{"id":2468,"date":"2023-07-22T03:17:44","date_gmt":"2023-07-22T03:17:44","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d1%82%d0%b5%d1%81%d1%82-%d0%bf%d1%80%d0%b8%d1%87%d0%b8%d0%bd%d0%bd%d0%be%d1%81%d1%82%d1%96-%d0%b3%d1%80%d0%b5%d0%b8%d0%bd%d0%b4%d0%b6%d0%b5%d1%80%d0%b0-%d0%b2-python\/"},"modified":"2023-07-22T03:17:44","modified_gmt":"2023-07-22T03:17:44","slug":"%d1%82%d0%b5%d1%81%d1%82-%d0%bf%d1%80%d0%b8%d1%87%d0%b8%d0%bd%d0%bd%d0%be%d1%81%d1%82%d1%96-%d0%b3%d1%80%d0%b5%d0%b8%d0%bd%d0%b4%d0%b6%d0%b5%d1%80%d0%b0-%d0%b2-python","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d1%82%d0%b5%d1%81%d1%82-%d0%bf%d1%80%d0%b8%d1%87%d0%b8%d0%bd%d0%bd%d0%be%d1%81%d1%82%d1%96-%d0%b3%d1%80%d0%b5%d0%b8%d0%bd%d0%b4%d0%b6%d0%b5%d1%80%d0%b0-%d0%b2-python\/","title":{"rendered":"\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0442\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0433\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432 python"},"content":{"rendered":"

<\/p>\n

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\u0422\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430<\/strong> \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454\u0442\u044c\u0441\u044f \u0434\u043b\u044f \u0432\u0438\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0442\u043e\u0433\u043e, \u0447\u0438 \u043a\u043e\u0440\u0438\u0441\u043d\u0438\u0439 \u043e\u0434\u0438\u043d \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f \u0456\u043d\u0448\u043e\u0433\u043e.<\/span><\/p>\n

\u0426\u0435\u0439 \u0442\u0435\u0441\u0442 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0430\u043a\u0456 \u043d\u0443\u043b\u044c\u043e\u0432\u0456 \u0442\u0430 \u0430\u043b\u044c\u0442\u0435\u0440\u043d\u0430\u0442\u0438\u0432\u043d\u0456 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0438:<\/span><\/p>\n

\u041d\u0443\u043b\u044c\u043e\u0432\u0430 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0430 (H 0<\/sub> ):<\/strong> \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 x<\/em> \u043d\u0435 \u0432\u0438\u043a\u043b\u0438\u043a\u0430\u0454 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 y<\/em> \u0434\u043e \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430<\/span><\/p>\n

\u0410\u043b\u044c\u0442\u0435\u0440\u043d\u0430\u0442\u0438\u0432\u043d\u0430 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0430 ( HA<\/sub> ):<\/strong> \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 x<\/em> \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0490\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432\u0438\u043a\u043b\u0438\u043a\u0430\u0454 y<\/em><\/span><\/p>\n

\u0422\u0435\u0440\u043c\u0456\u043d \u00ab\u043f\u0440\u0438\u0447\u0438\u043d\u0438 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430\u00bb \u043e\u0437\u043d\u0430\u0447\u0430\u0454, \u0449\u043e \u0437\u043d\u0430\u043d\u043d\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0447\u0430\u0441\u043e\u0432\u043e\u0433\u043e \u0440\u044f\u0434\u0443 x<\/em> \u0437 \u043f\u0435\u0432\u043d\u0438\u043c \u043b\u0430\u0433\u043e\u043c \u0454 \u043a\u043e\u0440\u0438\u0441\u043d\u0438\u043c \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0447\u0430\u0441\u043e\u0432\u043e\u0433\u043e \u0440\u044f\u0434\u0443 y<\/em> \u043d\u0430 \u043f\u0456\u0437\u043d\u0456\u0448\u0438\u0439 \u043f\u0435\u0440\u0456\u043e\u0434.<\/span><\/p>\n

