{"id":516,"date":"2023-07-29T15:53:45","date_gmt":"2023-07-29T15:53:45","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8-mutate-%e5%9c%a8-r-%e4%b8%ad%e5%88%9b%e5%bb%ba%e6%96%b0%e5%8f%98%e9%87%8f\/"},"modified":"2023-07-29T15:53:45","modified_gmt":"2023-07-29T15:53:45","slug":"%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8-mutate-%e5%9c%a8-r-%e4%b8%ad%e5%88%9b%e5%bb%ba%e6%96%b0%e5%8f%98%e9%87%8f","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%a6%82%e4%bd%95%e4%bd%bf%e7%94%a8-mutate-%e5%9c%a8-r-%e4%b8%ad%e5%88%9b%e5%bb%ba%e6%96%b0%e5%8f%98%e9%87%8f\/","title":{"rendered":"\u5982\u4f55\u4f7f\u7528 mutate \u5728 r \u4e2d\u521b\u5efa\u65b0\u53d8\u91cf"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684<strong>mutate()<\/strong>\u51fd\u6570\u5411\u6570\u636e\u6846\u6dfb\u52a0\u65b0\u53d8\u91cf\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5728 R \u4e2d\u6dfb\u52a0\u65b0\u53d8\u91cf<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b<strong>dplyr<\/strong>\u5e93\u51fd\u6570\u53ef\u7528\u4e8e\u5411\u6570\u636e\u6846\u6dfb\u52a0\u65b0\u53d8\u91cf\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>mutate()<\/strong> \u2013 \u5c06\u65b0\u53d8\u91cf\u6dfb\u52a0\u5230\u6570\u636e\u6846\u4e2d\uff0c\u540c\u65f6\u4fdd\u7559\u73b0\u6709\u53d8\u91cf<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>transmute()<\/strong> \u2013 \u5c06\u65b0\u53d8\u91cf\u6dfb\u52a0\u5230\u6570\u636e\u6846\u4e2d\u5e76\u5220\u9664\u73b0\u6709\u53d8\u91cf<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>mutate_all()<\/strong> \u2013 \u7acb\u5373\u4fee\u6539\u6570\u636e\u6846\u4e2d\u7684\u6240\u6709\u53d8\u91cf<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>mutate_at()<\/strong> \u2013 \u6309\u540d\u79f0\u4fee\u6539\u7279\u5b9a\u53d8\u91cf<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>mutate_if()<\/strong> \u2013 \u4fee\u6539\u6ee1\u8db3\u7279\u5b9a\u6761\u4ef6\u7684\u6240\u6709\u53d8\u91cf<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u53d8\u5f02\uff08\uff09<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\"><strong>mutate()<\/strong>\u51fd\u6570\u5c06\u65b0\u53d8\u91cf\u6dfb\u52a0\u5230\u6570\u636e\u6846\u4e2d\uff0c\u540c\u65f6\u4fdd\u7559\u6240\u6709\u73b0\u6709\u53d8\u91cf\u3002<\/span> <span style=\"color: #000000;\">mutate() \u7684\u57fa\u672c\u8bed\u6cd5\u662f\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong>data &lt;- <span style=\"color: #800080;\">mutate<\/span> (new_variable = existing_variable\/3)<\/strong><\/pre>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>data\uff1a<\/strong>\u8981\u4e3a\u5176\u5206\u914d\u65b0\u53d8\u91cf\u7684\u65b0\u6570\u636e\u5757<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>new_variable\uff1a<\/strong>\u65b0\u53d8\u91cf\u7684\u540d\u79f0<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u73b0\u6709\u53d8\u91cf\uff1a<\/strong>\u6570\u636e\u6846\u4e2d\u8981\u5bf9\u5176\u6267\u884c\u64cd\u4f5c\u4ee5\u521b\u5efa\u65b0\u53d8\u91cf\u7684\u73b0\u6709\u53d8\u91cf<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4f8b\u5982\uff0c\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u5c06\u65b0\u7684<em>root_sepal_width<\/em>\u53d8\u91cf\u6dfb\u52a0\u5230\u5d4c\u5165\u7684<em>iris<\/em>\u6570\u636e\u96c6\u4e2d\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data frame as the first six lines of the <em>iris<\/em> dataset<\/span>\ndata &lt;- head(iris)\n\n<span style=\"color: #008080;\">#view data<\/span>\ndata\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n#1 