{"id":1106,"date":"2023-07-27T15:43:32","date_gmt":"2023-07-27T15:43:32","guid":{"rendered":"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/"},"modified":"2023-07-27T15:43:32","modified_gmt":"2023-07-27T15:43:32","slug":"dati-giornalieri-aggregati-in-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/","title":{"rendered":"Come aggregare i dati giornalieri in dati mensili e annuali in r"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">A volte potresti voler aggregare i dati giornalieri in dati settimanali, mensili o annuali in R.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Questo tutorial spiega come farlo facilmente utilizzando i pacchetti <strong>lubridate<\/strong> e <strong>dplyr<\/strong> .<\/span><\/p>\n<h2> <strong>Esempio: aggregare i dati giornalieri in R<\/strong><\/h2>\n<p> <span style=\"color: #000000;\">Supponiamo di avere il seguente frame di dati in R che mostra le vendite giornaliere di un articolo in un periodo di 100 giorni consecutivi:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>set.seed(1)\n<span style=\"color: #008080;\">\n#create data frame<\/span>\ndf &lt;- data.frame(date = <span style=\"color: #3366ff;\">as.Date<\/span> (\" <span style=\"color: #008000;\">2020-12-01<\/span> \") + 0:99,\n                 sales = <span style=\"color: #3366ff;\">runif<\/span> (100, 20, 50))\n\n<span style=\"color: #008080;\">#view first six rows<\/span>\nhead(df)\n\n        dirty date\n1 2020-12-01 27.96526\n2 2020-12-02 31.16372\n3 2020-12-03 37.18560\n4 2020-12-04 47.24623\n5 2020-12-05 26.05046\n6 2020-12-06 46.95169<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Per aggregare questi dati, possiamo utilizzare la funzione <a href=\"https:\/\/lubridate.tidyverse.org\/reference\/round_date.html\" target=\"_blank\" rel=\"noopener noreferrer\">floor_date()<\/a> del pacchetto <strong>lubridate<\/strong> che utilizza la seguente sintassi:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #3366ff;\">floor_date<\/span> (x, unit)<\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Oro:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>x:<\/strong> un vettore di oggetti data.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>unit:<\/strong> unit\u00e0 di tempo a cui arrotondare. Le opzioni includono secondi, minuti, ore, giorni, settimane, mesi, bimestrale, trimestri, semestri e anni.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">I seguenti frammenti di codice mostrano come utilizzare questa funzione con le funzioni <a href=\"https:\/\/dplyr.tidyverse.org\/reference\/group_by.html\" target=\"_blank\" rel=\"noopener noreferrer\">group_by()<\/a> e <a href=\"https:\/\/dplyr.tidyverse.org\/reference\/summarise.html\" target=\"_blank\" rel=\"noopener noreferrer\">summary()<\/a> nel pacchetto <strong>dplyr<\/strong> per trovare le vendite medie per settimana, mese e anno:<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>Vendite medie settimanali<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #993300;\">library<\/span> (lubridate)<\/span>\n<span style=\"color: #000000;\"><span style=\"color: #993300;\">library<\/span> (dplyr)<\/span>\n\n#round dates down to week<\/span>\ndf$week &lt;- <span style=\"color: #3366ff;\">floor_date<\/span> (df$date, \" <span style=\"color: #008000;\">week<\/span> \")\n\n<span style=\"color: #008000;\"><span style=\"color: #008080;\">#find average sales per week\n<span style=\"color: #000000;\">df %&gt;%\n  <span style=\"color: #3366ff;\">group_by<\/span> (week) %&gt;%\n  <span style=\"color: #3366ff;\">summarize<\/span> (mean = <span style=\"color: #993300;\">mean<\/span> (sales))<\/span><\/span>\n\n<span style=\"color: #000000;\"># A tibble: 15 x 2\n   week means\n        \n 1 2020-11-29 33.9\n 2 2020-12-06 35.3\n 3 2020-12-13 39.0\n 4 2020-12-20 34.4\n 5 2020-12-27 33.6\n 6 2021-01-03 35.9\n 7 2021-01-10 37.8\n 8 2021-01-17 36.8\n 9 2021-01-24 32.8\n10 2021-01-31 33.9\n11 2021-02-07 34.1\n12 2021-02-14 41.6\n13 2021-02-21 31.8\n14 2021-02-28 35.2\n15 2021-03-07 37.1<\/span><\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>Vendite medie al mese<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #008080;\"><span style=\"color: #993300;\">library<\/span> <span style=\"color: #000000;\">(lubridate)<\/span>\n<span style=\"color: #993300;\">library<\/span> <span style=\"color: #000000;\">(dplyr)<\/span>\n\n#round dates down to week<\/span>\ndf$month &lt;- <span style=\"color: #3366ff;\">floor_date<\/span> (df$date, \" <span style=\"color: #008000;\">month<\/span> \")\n\n<span style=\"color: #008000;\"><span style=\"color: #008080;\">#find average sales by month\n<span style=\"color: #000000;\">df %&gt;%<\/span>\n  <span style=\"color: #3366ff;\">group_by<\/span> <span style=\"color: #000000;\">(month) %&gt;%<\/span>\n  <span style=\"color: #3366ff;\">summarize<\/span> <span style=\"color: #000000;\">(mean =<\/span> <span style=\"color: #993300;\">mean<\/span> <span style=\"color: #000000;\">(sales))<\/span><\/span>\n\n<span style=\"color: #000000;\"># A tibble: 4 x 2\n  month mean\n       \n1 2020-12-01 35.3\n2 2021-01-01 35.6\n3 2021-02-01 35.2\n4 2021-03-01 