\u0426\u0435\u0439 \u0442\u0435\u0441\u0442 \u0441\u0442\u0432\u043e\u0440\u044e\u0454 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0443 F-\u043a\u0440\u0438\u0442\u0435\u0440\u0456\u044e \u0437 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u043d\u0438\u043c p-\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f\u043c<\/a> . \u042f\u043a\u0449\u043e p-\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043d\u0438\u0436\u0447\u0435<\/span> \u043f\u0435\u0432\u043d\u043e\u0433\u043e \u0440\u0456\u0432\u043d\u044f \u0437\u043d\u0430\u0447\u0443\u0449\u043e\u0441\u0442\u0456 (\u0442\u043e\u0431\u0442\u043e \u03b1 = 0,05), \u0442\u043e\u0434\u0456 \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0456\u0434\u0445\u0438\u043b\u0438\u0442\u0438 \u043d\u0443\u043b\u044c\u043e\u0432\u0443 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0443 \u0442\u0430 \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0432\u0438\u0441\u043d\u043e\u0432\u043e\u043a, \u0449\u043e \u0443 \u043d\u0430\u0441 \u0454 \u0434\u043e\u0441\u0442\u0430\u0442\u043d\u044c\u043e \u0434\u043e\u043a\u0430\u0437\u0456\u0432, \u0449\u043e\u0431 \u0441\u0442\u0432\u0435\u0440\u0434\u0436\u0443\u0432\u0430\u0442\u0438, \u0449\u043e \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 x<\/em> \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440 \u0432\u0438\u043a\u043b\u0438\u043a\u0430\u0454 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 y.<\/span><\/p>\n

\u041c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e grangercausalitytests()<\/a> \u0456\u0437 \u043f\u0430\u043a\u0435\u0442\u0443 statsmodels \u0434\u043b\u044f \u0432\u0438\u043a\u043e\u043d\u0430\u043d\u043d\u044f \u0442\u0435\u0441\u0442\u0443 Granger-Causality \u0443 Python:<\/span><\/p>\n

