ff;\">OLS<\/span> (y,x). <span style=\"color: #3366ff;\">fit<\/span> ()\n\n<span style=\"color: #008080;\">#view model summary\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">model.summary<\/span> ())\n\n                            OLS Regression Results                            \n==================================================== ============================\nDept. Variable: R-squared score: 0.718\nModel: OLS Adj. R-squared: 0.661\nMethod: Least Squares F-statistic: 12.70\nDate: Fri, 05 Aug 2022 Prob (F-statistic): 0.00180\nTime: 09:24:38 Log-Likelihood: -38.618\nNo. Observations: 13 AIC: 83.24\nDf Residuals: 10 BIC: 84.93\nDf Model: 2                                         \nCovariance Type: non-robust                                         \n==================================================== ============================\n                 coef std err t P&gt;|t| [0.025 0.975]\n-------------------------------------------------- ----------------------------\nconst 71.4048 4.001 17.847 0.000 62.490 80.319\nhours 5.1275 1.018 5.038 0.001 2.860 7.395\nexams -1.2121 1.147 -1.057 0.315 -3.768 1.344\n==================================================== ============================\nOmnibus: 1,103 Durbin-Watson: 1,248\nProb(Omnibus): 0.576 Jarque-Bera (JB): 0.803\nSkew: -0.289 Prob(JB): 0.669\nKurtosis: 1.928 Cond. No. 11.7\n==================================================== ============================\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0418\u0437 \u0432\u044b\u0445\u043e\u0434\u043d\u043e\u0433\u043e \u0441\u0442\u043e\u043b\u0431\u0446\u0430 <strong>\u043a\u043e\u044d\u0444\u0444\u0438\u0446\u0438\u0435\u043d\u0442\u0430<\/strong> \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u043d\u0430\u043f\u0438\u0441\u0430\u0442\u044c \u043f\u043e\u0434\u043e\u0431\u0440\u0430\u043d\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u0443\u044e \u043c\u043e\u0434\u0435\u043b\u044c:<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0446\u0435\u043d\u043a\u0430 = 71,4048 + 5,1275 (\u0447\u0430\u0441\u044b) \u2013 1,2121 (\u044d\u043a\u0437\u0430\u043c\u0435\u043d\u044b)<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0422\u0435\u043f\u0435\u0440\u044c \u043f\u0440\u0435\u0434\u043f\u043e\u043b\u043e\u0436\u0438\u043c, \u0447\u0442\u043e \u043c\u044b \u0445\u043e\u0442\u0438\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u043e\u0434\u043e\u0431\u0440\u0430\u043d\u043d\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u0443\u044e \u043c\u043e\u0434\u0435\u043b\u044c \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u00ab\u043e\u0446\u0435\u043d\u043a\u0438\u00bb \u043f\u044f\u0442\u0438 \u043d\u043e\u0432\u044b\u0445 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u043e\u0432.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0412\u043e-\u043f\u0435\u0440\u0432\u044b\u0445, \u0434\u0430\u0432\u0430\u0439\u0442\u0435 \u0441\u043e\u0437\u0434\u0430\u0434\u0438\u043c DataFrame \u0434\u043b\u044f \u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u043f\u044f\u0442\u0438 \u043d\u043e\u0432\u044b\u0445 \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create new DataFrame\n<span style=\"color: #000000;\">df_new = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">hours<\/span> ': [1, 2, 2, 4, 5],\n                       ' <span style=\"color: #ff0000;\">exams<\/span> ': [1, 1, 4, 3, 3]})<\/span>\n\n#add column for constant\n<span style=\"color: #000000;\">df_new = sm. <span style=\"color: #3366ff;\">add_constant<\/span> (df_new)\n<\/span>\n#view new DataFrame\n<span style=\"color: #000000;\"><span style=\"color: #008000;\">print<\/span> (df_new)\n\n   const hours exams\n0 1.0 1 1\n1 1.0 2 1\n2 1.0 2 4\n3 1.0 4 3\n4 1.0 5 3<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><span style=\"color: #000000;\">\u0414\u0430\u043b\u0435\u0435 \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0444\u0443\u043d\u043a\u0446\u0438\u044e <strong>Predict()<\/strong> , \u0447\u0442\u043e\u0431\u044b \u0441\u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u00ab\u0431\u0430\u043b\u043b\u00bb \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0438\u0437 \u044d\u0442\u0438\u0445 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u043e\u0432, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u00ab\u0447\u0430\u0441\u044b\u00bb \u0438 \u00ab\u044d\u043a\u0437\u0430\u043c\u0435\u043d\u044b\u00bb \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u043f\u0435\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445-\u043f\u0440\u0435\u0434\u0438\u043a\u0442\u043e\u0440\u043e\u0432 \u0432 \u043d\u0430\u0448\u0435\u0439 \u043f\u043e\u0434\u043e\u0431\u0440\u0430\u043d\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438:<\/span><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#predict scores for the five new students<\/span>\nmodel. <span style=\"color: #3366ff;\">predict<\/span> (df_new)\n\n0 75.320242\n1 80.447734\n2 76.811480\n3 88.278550\n4 93.406042\ndtype:float64\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0412\u043e\u0442 \u043a\u0430\u043a \u0438\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\u041e\u0436\u0438\u0434\u0430\u0435\u0442\u0441\u044f, \u0447\u0442\u043e \u043f\u0435\u0440\u0432\u044b\u0439 \u0441\u0442\u0443\u0434\u0435\u043d\u0442 \u0432 \u043d\u043e\u0432\u043e\u043c DataFrame \u043d\u0430\u0431\u0435\u0440\u0435\u0442 <strong>75,32<\/strong> \u0431\u0430\u043b\u043b\u0430.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u041e\u0436\u0438\u0434\u0430\u0435\u0442\u0441\u044f, \u0447\u0442\u043e \u0432\u0442\u043e\u0440\u043e\u0439 \u0441\u0442\u0443\u0434\u0435\u043d\u0442 \u0432 \u043d\u043e\u0432\u043e\u043c DataFrame \u043d\u0430\u0431\u0435\u0440\u0435\u0442 <strong>80,45<\/strong> \u0431\u0430\u043b\u043b\u043e\u0432.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0418 \u0442\u0430\u043a \u0434\u0430\u043b\u0435\u0435.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0427\u0442\u043e\u0431\u044b \u043f\u043e\u043d\u044f\u0442\u044c, \u043a\u0430\u043a \u0431\u044b\u043b\u0438 \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u043d\u044b \u044d\u0442\u0438 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u044b, \u043d\u0430\u043c \u043d\u0443\u0436\u043d\u043e \u043e\u0431\u0440\u0430\u0442\u0438\u0442\u044c\u0441\u044f \u043a \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0435\u0439 \u043f\u043e\u0434\u043e\u0431\u0440\u0430\u043d\u043d\u043e\u0439 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438:<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0446\u0435\u043d\u043a\u0430 = 71,4048 + 5,1275 (\u0447\u0430\u0441\u044b) \u2013 1,2121 (\u044d\u043a\u0437\u0430\u043c\u0435\u043d\u044b)<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041f\u043e\u0434\u0441\u0442\u0430\u0432\u0438\u0432 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u00ab\u0447\u0430\u0441\u043e\u0432\u00bb \u0438 \u00ab\u044d\u043a\u0437\u0430\u043c\u0435\u043d\u043e\u0432\u00bb \u0434\u043b\u044f \u043d\u043e\u0432\u044b\u0445 \u0441\u0442\u0443\u0434\u0435\u043d\u0442\u043e\u0432, \u043c\u044b \u043c\u043e\u0436\u0435\u043c \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0438\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u044b\u0439 \u0431\u0430\u043b\u043b.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u043f\u0435\u0440\u0432\u044b\u0439 \u0441\u0442\u0443\u0434\u0435\u043d\u0442 \u0432 \u043d\u043e\u0432\u043e\u043c DataFrame \u0438\u043c\u0435\u043b \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 <strong>1<\/strong> \u0434\u043b\u044f \u0447\u0430\u0441\u043e\u0432 \u0438 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 <strong>1<\/strong> \u0434\u043b\u044f \u044d\u043a\u0437\u0430\u043c\u0435\u043d\u043e\u0432.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0422\u0430\u043a\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c, \u0438\u0445 \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u044b\u0439 \u0431\u0430\u043b\u043b \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u044b\u0432\u0430\u043b\u0441\u044f \u0441\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c:<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0446\u0435\u043d\u043a\u0430 = 71,4048 + 5,1275(1) \u2013 1,2121(1) = <strong>75,32<\/strong> .<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041e\u0446\u0435\u043d\u043a\u0430 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u0443\u0447\u0430\u0449\u0435\u0433\u043e\u0441\u044f \u0432 \u043d\u043e\u0432\u043e\u043c DataFrame \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u044b\u0432\u0430\u043b\u0430\u0441\u044c \u0442\u0430\u043a\u0438\u043c \u0436\u0435 \u043e\u0431\u0440\u0430\u0437\u043e\u043c.