La fonction recast()<\/b>, du package\u00a0reshape2<\/b>, permet d\u2019obtenir une table de contingence en une seule \u00e9tape \u00e0 partir d\u2019un data.frame. La fonction renvoie un data.frame.<\/p>\n
\u00a0<\/p>\n
library(reshape2) # On charge le package reshape2\n\n\u00a0\n\nairquality
#En 2 \u00e9tapes :\u00a0\n\naqm <- melt(airquality, id=c(\"Month\", \"Day\"), na.rm=TRUE)\n\n#On passe d\u2019un format \u201cWide\u201d \u00e0 un format \u201cLong\u201d\n\ndcast(aqm, Month ~ variable, mean, margins = TRUE)\n\n#On obtient une table de contingence contenant la moyenne de chaque variable en fonction du mois\n\n\u00a0
#En 1 seule \u00e9tape :\u00a0\n\nrecast(airquality, Month~ variable, id.var = 5:6, mean, na.rm=TRUE, margins=TRUE)\n\n#La fonction recast() permet d'obtenir une table de contingence en 1 seule \u00e9tape
<\/code><\/pre>\n\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"
La fonction recast(), du package\u00a0reshape2, permet d\u2019obtenir une table de contingence en une seule \u00e9tape \u00e0 partir d\u2019un data.frame. La fonction renvoie un data.frame. \u00a0 library(reshape2) # On charge le package reshape2 \u00a0 airquality#En 2 \u00e9tapes :\u00a0 aqm <- melt(airquality, id=c(\u00ab\u00a0Month\u00a0\u00bb, \u00ab\u00a0Day\u00a0\u00bb), na.rm=TRUE) #On passe d\u2019un format \u201cWide\u201d \u00e0 un format \u201cLong\u201d dcast(aqm, Month ~ variable, mean, margins = TRUE) #On obtient une table de contingence contenant la moyenne de chaque variable en fonction du mois \u00a0#En 1 seule \u00e9tape :\u00a0 recast(airquality, Month~ variable, id.var = 5:6, mean, na.rm=TRUE, margins=TRUE) #La fonction recast() permet d’obtenir une table de contingence en 1 seule \u00e9tape \u00a0Read More →<\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","rop_custom_images_group":[],"rop_custom_messages_group":[],"rop_publish_now":"initial","rop_publish_now_accounts":{"twitter_399453572_399453572":""},"rop_publish_now_history":[],"rop_publish_now_status":"pending","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[8,12],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-helene","4":"post-3137","6":"format-standard","7":"category-fonctions-utiles","8":"category-manipulation-de-donnees"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-OB","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3137","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/comments?post=3137"}],"version-history":[{"count":2,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3137\/revisions"}],"predecessor-version":[{"id":4278,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3137\/revisions\/4278"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=3137"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=3137"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=3137"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}