{"id":1325,"date":"2023-07-26T20:57:06","date_gmt":"2023-07-26T20:57:06","guid":{"rendered":"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/"},"modified":"2023-07-26T20:57:06","modified_gmt":"2023-07-26T20:57:06","slug":"zle-toczace-sie-pandy","status":"publish","type":"post","link":"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/","title":{"rendered":"Jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 w pandach"},"content":{"rendered":"

<\/p>\n

\n

\u015arednia ruchoma<\/strong> to po prostu \u015brednia liczby poprzednich okres\u00f3w w szeregu czasowym.<\/span><\/p>\n

Aby obliczy\u0107 \u015bredni\u0105 krocz\u0105c\u0105 jednej lub wi\u0119kszej liczby kolumn w ramce DataFrame pand, mo\u017cemy zastosowa\u0107 nast\u0119puj\u0105c\u0105 sk\u0142adni\u0119:<\/span><\/p>\n

 df[' column_name<\/span> ']. rolling<\/span> ( rolling_window<\/span> ). mean<\/span> ()\n<\/strong><\/pre>\n
 W tym samouczku przedstawiono kilka przyk\u0142ad\u00f3w praktycznego wykorzystania tej funkcji.<\/span><\/p>\n
 Przyk\u0142ad: obliczanie \u015bredniej ruchomej w pandach<\/strong><\/span><\/h3>\n
 Za\u0142\u00f3\u017cmy, \u017ce mamy nast\u0119puj\u0105c\u0105 ramk\u0119 DataFrame pand:<\/span><\/p>\n
 import<\/span> numpy as<\/span> np\nimport<\/span> pandas as<\/span> pd\n\n#make this example reproducible\n<\/span>n.p. random<\/span> . seeds<\/span> (0)\n\n#create dataset<\/span>\nperiod = np. arange<\/span> (1, 101, 1)\nleads = np. random<\/span> . uniform<\/span> (1, 20, 100)\nsales = 60 + 2*period + np. random<\/span> . normal<\/span> (loc=0, scale=.5*period, size=100)\ndf = pd. DataFrame<\/span> ({' period<\/span> ': period, ' leads<\/span> ': leads, ' sales<\/span> ': sales})\n\n#view first 10 rows\n<\/span>df. head<\/span> (10)\n\n   period leads sales\n0 1 11.427457 61.417425\n1 2 14.588598 64.900826\n2 3 12.452504 66.698494\n3 4 11.352780 64.927513\n4 5 9.049441 73.720630\n5 6 13.271988 77.687668\n6 7 9.314157 78.125728\n7 8 17.943687 75.280301\n8 9 19.309592 73.181613\n9 10 8.285389 85.272259\n<\/strong><\/pre>\n
 Mo\u017cemy u\u017cy\u0107 nast\u0119puj\u0105cej sk\u0142adni, aby utworzy\u0107 now\u0105 kolumn\u0119 zawieraj\u0105c\u0105 \u015bredni\u0105 ruchom\u0105 \u201esprzeda\u017cy\u201d z poprzednich 5 okres\u00f3w:<\/span><\/p>\n
 #find rolling mean of previous 5 sales periods\n<\/span>df[' rolling_sales_5<\/span> '] = df[' sales<\/span> ']. rolling<\/span> (5). mean<\/span> ()\n\n#view first 10 rows\n<\/span>df. head<\/span> (10)\n\n\tperiod leads sales rolling_sales_5\n0 1 11.427457 61.417425 NaN\n1 2 14.588598 64.900826 NaN\n2 3 12.452504 66.698494 NaN\n3 4 11.352780 64.927513 NaN\n4 5 9.049441 73.720630 66.332978\n5 6 13.271988 77.687668 69.587026\n6 7 9.314157 78.125728 72.232007\n7 8 17.943687 75.280301 73.948368\n8 9 19.309592 73.181613 75.599188\n9 10 8.285389 85.272259 77.909514\n<\/strong><\/pre>\n
 Mo\u017cemy r\u0119cznie sprawdzi\u0107, czy krocz\u0105ca \u015brednia sprzeda\u017cy wy\u015bwietlana dla okresu 5 jest \u015bredni\u0105 z poprzednich 5 okres\u00f3w:<\/span><\/p>\n
 \u015arednia krocz\u0105ca w okresie 5: (61,417+64,900+66,698+64,927+73,720)\/5 = 66,33<\/strong><\/span><\/p>\n
 Mo\u017cemy u\u017cy\u0107 podobnej sk\u0142adni do obliczenia \u015bredniej ruchomej wielu kolumn:<\/span><\/p>\n
 #find rolling mean of previous 5 leads periods \ndf[' rolling_leads_5<\/span> '] = df[' leads<\/span> ']. rolling<\/span> (5). mean<\/span> ()<\/span>\n\n#find rolling mean of previous 5 leads periods\n<\/span>df[' rolling_sales_5<\/span> '] = df[' sales<\/span> ']. rolling<\/span> (5). mean<\/span> ()\n\n#view first 10 rows\n<\/span>df. head<\/span> (10)\n\n\tperiod leads sales rolling_sales_5 rolling_leads_5\n0 1 11.427457 61.417425 NaN NaN\n1 2 14.588598 64.900826 NaN NaN\n2 3 12.452504 66.698494 NaN NaN\n3 4 11.352780 64.927513 NaN NaN\n4 5 9.049441 73.720630 66.332978 11.774156\n5 6 13.271988 77.687668 69.587026 12.143062\n6 7 9.314157 78.125728 72.232007 11.088174\n7 8 17.943687 75.280301 73.948368 12.186411\n8 9 19.309592 73.181613 75.599188 13.777773\n9 10 8.285389 85.272259 77.909514 13.624963\n<\/strong><\/pre>\n
 Mo\u017cemy r\u00f3wnie\u017c utworzy\u0107 szybki wykres liniowy za pomoc\u0105 Matplotlib do wizualizacji sprzeda\u017cy brutto w por\u00f3wnaniu ze \u015bredni\u0105 ruchom\u0105 sprzeda\u017cy:<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt<\/span>\nplt. plot<\/span> (df[' rolling_sales_5<\/span> '], label=' Rolling Mean<\/span> ')<\/span>\nplt. plot<\/span> (df[' sales<\/span> '], label=' Raw Data<\/span> ')<\/span>\nplt. legend<\/span> ()<\/span>\nplt. ylabel<\/span> (' Sales<\/span> ')<\/span>\nplt. xlabel<\/span> (' Period<\/span> ')<\/span>\nplt. show<\/span> ()<\/span>\n<\/span><\/strong><\/pre>\n