 from<\/span> statsmodels. tsa<\/span> . stattools<\/span> import<\/span> grangercausalitytests\n\n#perform Granger-Causality test<\/span>\ngrangercausalitytests(df[[' column1<\/span> ', ' column2<\/span> ']], maxlag=[ 3<\/span> ])\n<\/strong><\/pre>\n
 \u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e maxlag<\/strong> \u0432\u0438\u0437\u043d\u0430\u0447\u0430\u0454 \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u043b\u0430\u0433\u0456\u0432 \u0434\u043b\u044f \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u0432 \u043f\u0435\u0440\u0448\u043e\u043c\u0443 \u0447\u0430\u0441\u043e\u0432\u043e\u043c\u0443 \u0440\u044f\u0434\u0456.<\/span><\/span><\/p>\n
 \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043f\u043e\u043a\u0440\u043e\u043a\u043e\u0432\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \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
 \u041a\u0440\u043e\u043a 1. \u0417\u0430\u0432\u0430\u043d\u0442\u0430\u0436\u0442\u0435 \u0434\u0430\u043d\u0456<\/strong><\/span><\/h3>\n
 \u0414\u043b\u044f \u0446\u044c\u043e\u0433\u043e \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0443 \u043c\u0438 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0454\u043c\u043e \u043d\u0430\u0431\u0456\u0440 \u0434\u0430\u043d\u0438\u0445, \u0449\u043e \u043c\u0456\u0441\u0442\u0438\u0442\u044c \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043a\u0456\u043b\u044c\u043a\u043e\u0441\u0442\u0456 \u0432\u0438\u0433\u043e\u0442\u043e\u0432\u043b\u0435\u043d\u0438\u0445 \u044f\u0454\u0446\u044c, \u0430 \u0442\u0430\u043a\u043e\u0436 \u043a\u0456\u043b\u044c\u043a\u043e\u0441\u0442\u0456 \u043a\u0443\u0440\u0435\u0439 \u0443 \u0421\u043f\u043e\u043b\u0443\u0447\u0435\u043d\u0438\u0445 \u0428\u0442\u0430\u0442\u0430\u0445 \u0437 1930 \u043f\u043e 1983 \u0440\u0456\u043a:<\/span><\/p>\n
 import<\/span> pandas as<\/span> pd\n\n#define URL where dataset is located\n<\/span>url = \"https:\/\/raw.githubusercontent.com\/Statology\/Miscellaneous\/main\/chicken_egg.txt\"\n\n#read in dataset as pandas DataFrame\n<\/span>df = pd. read_csv<\/span> (url, sep=\" \")\n\n#view first five rows of DataFrame\n<\/span>df. head<\/span> ()\n\n\tyear chicken egg\n0 1930 468491 3581\n1 1931 449743 3532\n2 1932 436815 3327\n3 1933 444523 3255\n4 1934 433937 3156\n<\/strong><\/pre>\n
 \u041a\u0440\u043e\u043a 2: \u0412\u0438\u043a\u043e\u043d\u0430\u0439\u0442\u0435 \u0442\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430<\/strong><\/span><\/h3>\n
 \u0414\u0430\u043b\u0456 \u043c\u0438 \u0441\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u0454\u043c\u043e\u0441\u044f \u0444\u0443\u043d\u043a\u0446\u0456\u0454\u044e grangercausalitytests<\/strong> ()<\/strong> , \u0449\u043e\u0431 \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0442\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430, \u0449\u043e\u0431 \u043f\u043e\u0431\u0430\u0447\u0438\u0442\u0438, \u0447\u0438 \u0454 \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u0437\u0440\u043e\u0431\u043b\u0435\u043d\u0438\u0445 \u044f\u0454\u0446\u044c \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u043d\u043e\u044e \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044e \u043a\u0443\u0440\u0435\u0439 \u0443 \u043c\u0430\u0439\u0431\u0443\u0442\u043d\u044c\u043e\u043c\u0443. \u041c\u0438 \u043f\u0440\u043e\u0432\u0435\u0434\u0435\u043c\u043e \u0442\u0435\u0441\u0442 \u0456\u0437 \u0442\u0440\u044c\u043e\u043c\u0430 \u0437\u043c\u0456\u0449\u0435\u043d\u043d\u044f\u043c\u0438:<\/span><\/p>\n
 from<\/span> statsmodels. tsa<\/span> . stattools<\/span> import<\/span> grangercausalitytests<\/span>\n\n#perform Granger-Causality test<\/span>\ngrangercausalitytests(df[[' chicken<\/span> ', ' egg<\/span> ']], maxlag=[ 3<\/span> ])\n\nGranger Causality\nnumber of lags (no zero) 3\nssr based F test: F=5.4050, p=0.0030, df_denom=44, df_num=3\nssr based chi2 test: chi2=18.7946, p=0.0003, df=3\nlikelihood ratio test: chi2=16.0003, p=0.0011, df=3\nparameter F test: F=5.4050, p=0.0030, df_denom=44, df_num=3<\/strong><\/pre>\n
 \u0421\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u043d\u0438\u043a F-\u043a\u0440\u0438\u0442\u0435\u0440\u0456\u044e \u0434\u043e\u0440\u0456\u0432\u043d\u044e\u0454 5,405<\/strong> , \u0430 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f p \u2014 0,0030<\/strong> .<\/span><\/p>\n
