La fonction lapply() permet d’appliquer une fonction \u00e0 chaque \u00e9l\u00e9ment d\u2019une liste.
Le premier argument est une liste sur laquelle on veut appliquer la fonction plac\u00e9e en deuxi\u00e8me argument (mean, sum, sd, function(x)\u2026).<\/p>\n
x <- list(a = 1:7, b = runif(n = 5, min = 10, max = 20), booleen = c(TRUE,FALSE,FALSE,TRUE))\n\ny<-lapply(x,mean)\n\n#de mani\u00e8re plus g\u00e9n\u00e9rale, cela \u00e9quivaut \u00e0 :\n\ny<-apply(x,function(x) mean(x))\n\n# on ajoute function(x) devant une les fonctions non-pr\u00e9d\u00e9finies dans R\n\nz<-sapply(x,mean)\n\n# la fonction sapply est \u00e9quivalente \u00e0 lapply
# mais lapply retourne une liste tandis que la fonction sapply retourne un vecteur num\u00e9rique, une matrice ou quand cela n'est pas possible, une liste.\n\n<\/code><\/pre>\n\u00a0<\/p>\n
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La fonction lapply() permet d’appliquer une fonction \u00e0 chaque \u00e9l\u00e9ment d\u2019une liste. Le premier argument est une liste sur laquelle on veut appliquer la fonction plac\u00e9e en deuxi\u00e8me argument (mean, sum, sd, function(x)\u2026). x <- list(a = 1:7, b = runif(n = 5, min = 10, max = 20), booleen = c(TRUE,FALSE,FALSE,TRUE)) y<-lapply(x,mean) #de mani\u00e8re plus g\u00e9n\u00e9rale, cela \u00e9quivaut \u00e0 : y<-apply(x,function(x) mean(x)) # on ajoute function(x) devant une les fonctions non-pr\u00e9d\u00e9finies dans R z<-sapply(x,mean) # la fonction sapply est \u00e9quivalente \u00e0 lapply # mais lapply retourne une liste tandis que la fonction sapply retourne un vecteur num\u00e9rique, une matrice ou quand cela n’est pasRead 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":[8,12,23],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-helene","4":"post-3034","6":"format-standard","7":"category-fonctions-utiles","8":"category-manipulation-de-donnees","9":"category-transformation-de-donnees"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-MW","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3034","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=3034"}],"version-history":[{"count":2,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3034\/revisions"}],"predecessor-version":[{"id":4254,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3034\/revisions\/4254"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=3034"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=3034"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=3034"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}