37.0\n<\/span><\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>Vendite medie all&#8217;anno<\/strong><\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #000000;\"><span style=\"color: #008080;\"><span style=\"color: #993300;\">library<\/span> <span style=\"color: #000000;\">(lubridate)<\/span>\n<span style=\"color: #993300;\">library<\/span> <span style=\"color: #000000;\">(dplyr)<\/span>\n\n#round dates down to week<\/span>\ndf$year &lt;- <span style=\"color: #3366ff;\">floor_date<\/span> (df$date, \" <span style=\"color: #008000;\">year<\/span> \")\n\n<span style=\"color: #008000;\"><span style=\"color: #008080;\">#find average sales by month\n<span style=\"color: #000000;\">df %&gt;%<\/span>\n  <span style=\"color: #3366ff;\">group_by<\/span> <span style=\"color: #000000;\">(year) %&gt;%<\/span>\n  <span style=\"color: #3366ff;\">summarize<\/span> <span style=\"color: #000000;\">(mean =<\/span> <span style=\"color: #993300;\">mean<\/span> <span style=\"color: #000000;\">(sales))\n\n# A tibble: 2 x 2\n  year means\n       \n1 2020-01-01 35.3\n2 2021-01-01 35.7<\/span><\/span>\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Tieni presente che scegliamo di aggregare in base alla media, ma possiamo utilizzare qualsiasi statistica riepilogativa che desideriamo, come mediana, moda, massimo, minimo, ecc.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>Risorse addizionali<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">I seguenti tutorial spiegano come eseguire altre attivit\u00e0 comuni in R:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/it\/r-media-per-gruppo\/\" target=\"_blank\" rel=\"noopener noreferrer\">Come calcolare la media per gruppo in R<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/somma-cumulativa-in-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">Come calcolare le somme cumulative in R<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/tracciare-le-serie-temporali-in-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">Come tracciare una serie temporale in R<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A volte potresti voler aggregare i dati giornalieri in dati settimanali, mensili o annuali in R. Questo tutorial spiega come farlo facilmente utilizzando i pacchetti lubridate e dplyr . Esempio: aggregare i dati giornalieri in R Supponiamo di avere il seguente frame di dati in R che mostra le vendite giornaliere di un articolo in [&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":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Come aggregare i dati giornalieri in dati mensili e annuali in R<\/title>\n<meta name=\"description\" content=\"Questo tutorial spiega come aggregare i dati giornalieri in date settimanali, mensili e annuali in R, con esempi.\" \/>\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\/it\/dati-giornalieri-aggregati-in-r\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Come aggregare i dati giornalieri in dati mensili e annuali in R\" \/>\n<meta property=\"og:description\" content=\"Questo tutorial spiega come aggregare i dati giornalieri in date settimanali, mensili e annuali in R, con esempi.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-27T15:43:32+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin anderson\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minuti\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/\",\"url\":\"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/\",\"name\":\"Come aggregare i dati giornalieri in dati mensili e annuali in R\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/it\/#website\"},\"datePublished\":\"2023-07-27T15:43:32+00:00\",\"dateModified\":\"2023-07-27T15:43:32+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\"},\"description\":\"Questo tutorial spiega come aggregare i dati giornalieri in date settimanali, mensili e annuali in R, con esempi.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/#breadcrumb\"},\"inLanguage\":\"it-IT\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/it\/dati-giornalieri-aggregati-in-r\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Casa\",\"item\":\"https:\/\/statorials.org\/it\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Come aggregare i dati giornalieri in dati mensili e annuali in r\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/it\/#website\",\"url\":\"https:\/\/statorials.org\/it\/\",\"name\":\"Statorials\",\"description\":\"La tua guida all&#039;alfabetizzazione statistica!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/it\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"it-IT\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\",\"name\":\"Benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"it-IT\",\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/statorials.org\/it\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"https:\/\/statorials.org\/it\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin anderson\"},\"description\":\"Ciao, sono Benjamin, un professore di statistica in pensione diventato insegnante dedicato di Statorials. 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