 \u041e\u0441\u043a\u0456\u043b\u044c\u043a\u0438 p-\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043c\u0435\u043d\u0448\u0435 0,05, \u043c\u0438 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0456\u0434\u0445\u0438\u043b\u0438\u0442\u0438 \u043d\u0443\u043b\u044c\u043e\u0432\u0443 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0443 \u0442\u0435\u0441\u0442\u0443 \u0442\u0430 \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0432\u0438\u0441\u043d\u043e\u0432\u043e\u043a, \u0449\u043e \u0437\u043d\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u044f\u0454\u0446\u044c \u043a\u043e\u0440\u0438\u0441\u043d\u043e \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f \u043c\u0430\u0439\u0431\u0443\u0442\u043d\u044c\u043e\u0457 \u043a\u0456\u043b\u044c\u043a\u043e\u0441\u0442\u0456 \u043a\u0443\u0440\u0435\u0439.<\/span><\/p>\n
 \u041a\u0440\u043e\u043a 3: \u0412\u0438\u043a\u043e\u043d\u0430\u0439\u0442\u0435 \u043f\u0435\u0440\u0435\u0432\u0456\u0440\u043a\u0443 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0443 \u0437\u0432\u043e\u0440\u043e\u0442\u043d\u043e\u043c\u0443 \u043f\u043e\u0440\u044f\u0434\u043a\u0443<\/strong><\/span><\/h3>\n
 \u041d\u0435\u0437\u0432\u0430\u0436\u0430\u044e\u0447\u0438 \u043d\u0430 \u0442\u0435, \u0449\u043e \u043c\u0438 \u0432\u0456\u0434\u043a\u0438\u043d\u0443\u043b\u0438 \u043d\u0443\u043b\u044c\u043e\u0432\u0443 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0443 \u0442\u0435\u0441\u0442\u0443, \u043d\u0430\u0441\u043f\u0440\u0430\u0432\u0434\u0456 \u0446\u0456\u043b\u043a\u043e\u043c \u043c\u043e\u0436\u043b\u0438\u0432\u043e, \u0449\u043e \u043c\u043e\u0436\u0435 \u0441\u0442\u0430\u0442\u0438\u0441\u044f \u0432\u0438\u043f\u0430\u0434\u043e\u043a \u0437\u0432\u043e\u0440\u043e\u0442\u043d\u043e\u0457 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456. \u0406\u043d\u0448\u0438\u043c\u0438 \u0441\u043b\u043e\u0432\u0430\u043c\u0438, \u043c\u043e\u0436\u043b\u0438\u0432\u043e, \u0449\u043e \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u043a\u0443\u0440\u0435\u0439 \u0432\u0438\u043a\u043b\u0438\u043a\u0430\u0454 \u0437\u043c\u0456\u043d\u0443 \u043a\u0456\u043b\u044c\u043a\u043e\u0441\u0442\u0456 \u044f\u0454\u0446\u044c.<\/span><\/p>\n
 \u0429\u043e\u0431 \u0432\u0438\u043a\u043b\u044e\u0447\u0438\u0442\u0438 \u0442\u0430\u043a\u0443 \u043c\u043e\u0436\u043b\u0438\u0432\u0456\u0441\u0442\u044c, \u043d\u0430\u043c \u043f\u043e\u0442\u0440\u0456\u0431\u043d\u043e \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0442\u0435\u0441\u0442 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430-\u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0443 \u0437\u0432\u043e\u0440\u043e\u0442\u043d\u043e\u043c\u0443 \u043f\u043e\u0440\u044f\u0434\u043a\u0443, \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u044e\u0447\u0438 \u043a\u0443\u0440\u0435\u0439 \u044f\u043a \u0437\u043c\u0456\u043d\u043d\u0443-\u043f\u0440\u043e\u0432\u0456\u0441\u043d\u0438\u043a \u0456 \u044f\u0439\u0446\u044f \u044f\u043a \u0437\u043c\u0456\u043d\u043d\u0443 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u0456<\/a> :<\/span><\/p>\n
 from<\/span> statsmodels. tsa<\/span> . stattools<\/span> import<\/span> grangercausalitytests<\/span>\n\n#perform Granger-Causality test<\/span>\ngrangercausalitytests(df[[' egg<\/span> ', ' chicken<\/span> ']], maxlag=[ 3<\/span> ])\n\nGranger Causality\nnumber of lags (no zero) 3\nssr based F test: F=0.5916, p=0.6238, df_denom=44, df_num=3\nssr based chi2 test: chi2=2.0572, p=0.5606, df=3\nlikelihood ratio test: chi2=2.0168, p=0.5689, df=3\nparameter F test: F=0.5916, p=0.6238, df_denom=44, df_num=3\n<\/strong><\/pre>\n
 \u0421\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u0438\u0439 \u043f\u043e\u043a\u0430\u0437\u043d\u0438\u043a F-\u043a\u0440\u0438\u0442\u0435\u0440\u0456\u044e \u0434\u043e\u0440\u0456\u0432\u043d\u044e\u0454 0,5916<\/strong> , \u0430 \u0432\u0456\u0434\u043f\u043e\u0432\u0456\u0434\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f p \u2014 0,6238<\/strong> .<\/span><\/p>\n
 \u041e\u0441\u043a\u0456\u043b\u044c\u043a\u0438 p-\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u043d\u0435 \u043c\u0435\u043d\u0448\u0435 0,05, \u043c\u0438 \u043d\u0435 \u043c\u043e\u0436\u0435\u043c\u043e \u0432\u0456\u0434\u0445\u0438\u043b\u0438\u0442\u0438 \u043d\u0443\u043b\u044c\u043e\u0432\u0443 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0443. \u0406\u043d\u0448\u0438\u043c\u0438 \u0441\u043b\u043e\u0432\u0430\u043c\u0438, \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u043a\u0443\u0440\u0435\u0439 \u043d\u0435 \u043f\u0435\u0440\u0435\u0434\u0431\u0430\u0447\u0430\u0454 \u043c\u0430\u0439\u0431\u0443\u0442\u043d\u044c\u043e\u0457 \u043a\u0456\u043b\u044c\u043a\u043e\u0441\u0442\u0456 \u044f\u0454\u0446\u044c.<\/span><\/p>\n
