Les fonction colSums() <\/b>et rowSums()<\/b> permettent de calculer les sommes respectivement, sur les colonnes et les lignes d\u2019une matrice.<\/p>\n
Les fonction colMeans() <\/b>et rowMeans()<\/b> permettent de calculer les moyennes respectivement, sur les colonnes et les lignes d\u2019une matrice.<\/p>\n
\u00a0<\/p>\n
m <- matrix(data = c(12,15,14,13,16,18,15,5,14,11,10,17,4,6,17,16), nrow=4, ncol=4)\n\n#On cr\u00e9e une matrice \u00e0 4 colonnes et 4 lignes\n\n\u00a0\n\ncolSums(m)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #On fait la somme sur les colonnes\n\n[1] 54 54 52 43\n\n\u00a0\n\nrowSums(m)\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0#On fait la somme sur les lignes\n\n[1] 46 50 56 51\n\n\u00a0\n\ncolMeans(m) \u00a0\u00a0\u00a0\u00a0\u00a0#On fait la moyenne sur les colonnes\n\n[1] 13.50 13.50 13.00 10.75\n\n\u00a0\n\nrowMeans(m)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #On fait la moyenne sur les lignes\n\n[1] 11.50 12.50 14.00 12.75
<\/code><\/pre>\n\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"
Les fonction colSums() et rowSums() permettent de calculer les sommes respectivement, sur les colonnes et les lignes d\u2019une matrice. Les fonction colMeans() et rowMeans() permettent de calculer les moyennes respectivement, sur les colonnes et les lignes d\u2019une matrice. \u00a0 m <- matrix(data = c(12,15,14,13,16,18,15,5,14,11,10,17,4,6,17,16), nrow=4, ncol=4) #On cr\u00e9e une matrice \u00e0 4 colonnes et 4 lignes \u00a0 colSums(m)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #On fait la somme sur les colonnes [1] 54 54 52 43 \u00a0 rowSums(m)\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0#On fait la somme sur les lignes [1] 46 50 56 51 \u00a0 colMeans(m) \u00a0\u00a0\u00a0\u00a0\u00a0#On fait la moyenne sur les colonnes [1] 13.50 13.50 13.00 10.75 \u00a0 rowMeans(m)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 #On fait la moyenne surRead 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-3113","6":"format-standard","7":"category-fonctions-utiles","8":"category-manipulation-de-donnees"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-Od","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3113","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=3113"}],"version-history":[{"count":2,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3113\/revisions"}],"predecessor-version":[{"id":4268,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3113\/revisions\/4268"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=3113"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=3113"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=3113"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}