{"id":966,"date":"2023-07-28T03:48:36","date_gmt":"2023-07-28T03:48:36","guid":{"rendered":"https:\/\/statorials.org\/ru\/%d1%8d%d0%ba%d1%81%d0%bf%d0%be%d0%bd%d0%b5%d0%bd%d1%86%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%b7%d1%8f%d1%89%d0%b0%d1%8f-%d1%81%d1%80%d0%b5%d0%b4%d0%bd%d1%8f%d1%8f\/"},"modified":"2023-07-28T03:48:36","modified_gmt":"2023-07-28T03:48:36","slug":"%d1%8d%d0%ba%d1%81%d0%bf%d0%be%d0%bd%d0%b5%d0%bd%d1%86%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%b7%d1%8f%d1%89%d0%b0%d1%8f-%d1%81%d1%80%d0%b5%d0%b4%d0%bd%d1%8f%d1%8f","status":"publish","type":"post","link":"https:\/\/statorials.org\/ru\/%d1%8d%d0%ba%d1%81%d0%bf%d0%be%d0%bd%d0%b5%d0%bd%d1%86%d0%b8%d0%b0%d0%bb%d1%8c%d0%bd%d0%b0%d1%8f-%d1%81%d0%ba%d0%be%d0%bb%d1%8c%d0%b7%d1%8f%d1%89%d0%b0%d1%8f-%d1%81%d1%80%d0%b5%d0%b4%d0%bd%d1%8f%d1%8f\/","title":{"rendered":"\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0443\u044e \u0441\u0440\u0435\u0434\u043d\u044e\u044e \u0432 pandas"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0412 \u0430\u043d\u0430\u043b\u0438\u0437\u0435 \u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445 \u0440\u044f\u0434\u043e\u0432 <strong>\u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435<\/strong> \u2014 \u044d\u0442\u043e \u043f\u0440\u043e\u0441\u0442\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0440\u044f\u0434\u0430 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u043f\u0435\u0440\u0438\u043e\u0434\u043e\u0432.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\u042d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0435 \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435<\/strong> \u2014 \u044d\u0442\u043e \u0442\u0438\u043f \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0433\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0433\u043e, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043f\u0440\u0438\u0434\u0430\u0435\u0442 \u0431\u043e\u043b\u044c\u0448\u0438\u0439 \u0432\u0435\u0441 \u043d\u0435\u0434\u0430\u0432\u043d\u0438\u043c \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u044f\u043c, \u0430 \u044d\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e \u043e\u043d\u043e \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u043e \u0431\u044b\u0441\u0442\u0440\u0435\u0435 \u0443\u043b\u0430\u0432\u043b\u0438\u0432\u0430\u0442\u044c \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0442\u0435\u043d\u0434\u0435\u043d\u0446\u0438\u0438.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\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 \u0432\u044b\u0447\u0438\u0441\u043b\u0438\u0442\u044c \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0435 \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0434\u043b\u044f \u0441\u0442\u043e\u043b\u0431\u0446\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 DataFrame pandas.<\/span><\/p>\n<h3> <strong>\u041f\u0440\u0438\u043c\u0435\u0440: \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u0430\u044f \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0430\u044f \u0441\u0440\u0435\u0434\u043d\u044f\u044f \u0432 \u043f\u0430\u043d\u0434\u0430\u0445<\/strong><\/h3>\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:<\/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<\/span>\ndf = pd.DataFrame({'period': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],\n                   'sales': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19]})\n\n<span style=\"color: #008080;\">#view DataFrame<\/span> \ndf\n\n        period sales\n0 1 25\n1 2 20\n2 3 14\n3 4 16\n4 5 27\n5 6 20\n6 7 12\n7 8 15\n8 9 14\n9 10 19\n<\/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 <a href=\"https:\/\/pandas.pydata.org\/pandas-docs\/stable\/reference\/api\/pandas.DataFrame.ewm.html\" target=\"_blank\" rel=\"noopener noreferrer\">pandas.DataFrame.ewm()<\/a> \u0434\u043b\u044f \u0440\u0430\u0441\u0447\u0435\u0442\u0430 \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e \u0432\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u043e\u0433\u043e \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0433\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0433\u043e \u0437\u0430 \u0440\u044f\u0434 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u043f\u0435\u0440\u0438\u043e\u0434\u043e\u0432.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0432\u043e\u0442 \u043a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e \u0432\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u0443\u044e \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0443\u044e \u0441\u0440\u0435\u0434\u043d\u044e\u044e, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044f \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0435 \u0447\u0435\u0442\u044b\u0440\u0435 \u043f\u0435\u0440\u0438\u043e\u0434\u0430:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create new column to hold 4-day exponentially weighted moving average<\/span>\ndf['4dayEWM'] = df['sales']. <span style=\"color: #3366ff;\">ewm<\/span> (span= <span style=\"color: #008000;\">4<\/span> , adjust= <span style=\"color: #008000;\">False<\/span> ). <span style=\"color: #3366ff;\">mean<\/span> ()\n\n<span style=\"color: #008080;\">#view DataFrame<\/span> \ndf\n\n        period sales 4dayEWM\n0 1 25 25.000000\n1 2 20 23.000000\n2 3 14 19.400000\n3 4 16 18.040000\n4 5 27 21.624000\n5 6 20 20.974400\n6 7 12 17.384640\n7 