{"id":2898,"date":"2023-07-20T04:47:53","date_gmt":"2023-07-20T04:47:53","guid":{"rendered":"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/"},"modified":"2023-07-20T04:47:53","modified_gmt":"2023-07-20T04:47:53","slug":"blad-r-w-lm-fitx-na-nan-inf-w-y","status":"publish","type":"post","link":"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/","title":{"rendered":"Jak naprawi\u0107: b\u0142\u0105d w lm.fit(x, y, offset = offset, \u2026): na\/nan\/inf w \u201ey\u201d"},"content":{"rendered":"

<\/p>\n

\n

B\u0142\u0105d, kt\u00f3ry mo\u017cesz napotka\u0107 podczas korzystania z R, to:<\/span><\/p>\n

 Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...): \n  NA\/NaN\/Inf in 'y'\n<\/strong><\/span><\/pre>\n
 Ten b\u0142\u0105d wyst\u0119puje, gdy pr\u00f3bujesz u\u017cy\u0107 funkcji lm()<\/a> w celu dopasowania modelu regresji liniowej w j\u0119zyku R, ale zmienna predykcyjna lub zmienna odpowiedzi zawiera warto\u015bci NaN<\/strong> lub Inf<\/strong> .<\/span><\/p>\n
 Poni\u017cszy przyk\u0142ad pokazuje, jak w praktyce skorygowa\u0107 ten b\u0142\u0105d.<\/span><\/p>\n
 Jak odtworzy\u0107 b\u0142\u0105d<\/strong><\/span><\/h3>\n
 Za\u0142\u00f3\u017cmy, \u017ce mamy w R nast\u0119puj\u0105c\u0105 ramk\u0119 danych zawieraj\u0105c\u0105 informacje o rozegranych minutach i punktach zdobytych przez r\u00f3\u017cnych koszykarzy:<\/span><\/p>\n
 #create data frame with some NA, NaN, Inf values\n<\/span>df <- data. frame<\/span> (minutes=c(4, NA, 28, 12, 30, 21, 14),\n                 dots=c(12, NaN, 30, Inf, 43, 25, 17))\n\n#view data frame\n<\/span>df\n\n  minutes points\n1 4 12\n2 NA NaN\n3 28 30\n4 12 Lower\n5 30 43\n6 21 25\n7 14 17\n<\/span><\/span><\/strong><\/pre>\n
 Nale\u017cy pami\u0119ta\u0107, \u017ce ramka danych zawiera warto\u015bci NaN<\/strong> i Inf<\/strong> .<\/span><\/span><\/p>\n
 Za\u0142\u00f3\u017cmy teraz, \u017ce pr\u00f3bujemy dopasowa\u0107 model regresji liniowej, u\u017cywaj\u0105c \u201eminut\u201d jako zmiennej predykcyjnej i \u201epunkt\u00f3w\u201d jako zmiennej odpowiedzi:<\/span><\/span><\/p>\n
 #attempt to fit regression model\n<\/span>lm(points ~ minutes, data=df)\n\nError in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...): \n  NA\/NaN\/Inf in 'y'\n<\/span><\/span><\/strong><\/pre>\n
 Otrzymujemy b\u0142\u0105d, poniewa\u017c w ramce danych znajduj\u0105 si\u0119 warto\u015bci NaN<\/strong> i Inf<\/strong> .<\/span><\/p>\n
 Jak naprawi\u0107 b\u0142\u0105d<\/strong><\/span><\/h3>\n
 Nale\u017cy zaznaczy\u0107, \u017ce warto\u015bci NA<\/strong> w ramce danych nie stanowi\u0105 problemu. W rzeczywisto\u015bci R po prostu ignoruje warto\u015bci NA<\/strong> podczas dopasowywania modelu regresji liniowej.<\/span><\/p>\n
 Prawdziwym problemem s\u0105 warto\u015bci NaN<\/strong> i Inf<\/strong> .<\/span><\/p>\n
 Naj\u0142atwiejszym sposobem rozwi\u0105zania tego problemu jest zast\u0105pienie warto\u015bci NaN<\/strong> i Inf<\/strong> warto\u015bciami NA<\/strong> :<\/span><\/p>\n
 #Replace NaN & Inf with NA\n<\/span>df[is. na<\/span> (df) | df==\" Inf<\/span> \"] = NA\n\n#view updated data frame\n<\/span>df\n\n  minutes points\n1 4 12\n2 NA NA\n3 28 30\n4 12 NA\n5 30 43\n6 21 25\n7 14 17<\/span><\/span><\/strong><\/pre>\n
 Mo\u017cemy teraz dostosowa\u0107 model regresji:<\/span><\/span><\/p>\n
 #fit regression model<\/span>\nlm(points ~ minutes, data=df)\n\nCall:\nlm(formula = points ~ minutes, data = df)\n\nCoefficients:\n(Intercept) minutes  \n      5,062 1,048<\/span><\/span><\/strong><\/pre>\n