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\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<p> <span style=\"color: #000000;\">\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 \u0437\u0430\u0434\u0430\u0447\u0438 \u043d\u0430 Python:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u043b\u043e\u0433\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f-\u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044f-python\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0432\u044b\u043f\u043e\u043b\u043d\u0438\u0442\u044c \u043b\u043e\u0433\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0443\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u044e \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0430\u0438\u043a-\u0432-\u043f\u0438\u0442\u043e\u043d\u0435\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c AIC \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u043a\u0432\u0430\u0434\u0440\u0430\u0442-r-\u0432-python-\u0440\u0435\u0433\u0443\u043b\u0438\u0440\u0443\u0435\u0442\/\" target=\"_blank\" rel=\"noopener\">\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0441\u043a\u043e\u0440\u0440\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u044b\u0439 R-\u043a\u0432\u0430\u0434\u0440\u0430\u0442 \u0432 Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\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, \u0447\u0442\u043e\u0431\u044b \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u043f\u043e\u0434\u0433\u043e\u043d\u043a\u0443 \u043c\u043e\u0434\u0435\u043b\u0438 \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e \u043c\u043e\u0434\u0443\u043b\u044f statsmodels \u0432 Python \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u043e\u0432\u044b\u0445 \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439: model. predict (df_new) \u042d\u0442\u043e\u0442 \u043a\u043e\u043d\u043a\u0440\u0435\u0442\u043d\u044b\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0431\u0443\u0434\u0435\u0442 \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u044b\u0432\u0430\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u0435\u043c\u044b\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u044f \u043e\u0442\u0432\u0435\u0442\u0430 \u0434\u043b\u044f \u043a\u0430\u0436\u0434\u043e\u0439 \u0441\u0442\u0440\u043e\u043a\u0438 \u043d\u043e\u0432\u043e\u0433\u043e DataFrame \u0441 \u0438\u043c\u0435\u043d\u0435\u043c df_new , \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u043c\u043e\u0434\u0435\u043b\u044c \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u0438, \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0449\u0443\u044e \u0434\u043b\u044f \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439, \u043d\u0430\u0437\u044b\u0432\u0430\u0435\u043c\u0443\u044e model . \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, [&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-3570","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 \u0434\u0435\u043b\u0430\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u044b \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0432 Statsmodels \u2014 Statory<\/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 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0430\u043f\u043f\u0440\u043e\u043a\u0441\u0438\u043c\u0430\u0446\u0438\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u043e\u0432\u044b\u0445 \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439, \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\/\u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0435-\u043c\u043e\u0434\u0435\u043b\u0438-\u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u044e\u0442\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u041a\u0430\u043a \u0434\u0435\u043b\u0430\u0442\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u044b \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0432 Statsmodels \u2014 Statory\" \/>\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 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0430\u043f\u043f\u0440\u043e\u043a\u0441\u0438\u043c\u0430\u0446\u0438\u044e \u0440\u0435\u0433\u0440\u0435\u0441\u0441\u0438\u043e\u043d\u043d\u043e\u0439 \u043c\u043e\u0434\u0435\u043b\u0438 \u0441 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u0435\u043c \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u043e\u0432\u044b\u0445 \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439, \u043d\u0430 \u043f\u0440\u0438\u043c\u0435\u0440\u0435.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ru\/\u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0435-\u043c\u043e\u0434\u0435\u043b\u0438-\u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0438\u0440\u0443\u044e\u0442\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-16T18:41:15+00:00\" \/>\n<meta name=\"author\" content=\"\u0431\u0435\u043d\u0434\u0436\u0430\u043c\u0438\u043d \u0430\u043d\u0434\u0435\u0440\u0441\u043e\u043d\" \/>\n<meta name=\"twitter:card\" 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