8 15 16.430784\n8 9 14 15.458470\n9 10 19 16.875082<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041c\u044b \u0442\u0430\u043a\u0436\u0435 \u043c\u043e\u0436\u0435\u043c \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0443 matplotlib \u0434\u043b\u044f \u0432\u0438\u0437\u0443\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u043f\u0440\u043e\u0434\u0430\u0436 \u043e\u0442\u043d\u043e\u0441\u0438\u0442\u0435\u043b\u044c\u043d\u043e 4-\u0434\u043d\u0435\u0432\u043d\u043e\u0433\u043e \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e \u0432\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u043e\u0433\u043e \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0433\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0433\u043e:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> matplotlib.pyplot <span style=\"color: #107d3f;\">as<\/span> plt\n\n<span style=\"color: #008080;\">#plot sales and 4-day exponentially weighted moving average<\/span>\nplt. <span style=\"color: #3366ff;\">plot<\/span> (df['sales'], label='Sales')\nplt. <span style=\"color: #3366ff;\">plot<\/span> (df['4dayEWM'], label='4-day EWM')\n\n<span style=\"color: #008080;\">#add legend to plot<\/span>\nplt. <span style=\"color: #3366ff;\">legend<\/span> (loc=2)\n<\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-10144 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/ewmpandas1.png\" alt=\"\u042d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e \u0432\u0437\u0432\u0435\u0448\u0435\u043d\u043d\u0430\u044f \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0430\u044f \u0441\u0440\u0435\u0434\u043d\u044f\u044f \u0432 \u043f\u0430\u043d\u0434\u0430\u0445\" width=\"464\" height=\"318\" srcset=\"\" sizes=\"auto, \"><\/p>\n<h3> <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><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ru\/\u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435-\u0441\u0440\u0435\u0434\u043d\u0435\u0435-\u043f\u0438\u0442\u043e\u043d\u0430\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0438\u0435 \u0441\u0440\u0435\u0434\u043d\u0438\u0435 \u0432 Python<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0441\u0440\u0435\u0434\u043d\u0438\u0438-\u0441\u0442\u043e\u043b\u0431\u0435\u0446-\u043f\u0430\u043d\u0434\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0441\u0442\u043e\u043b\u0431\u0446\u043e\u0432 \u0432 Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/ru\/\u0430\u0432\u0442\u043e\u043a\u043e\u0440\u0440\u0435\u043b\u044f\u0446\u0438\u043e\u043d\u043d\u044b\u0438-\u043f\u0438\u0442\u043e\u043d\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u041a\u0430\u043a \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u0430\u0432\u0442\u043e\u043a\u043e\u0440\u0440\u0435\u043b\u044f\u0446\u0438\u044e \u0432 Python<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0412 \u0430\u043d\u0430\u043b\u0438\u0437\u0435 \u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445 \u0440\u044f\u0434\u043e\u0432 \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u2014 \u044d\u0442\u043e \u043f\u0440\u043e\u0441\u0442\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0435 \u0440\u044f\u0434\u0430 \u043f\u0440\u0435\u0434\u044b\u0434\u0443\u0449\u0438\u0445 \u043f\u0435\u0440\u0438\u043e\u0434\u043e\u0432. \u042d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0435 \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u2014 \u044d\u0442\u043e \u0442\u0438\u043f \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0433\u043e \u0441\u0440\u0435\u0434\u043d\u0435\u0433\u043e, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043f\u0440\u0438\u0434\u0430\u0435\u0442 \u0431\u043e\u043b\u044c\u0448\u0438\u0439 \u0432\u0435\u0441 \u043d\u0435\u0434\u0430\u0432\u043d\u0438\u043c \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u044f\u043c, \u0430 \u044d\u0442\u043e \u043e\u0437\u043d\u0430\u0447\u0430\u0435\u0442, \u0447\u0442\u043e \u043e\u043d\u043e \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u043e \u0431\u044b\u0441\u0442\u0440\u0435\u0435 \u0443\u043b\u0430\u0432\u043b\u0438\u0432\u0430\u0442\u044c \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0442\u0435\u043d\u0434\u0435\u043d\u0446\u0438\u0438. \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 \u0432\u044b\u0447\u0438\u0441\u043b\u0438\u0442\u044c \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0435 \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0435\u0435 \u0441\u0440\u0435\u0434\u043d\u0435\u0435 \u0434\u043b\u044f \u0441\u0442\u043e\u043b\u0431\u0446\u0430 \u0437\u043d\u0430\u0447\u0435\u043d\u0438\u0439 \u0432 DataFrame pandas. \u041f\u0440\u0438\u043c\u0435\u0440: \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u0430\u044f [&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-966","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 \u0440\u0430\u0441\u0441\u0447\u0438\u0442\u0430\u0442\u044c \u044d\u043a\u0441\u043f\u043e\u043d\u0435\u043d\u0446\u0438\u0430\u043b\u044c\u043d\u0443\u044e \u0441\u043a\u043e\u043b\u044c\u0437\u044f\u0449\u0443\u044e \u0441\u0440\u0435\u0434\u043d\u044e\u044e \u0432 Pandas<\/title>\n<meta name=\"description\" content=\"\u041f\u0440\u043e\u0441\u0442\u043e\u0435 \u043e\u0431\u044a\u044f\u0441\u043d\u0435\u043d\u0438\u0435 \u0442\u043e\u0433\u043e, \u043a\u0430\u043a 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