 Pami\u0119taj, \u017ce nie otrzymujemy \u017cadnych b\u0142\u0119d\u00f3w, poniewa\u017c zast\u0105pili\u015bmy warto\u015bci NaN<\/strong> i Inf<\/strong> w ramce danych.<\/span><\/p>\n
 Dodatkowe zasoby<\/strong><\/span><\/h3>\n
 Poni\u017csze samouczki wyja\u015bniaj\u0105, jak naprawi\u0107 inne typowe b\u0142\u0119dy w R:<\/span><\/p>\n
 Jak naprawi\u0107 w R: nieoczekiwana sta\u0142a \u0142a\u0144cuchowa<\/a>
 Jak naprawi\u0107 w R: Nieprawid\u0142owa formu\u0142a szablonu w ExtractVars
 Jak naprawi\u0107 w R: argument nie jest ani numeryczny, ani logiczny: return na<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
B\u0142\u0105d, kt\u00f3ry mo\u017cesz napotka\u0107 podczas korzystania z R, to: Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, …): NA\/NaN\/Inf in 'y’ Ten b\u0142\u0105d wyst\u0119puje, gdy pr\u00f3bujesz u\u017cy\u0107 funkcji lm() w celu dopasowania modelu regresji liniowej w j\u0119zyku R, ale zmienna predykcyjna lub zmienna odpowiedzi zawiera warto\u015bci NaN lub Inf . Poni\u017cszy przyk\u0142ad pokazuje, […]<\/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-2898","post","type-post","status-publish","format-standard","hentry","category-przewodnik"],"yoast_head":"\nJak naprawi\u0107: b\u0142\u0105d w lm.fit(x, y, offset = offset, ...): na\/nan\/inf w 'y' - Statorials<\/title>\n<meta name=\"description\" content=\"W tym samouczku wyja\u015bniono, jak naprawi\u0107 nast\u0119puj\u0105cy b\u0142\u0105d w R: b\u0142\u0105d w lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...): na\/nan\/inf w 'y'.\" \/>\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\/blad-r-w-lm-fitx-na-nan-inf-w-y\/\" \/>\n<meta property=\"og:locale\" content=\"pl_PL\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Jak naprawi\u0107: b\u0142\u0105d w lm.fit(x, y, offset = offset, ...): na\/nan\/inf w 'y' - Statorials\" \/>\n<meta property=\"og:description\" content=\"W tym samouczku wyja\u015bniono, jak naprawi\u0107 nast\u0119puj\u0105cy b\u0142\u0105d w R: b\u0142\u0105d w lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...): na\/nan\/inf w 'y'.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-20T04:47:53+00:00\" \/>\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\/blad-r-w-lm-fitx-na-nan-inf-w-y\/\",\"url\":\"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/\",\"name\":\"Jak naprawi\u0107: b\u0142\u0105d w lm.fit(x, y, offset = offset, ...): na\/nan\/inf w 'y' - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/pl\/#website\"},\"datePublished\":\"2023-07-20T04:47:53+00:00\",\"dateModified\":\"2023-07-20T04:47:53+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/pl\/#\/schema\/person\/6484727a4612df3e69f016c3129c6965\"},\"description\":\"W tym samouczku wyja\u015bniono, jak naprawi\u0107 nast\u0119puj\u0105cy b\u0142\u0105d w R: b\u0142\u0105d w lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...): na\/nan\/inf w 'y'.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/#breadcrumb\"},\"inLanguage\":\"pl-PL\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/pl\/blad-r-w-lm-fitx-na-nan-inf-w-y\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Dom\",\"item\":\"https:\/\/statorials.org\/pl\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Jak naprawi\u0107: b\u0142\u0105d w lm.fit(x, y, offset = offset, \u2026): na\/nan\/inf w \u201ey\u201d\"}]},{\"@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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 Wynik pokazuje wsp\u00f3\u0142czynniki<\/a> modelu regresji.<\/span><\/p>\n