 \u0422\u0430\u043a\u0438\u043c \u0447\u0438\u043d\u043e\u043c, \u043c\u043e\u0436\u043d\u0430 \u0437\u0440\u043e\u0431\u0438\u0442\u0438 \u0432\u0438\u0441\u043d\u043e\u0432\u043e\u043a, \u0449\u043e \u0437\u043d\u0430\u0442\u0438 \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u0442\u044c \u044f\u0454\u0446\u044c \u043a\u043e\u0440\u0438\u0441\u043d\u043e \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f \u043c\u0430\u0439\u0431\u0443\u0442\u043d\u044c\u043e\u0457 \u043a\u0456\u043b\u044c\u043a\u043e\u0441\u0442\u0456 \u043a\u0443\u0440\u0435\u0439.<\/span><\/p>\n
 \u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h3>\n
 \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 \u043f\u043e\u0448\u0438\u0440\u0435\u043d\u0456 \u0437\u0430\u0432\u0434\u0430\u043d\u043d\u044f \u0437 \u0447\u0430\u0441\u043e\u0432\u0438\u043c\u0438 \u0440\u044f\u0434\u0430\u043c\u0438 \u0432 Python:<\/span><\/p>\n
 \u042f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0433\u0440\u0430\u0444\u0456\u043a \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u0443 Seaborn<\/a>
 \u042f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0433\u0440\u0430\u0444\u0456\u043a \u0447\u0430\u0441\u043e\u0432\u0438\u0445 \u0440\u044f\u0434\u0456\u0432 \u0443 Matplotlib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u0422\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454\u0442\u044c\u0441\u044f \u0434\u043b\u044f \u0432\u0438\u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f \u0442\u043e\u0433\u043e, \u0447\u0438 \u043a\u043e\u0440\u0438\u0441\u043d\u0438\u0439 \u043e\u0434\u0438\u043d \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0434\u043b\u044f \u043f\u0440\u043e\u0433\u043d\u043e\u0437\u0443\u0432\u0430\u043d\u043d\u044f \u0456\u043d\u0448\u043e\u0433\u043e. \u0426\u0435\u0439 \u0442\u0435\u0441\u0442 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0430\u043a\u0456 \u043d\u0443\u043b\u044c\u043e\u0432\u0456 \u0442\u0430 \u0430\u043b\u044c\u0442\u0435\u0440\u043d\u0430\u0442\u0438\u0432\u043d\u0456 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0438: \u041d\u0443\u043b\u044c\u043e\u0432\u0430 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0430 (H 0 ): \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 x \u043d\u0435 \u0432\u0438\u043a\u043b\u0438\u043a\u0430\u0454 \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 y \u0434\u043e \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0410\u043b\u044c\u0442\u0435\u0440\u043d\u0430\u0442\u0438\u0432\u043d\u0430 \u0433\u0456\u043f\u043e\u0442\u0435\u0437\u0430 ( HA ): \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 x \u0447\u0430\u0441\u043e\u0432\u0438\u0439 \u0440\u044f\u0434 \u0490\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432\u0438\u043a\u043b\u0438\u043a\u0430\u0454 y \u0422\u0435\u0440\u043c\u0456\u043d \u00ab\u043f\u0440\u0438\u0447\u0438\u043d\u0438 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430\u00bb \u043e\u0437\u043d\u0430\u0447\u0430\u0454, […]<\/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":"\n\u042f\u043a \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0442\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432 Python - 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 \u0432\u0438\u043a\u043e\u043d\u0430\u0442\u0438 \u0442\u0435\u0441\u0442 \u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432 Python, \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0447\u0438 \u043f\u043e\u0432\u043d\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434.\" 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\u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456 \u0413\u0440\u0435\u0439\u043d\u0434\u0436\u0435\u0440\u0430 \u0432 Python, \u0432\u043a\u043b\u044e\u0447\u0430\u044e\u0447\u0438 \u043f\u043e\u0432\u043d\u0438\u0439 \u043f\u0440\u0438\u043a\u043b\u0430\u0434.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/uk\/\u0442\u0435\u0441\u0442-\u043f\u0440\u0438\u0447\u0438\u043d\u043d\u043e\u0441\u0442\u0456-\u0433\u0440\u0435\u0438\u043d\u0434\u0436\u0435\u0440\u0430-\u0432-python\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-22T03:17:44+00:00\" \/>\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\" 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 \u041f\u043e\u0432\u2019\u044f\u0437\u0430\u043d\u0435:<\/strong><\/span> \u042f\u043a \u0447\u0438\u0442\u0430\u0442\u0438 \u0444\u0430\u0439\u043b\u0438 CSV \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e Pandas<\/a><\/p>\n