\"Wykre\u015blanie<\/p>\n
 Niebieska linia pokazuje 5-okresow\u0105 \u015bredni\u0105 ruchom\u0105 sprzeda\u017cy, a pomara\u0144czowa linia pokazuje surowe dane dotycz\u0105ce sprzeda\u017cy.<\/span><\/p>\n
 Dodatkowe zasoby<\/strong><\/h3>\n
 Poni\u017csze samouczki wyja\u015bniaj\u0105, jak wykonywa\u0107 inne typowe zadania w pandach:<\/span><\/p>\n
 Jak obliczy\u0107 korelacj\u0119 przesuwn\u0105 w pandach<\/a>
 Jak obliczy\u0107 \u015bredni\u0105 kolumn w Pandach<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\u015arednia ruchoma to po prostu \u015brednia liczby poprzednich okres\u00f3w w szeregu czasowym. Aby obliczy\u0107 \u015bredni\u0105 krocz\u0105c\u0105 jednej lub wi\u0119kszej liczby kolumn w ramce DataFrame pand, mo\u017cemy zastosowa\u0107 nast\u0119puj\u0105c\u0105 sk\u0142adni\u0119: df[’ column_name ’]. rolling ( rolling_window ). mean () W tym samouczku przedstawiono kilka przyk\u0142ad\u00f3w praktycznego wykorzystania tej funkcji. Przyk\u0142ad: obliczanie \u015bredniej ruchomej w pandach Za\u0142\u00f3\u017cmy, […]<\/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":[],"class_list":["post-1325","post","type-post","status-publish","format-standard","hentry","category-przewodnik"],"yoast_head":"\nJak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 w Pandach \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"W tym samouczku wyja\u015bniono, wraz z przyk\u0142adami, jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 dla jednej lub wi\u0119kszej liczby kolumn w ramce DataFrame pandy.\" \/>\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\/pl\/zle-toczace-sie-pandy\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 w Pandach \u2013 Statorials\" \/>\n<meta property=\"og:description\" content=\"W tym samouczku wyja\u015bniono, wraz z przyk\u0142adami, jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 dla jednej lub wi\u0119kszej liczby kolumn w ramce DataFrame pandy.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-26T20:57:06+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/roulantmeanpandas1.png\" \/>\n<meta name=\"author\" content=\"Benjamin Anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Napisane przez\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin Anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Szacowany czas czytania\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minuty\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/\",\"url\":\"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/\",\"name\":\"Jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 w Pandach \u2013 Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/pl\/#website\"},\"datePublished\":\"2023-07-26T20:57:06+00:00\",\"dateModified\":\"2023-07-26T20:57:06+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\"},\"description\":\"W tym samouczku wyja\u015bniono, wraz z przyk\u0142adami, jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 dla jednej lub wi\u0119kszej liczby kolumn w ramce DataFrame pandy.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/#breadcrumb\"},\"inLanguage\":\"pl-PL\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/pl\/zle-toczace-sie-pandy\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Dom\",\"item\":\"https:\/\/statorials.org\/pl\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Jak obliczy\u0107 \u015bredni\u0105 ruchom\u0105 w pandach\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/pl\/#website\",\"url\":\"https:\/\/statorials.org\/pl\/\",\"name\":\"Statorials\",\"description\":\"Tw\u00f3j przewodnik po kompetencjach statystycznych!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/pl\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"pl-PL\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\",\"name\":\"Benjamin Anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"pl-PL\",\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/pl\/wp-content\/uploads\/2023\/11\/Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/pl\/wp-content\/uploads\/2023\/11\/Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin Anderson\"},\"description\":\"Cze\u015b\u0107, jestem Benjamin i jestem emerytowanym profesorem statystyki, kt\u00f3ry zosta\u0142 oddanym nauczycielem Statorials. 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