{"id":2580,"date":"2023-07-21T15:45:50","date_gmt":"2023-07-21T15:45:50","guid":{"rendered":"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/"},"modified":"2023-07-21T15:45:50","modified_gmt":"2023-07-21T15:45:50","slug":"boxplot-a-piu-colonne","status":"publish","type":"post","link":"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/","title":{"rendered":"Seaborn: come creare un boxplot a pi\u00f9 colonne"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u00c8 possibile utilizzare la seguente sintassi di base in Seaborn per creare un boxplot a pi\u00f9 colonne di un DataFrame panda:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>sns. <span style=\"color: #3366ff;\">boxplot<\/span> (x=' <span style=\"color: #ff0000;\">variable<\/span> ', y=' <span style=\"color: #ff0000;\">value<\/span> ', data=df)\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">L&#8217;esempio seguente mostra come utilizzare questa sintassi nella pratica.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Esempio: boxplot di pi\u00f9 colonne utilizzando Seaborn<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Supponiamo di avere il seguente DataFrame panda che mostra i punti segnati dai giocatori di tre diverse squadre di basket:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame<span style=\"color: #000000;\">\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">A<\/span> ': [5, 7, 7, 9, 12, 12],\n                   ' <span style=\"color: #ff0000;\">B<\/span> ': [8, 8, 9, 13, 15, 17],\n                   ' <span style=\"color: #ff0000;\">C<\/span> ': [1, 2, 2, 4, 5, 7]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n        A B C\n0 5 8 1\n1 7 8 2\n2 7 9 2\n3 9 13 4\n4 12 15 5\n5 12 17 7\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Supponiamo di voler creare tre box plot che mostrino la distribuzione dei punti segnati da ciascuna squadra.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Per creare diversi boxplot in seaborn, devi prima unire il DataFrame dei panda in un <a href=\"https:\/\/statorials.org\/it\/dati-lunghi-vs-dati-ampi\/\" target=\"_blank\" rel=\"noopener\">formato lungo<\/a> :<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#melt data frame into long format\n<\/span>df_melted = pd. <span style=\"color: #3366ff;\">melt<\/span> (df)\n\n<span style=\"color: #008080;\">#view first 10 rows of melted data frame\n<\/span>df_melted. <span style=\"color: #3366ff;\">head<\/span> ( <span style=\"color: #008000;\">10<\/span> )\n\n\tvariable value\n0 to 5\n1 to 7\n2 to 7\n3 to 9\n4 to 12\n5 to 12\n6 B 8\n7 B 8\n8 B 9\n9 B 13<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Ora possiamo creare pi\u00f9 boxplot utilizzando Seaborn:<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<span style=\"color: #008000;\">import<\/span> seaborn <span style=\"color: #008000;\">as<\/span> sns\n\n<span style=\"color: #008080;\">#create seaborn boxplots by group\n<\/span>sns. <span style=\"color: #3366ff;\">boxplot<\/span> (x=' <span style=\"color: #ff0000;\">variable<\/span> ', y=' <span style=\"color: #ff0000;\">value<\/span> ', data=df_melted)<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-22854 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mult11-1.jpg\" alt=\"Boxplot Seaborn di pi\u00f9 colonne\" width=\"535\" height=\"358\" srcset=\"\" sizes=\"\"><\/p>\n<p> <span style=\"color: #000000;\">L&#8217;asse x mostra le squadre e l&#8217;asse y mostra la distribuzione dei punti segnati.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Tieni presente che possiamo utilizzare la seguente sintassi anche per <a href=\"https:\/\/statorials.org\/it\/titolo-marino\/\" target=\"_blank\" rel=\"noopener\">aggiungere un titolo<\/a> e modificare <a href=\"https:\/\/statorials.org\/it\/etichette-dellasse-marino\/\" target=\"_blank\" rel=\"noopener\">le etichette degli assi<\/a> :<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<span style=\"color: #008000;\">import<\/span> seaborn <span style=\"color: #008000;\">as<\/span> sns\n\n<span style=\"color: #008080;\">#create seaborn boxplots by group\n<\/span>sns. <span style=\"color: #3366ff;\">boxplot<\/span> (x=' <span style=\"color: #ff0000;\">variable<\/span> ', y=' <span style=\"color: #ff0000;\">value<\/span> ', data=df_melted). <span style=\"color: #3366ff;\">set<\/span> (title=' <span style=\"color: #ff0000;\">Points by Team<\/span> ')\n\n<span style=\"color: #008080;\">#modify axis labels\n<\/span>plt. <span style=\"color: #3366ff;\">xlabel<\/span> ('Team')\nplt. <span style=\"color: #3366ff;\">ylabel<\/span> ('Points')<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-22855 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mult12-1.jpg\" alt=\"\" width=\"532\" height=\"372\" srcset=\"\" sizes=\"\"><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Risorse addizionali<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">I seguenti tutorial spiegano come creare altre visualizzazioni comuni in <a href=\"https:\/\/seaborn.pydata.org\/\" target=\"_blank\" rel=\"noopener\">Seaborn<\/a> :<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/it\/camembert-marino\/\" target=\"_blank\" rel=\"noopener\">Come creare un grafico a torta in Seaborn<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/mappa-delle-aree-marine\/\" target=\"_blank\" rel=\"noopener\">Come creare un grafico ad area in Seaborn<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/cronologia-dei-nati-sul-mare\/\" target=\"_blank\" rel=\"noopener\">Come creare un grafico di serie temporali in Seaborn<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u00c8 possibile utilizzare la seguente sintassi di base in Seaborn per creare un boxplot a pi\u00f9 colonne di un DataFrame panda: sns. boxplot (x=&#8217; variable &#8216;, y=&#8217; value &#8216;, data=df) L&#8217;esempio seguente mostra come utilizzare questa sintassi nella pratica. Esempio: boxplot di pi\u00f9 colonne utilizzando Seaborn Supponiamo di avere il seguente DataFrame panda che mostra [&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>Seaborn: Come creare un boxplot a pi\u00f9 colonne - Statorials<\/title>\n<meta name=\"description\" content=\"Questo tutorial spiega come creare un boxplot in Seaborn utilizzando pi\u00f9 colonne di un DataFrame Panda, incluso un esempio.\" \/>\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\/boxplot-a-piu-colonne\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Seaborn: Come creare un boxplot a pi\u00f9 colonne - Statorials\" \/>\n<meta property=\"og:description\" content=\"Questo tutorial spiega come creare un boxplot in Seaborn utilizzando pi\u00f9 colonne di un DataFrame Panda, incluso un esempio.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-21T15:45:50+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/mult11-1.jpg\" \/>\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\/boxplot-a-piu-colonne\/\",\"url\":\"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/\",\"name\":\"Seaborn: Come creare un boxplot a pi\u00f9 colonne - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/it\/#website\"},\"datePublished\":\"2023-07-21T15:45:50+00:00\",\"dateModified\":\"2023-07-21T15:45:50+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\"},\"description\":\"Questo tutorial spiega come creare un boxplot in Seaborn utilizzando pi\u00f9 colonne di un DataFrame Panda, incluso un esempio.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/#breadcrumb\"},\"inLanguage\":\"it-IT\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/it\/boxplot-a-piu-colonne\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Casa\",\"item\":\"https:\/\/statorials.org\/it\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Seaborn: come creare un boxplot a pi\u00f9 colonne\"}]},{\"@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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