{"id":3448,"date":"2017-07-20T10:52:04","date_gmt":"2017-07-20T09:52:04","guid":{"rendered":"https:\/\/abcdr.guyader.pro\/?p=3448"},"modified":"2018-04-23T14:28:11","modified_gmt":"2018-04-23T13:28:11","slug":"comment-modifier-les-colonnes-qui-repondent-a-une-condition-mutate_if","status":"publish","type":"post","link":"https:\/\/thinkr.fr\/abcdr\/comment-modifier-les-colonnes-qui-repondent-a-une-condition-mutate_if\/","title":{"rendered":"Comment modifier les colonnes qui r\u00e9pondent \u00e0 une condition ? mutate_if()"},"content":{"rendered":"<p>Parfois, on souhaite<strong> appliquer une fonction \u00e0 plusieurs colonnes de notre tableau, en fonction d&rsquo;une condition<\/strong>. Pour cela, direction <code>mutate_if()<\/code>, du package {dplyr}.<\/p>\n<p>Comme son nom l&rsquo;indique, <code>mutate_if<\/code> effectue une modification si la condition est remplie. Les arguments sont :<\/p>\n<li> Un tableau de donn\u00e9es <\/li>\n<li> La condition \u00e0 remplir (le test effectu\u00e9 qui devra renvoy\u00e9 TRUE) <\/li>\n<li> La transformation \u00e0 effectuer.<\/li>\n<p>Et pour comprendre par l&rsquo;exemple :<\/p>\n<pre><code>\n  library(dplyr)\n  data(\"iris\")\n  str(iris)\n  'data.frame': 150 obs. of  5 variables:\n $ Sepal.Length: num  5.1 4.9 4.7 4.6 ...\n $ Sepal.Width : num  3.5 3 3.2 3.1 3 ...\n $ Petal.Length: num  1.4 1.4 1.3 1.5 ...\n $ Petal.Width : num  0.2 0.2 0.2 0.2 ...\n $ Species     : Factor w\/ 3 levels   ...\n  new_iris &lt;- mutate_if(iris, is.numeric, as.factor)\n  str(new_iris)\n  &#039;data.frame&#039;:   150 obs. of  5 variables:\n $ Sepal.Length: Factor w\/ 35 levels ...\n $ Sepal.Width : Factor w\/ 23 levels ...\n $ Petal.Length: Factor w\/ 43 levels ...\n $ Petal.Width : Factor w\/ 22 levels ...\n $ Species     : Factor w\/ 3 levels  ...\n<\/code><\/pre>\n<p>\u00c0 noter : il est possible d&rsquo;int\u00e9grer ses propres fonctions de transformation. Par exemple, si l&rsquo;on veut les mesures d&rsquo;iris en millim\u00e8tres, plut\u00f4t qu&rsquo;en centim\u00e8tres.<\/p>\n<pre><code>\n  mutate_if(iris, is.numeric, function(x){x * 100})\n<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"<p>Parfois, on souhaite appliquer une fonction \u00e0 plusieurs colonnes de notre tableau, en fonction d&rsquo;une condition. Pour cela, direction mutate_if(), du package {dplyr}. Comme son nom l&rsquo;indique, mutate_if effectue une modification si la condition est remplie. Les arguments sont : Un tableau de donn\u00e9es La condition \u00e0 remplir (le test effectu\u00e9 qui devra renvoy\u00e9 TRUE) La transformation \u00e0 effectuer. Et pour comprendre par l&rsquo;exemple : library(dplyr) data(\u00ab\u00a0iris\u00a0\u00bb) str(iris) &lsquo;data.frame&rsquo;: 150 obs. of 5 variables: $ Sepal.Length: num 5.1 4.9 4.7 4.6 &#8230; $ Sepal.Width : num 3.5 3 3.2 3.1 3 &#8230; $ Petal.Length: num 1.4 1.4 1.3 1.5 &#8230; $ Petal.Width : num 0.2<a class=\"more-link\" href=\"https:\/\/thinkr.fr\/abcdr\/comment-modifier-les-colonnes-qui-repondent-a-une-condition-mutate_if\/\">Read More &rarr;<\/a><\/p>\n","protected":false},"author":4,"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":[12,22],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-colin","4":"post-3448","6":"format-standard","7":"category-manipulation-de-donnees","8":"category-tidyverse"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-TC","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3448","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\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/comments?post=3448"}],"version-history":[{"count":3,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3448\/revisions"}],"predecessor-version":[{"id":4459,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3448\/revisions\/4459"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=3448"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=3448"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=3448"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}