{"id":2264,"date":"2023-07-23T00:47:34","date_gmt":"2023-07-23T00:47:34","guid":{"rendered":"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/"},"modified":"2023-07-23T00:47:34","modified_gmt":"2023-07-23T00:47:34","slug":"asse-0-asse-1-panda-pitone","status":"publish","type":"post","link":"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/","title":{"rendered":"La differenza tra asse=0 e asse=1 nei panda"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Molte funzioni in <a href=\"https:\/\/pandas.pydata.org\/\" target=\"_blank\" rel=\"noopener\">Panda<\/a> richiedono di specificare un asse lungo il quale applicare un determinato calcolo.<\/span><\/p>\n<p> <span style=\"color: #000000;\">In generale vale la seguente regola pratica:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>asse=0<\/strong> : applica il calcolo &#8220;per colonna&#8221;.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>asse=1<\/strong> : applica il calcolo \u201cper riga\u201d.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Gli esempi seguenti mostrano come utilizzare l&#8217;argomento <strong>dell&#8217;asse<\/strong> in diversi scenari con i seguenti DataFrame panda:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #ff0000;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">team<\/span> ': ['A', 'A', 'B', 'B', 'B', 'B', 'C', 'C'],\n                   ' <span style=\"color: #ff0000;\">points<\/span> ': [25, 12, 15, 14, 19, 23, 25, 29],\n                   ' <span style=\"color: #ff0000;\">assists<\/span> ': [5, 7, 7, 9, 12, 9, 9, 4],\n                   ' <span style=\"color: #ff0000;\">rebounds<\/span> ': [11, 8, 10, 6, 6, 5, 9, 12]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span>df\n\n\tteam points assists rebounds\n0 to 25 5 11\n1 to 12 7 8\n2 B 15 7 10\n3 B 14 9 6\n4 B 19 12 6\n5 B 23 9 5\n6 C 25 9 9\n7 C 29 4 12<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>Esempio 1: trovare la media lungo diversi assi<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Possiamo usare <strong>axis=0<\/strong> per trovare la media di ogni colonna nel DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find mean of each column\n<\/span>df. <span style=\"color: #3366ff;\">mean<\/span> (axis= <span style=\"color: #008000;\">0<\/span> )\n\npoints 20.250\nassists 7,750\nrebounds 8,375\ndtype:float64\n<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">L&#8217;output visualizza il valore medio di ciascuna colonna numerica nel DataFrame.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Tieni presente che i panda evitano automaticamente di calcolare la media della colonna &#8220;squadra&#8221; perch\u00e9 \u00e8 una colonna di personaggi.<\/span><\/p>\n<p> <span style=\"color: #000000;\">Possiamo anche usare <strong>axis=1<\/strong> per trovare la media di ogni riga nel DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find mean of each row\n<\/span>df. <span style=\"color: #3366ff;\">mean<\/span> (axis= <span style=\"color: #008000;\">1<\/span> )\n\n0 13.666667\n1 9.000000\n2 10.666667\n3 9.666667\n4 12.333333\n5 12.333333\n6 14.333333\n7 15.000000\ndtype:float64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Dal risultato possiamo vedere:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">Il valore medio della prima riga \u00e8 <strong>13.667<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Il valore medio nella seconda riga \u00e8 <strong>9000<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Il valore medio nella terza riga \u00e8 <strong>10.667<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">E cos\u00ec via.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Esempio 2: trovare la somma lungo assi diversi<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Possiamo usare <strong>axis=0<\/strong> per trovare la somma di colonne specifiche nel DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find sum of 'points' and 'assists' columns<\/span>\ndf[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ']]. <span style=\"color: #3366ff;\">sum<\/span> (axis= <span style=\"color: #008000;\">0<\/span> )\n\npoints 162\nassists 62\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Possiamo anche usare <strong>axis=1<\/strong> per trovare la somma di ogni riga nel DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find sum of each row\n<\/span>df. <span style=\"color: #3366ff;\">sum<\/span> (axis= <span style=\"color: #008000;\">1<\/span> )\n\n0 41\n1 27\n2 32\n3 29\n4 37\n5 37\n6 43\n7 45\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>Esempio 3: trovare Max lungo assi diversi<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">Possiamo usare <strong>axis=0<\/strong> per trovare il valore massimo di colonne specifiche nel DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find max of 'points', 'assists', and 'rebounds' columns\n<\/span>df[[' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">assists<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ']]. <span style=\"color: #3366ff;\">max<\/span> (axis= <span style=\"color: #008000;\">0<\/span> )\n\npoints 29\nassists 12\nrebounds 12\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Possiamo anche usare <strong>axis=1<\/strong> per trovare il valore massimo di ogni riga nel DataFrame:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008080;\">#find max of each row\n<\/span>df. <span style=\"color: #3366ff;\">max<\/span> (axis= <span style=\"color: #008000;\">1<\/span> )\n\n0 25\n1 12\n2 15\n3 14\n4 19\n5 23\n6 25\n7 29\ndtype: int64<\/span><\/span><\/strong><\/pre>\n<p> <span style=\"color: #000000;\">Dal risultato possiamo vedere:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">Il valore massimo nella prima riga \u00e8 <strong>25<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Il valore massimo nella seconda riga \u00e8 <strong>12<\/strong> .<\/span><\/li>\n<li> <span style=\"color: #000000;\">Il valore massimo nella terza riga \u00e8 <strong>15<\/strong> .<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">E cos\u00ec via.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>Risorse addizionali<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">I seguenti tutorial spiegano come eseguire altre operazioni comuni nei panda:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/it\/colonna-dei-panda-medi\/\" target=\"_blank\" rel=\"noopener\">Come calcolare la media delle colonne in Pandas<\/a><br \/> <a href=\"https:\/\/statorials.org\/it\/sono-colonne-di-panda\/\" target=\"_blank\" rel=\"noopener\">Come calcolare la somma delle colonne in Pandas<\/a><br \/> Come trovare il valore massimo delle colonne in Pandas<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Molte funzioni in Panda richiedono di specificare un asse lungo il quale applicare un determinato calcolo. In generale vale la seguente regola pratica: asse=0 : applica il calcolo &#8220;per colonna&#8221;. asse=1 : applica il calcolo \u201cper riga\u201d. Gli esempi seguenti mostrano come utilizzare l&#8217;argomento dell&#8217;asse in diversi scenari con i seguenti DataFrame panda: import pandas [&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>La differenza tra asse=0 e asse=1 in Pandas \u2013 Stology<\/title>\n<meta name=\"description\" content=\"Questo tutorial spiega la differenza tra asse=0 e asse=1 quando si utilizzano varie funzioni Panda.\" \/>\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\/asse-0-asse-1-panda-pitone\/\" \/>\n<meta property=\"og:locale\" content=\"it_IT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"La differenza tra asse=0 e asse=1 in Pandas \u2013 Stology\" \/>\n<meta property=\"og:description\" content=\"Questo tutorial spiega la differenza tra asse=0 e asse=1 quando si utilizzano varie funzioni Panda.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-23T00:47:34+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\/asse-0-asse-1-panda-pitone\/\",\"url\":\"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/\",\"name\":\"La differenza tra asse=0 e asse=1 in Pandas \u2013 Stology\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/it\/#website\"},\"datePublished\":\"2023-07-23T00:47:34+00:00\",\"dateModified\":\"2023-07-23T00:47:34+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/it\/#\/schema\/person\/0896f191fb9fb019f2cd8623112cb3ae\"},\"description\":\"Questo tutorial spiega la differenza tra asse=0 e asse=1 quando si utilizzano varie funzioni Panda.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/#breadcrumb\"},\"inLanguage\":\"it-IT\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/it\/asse-0-asse-1-panda-pitone\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Casa\",\"item\":\"https:\/\/statorials.org\/it\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"La differenza tra asse=0 e asse=1 nei panda\"}]},{\"@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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