5.1 3.5 1.4 0.2 setosa\n#2 4.9 3.0 1.4 0.2 setosa\n#3 4.7 3.2 1.3 0.2 setosa\n#4 4.6 3.1 1.5 0.2 setosa\n#5 5.0 3.6 1.4 0.2 setosa\n#6 5.4 3.9 1.7 0.4 setosa\n\n<span style=\"color: #008080;\">#load <em>dplyr<\/em> library<\/span>\n<span style=\"color: #000000;\">library(dplyr)<\/span>\n\n<span style=\"color: #008080;\">#define new column <em>root_sepal_width<\/em> as the square root of the <em>Sepal.Width<\/em> variable<\/span>\ndata %&gt;% <span style=\"color: #800080;\">mutate<\/span> (root_sepal_width = sqrt(Sepal.Width))\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Species root_sepal_width\n#1 5.1 3.5 1.4 0.2 setosa 1.870829\n#2 4.9 3.0 1.4 0.2 setosa 1.732051\n#3 4.7 3.2 1.3 0.2 setosa 1.788854\n#4 4.6 3.1 1.5 0.2 setosa 1.760682\n#5 5.0 3.6 1.4 0.2 setosa 1.897367\n#6 5.4 3.9 1.7 0.4 setosa 1.974842\n<\/strong><\/pre>\n<h2><span style=\"color: #000000;\"><strong>\u8f6c\u53d8\uff08\uff09<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\"><strong>transmute()<\/strong>\u51fd\u6570\u5c06\u65b0\u53d8\u91cf\u6dfb\u52a0\u5230\u6570\u636e\u5e27\u5e76\u5220\u9664\u73b0\u6709\u53d8\u91cf\u3002\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u5411\u6570\u636e\u96c6\u6dfb\u52a0\u4e24\u4e2a\u65b0\u53d8\u91cf\u5e76\u5220\u9664\u6240\u6709\u73b0\u6709\u53d8\u91cf\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data frame as the first six lines of the <em>iris<\/em> dataset\n<\/span>data &lt;- head(iris)\n\n<span style=\"color: #008080;\">#viewdata\n<\/span>data\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n#1 5.1 3.5 1.4 0.2 setosa\n#2 4.9 3.0 1.4 0.2 setosa\n#3 4.7 3.2 1.3 0.2 setosa\n#4 4.6 3.1 1.5 0.2 setosa\n#5 5.0 3.6 1.4 0.2 setosa\n#6 5.4 3.9 1.7 0.4 setosa\n\n<span style=\"color: #008080;\">#define two new variables and remove all existing variables\n<\/span>data %&gt;% <span style=\"color: #800080;\">transmute<\/span> (root_sepal_width = sqrt(Sepal.Width),\n                   root_petal_width = sqrt(Petal.Width))\n\n# root_sepal_width root_petal_width\n#1 1.870829 0.4472136\n#2 1.732051 0.4472136\n#3 1.788854 0.4472136\n#4 1.760682 0.4472136\n#5 1.897367 0.4472136\n#6 1.974842 0.6324555\n<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>mutate_all()<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\"><strong>mutate_all()<\/strong>\u51fd\u6570\u4e00\u6b21\u4fee\u6539\u6570\u636e\u6846\u4e2d\u7684\u6240\u6709\u53d8\u91cf\uff0c\u5141\u8bb8\u60a8\u4f7f\u7528<strong>funs()<\/strong>\u51fd\u6570\u5bf9\u6240\u6709\u53d8\u91cf\u6267\u884c\u7279\u5b9a\u51fd\u6570\u3002\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u4f7f\u7528<strong>mutate_all()<\/strong>\u5c06\u6570\u636e\u6846\u4e2d\u7684\u6240\u6709\u5217\u9664\u4ee5 10\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define new data frame as the first six rows of <em>iris<\/em> without the <em>Species<\/em> variable<\/span>\ndata2 &lt;- head(iris) %&gt;% select(-Species)\n\n<span style=\"color: #008080;\">#view the new data frame<\/span>\ndata2\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width\n#1 5.1 3.5 1.4 0.2\n#2 4.9 3.0 1.4 0.2\n#3 4.7 3.2 1.3 0.2\n#4 4.6 3.1 1.5 0.2\n#5 5.0 3.6 1.4 0.2\n#6 5.4 3.9 1.7 0.4\n\n<span style=\"color: #008080;\">#divide all variables in the data frame by 10\n<\/span>data2 %&gt;% <span style=\"color: #800080;\">mutate_all<\/span> (funs(.\/10))\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width\n#1 0.51 0.35 0.14 0.02\n#2 0.49 0.30 0.14 0.02\n#3 0.47 0.32 0.13 0.02\n#4 0.46 0.31 0.15 0.02\n#5 0.50 0.36 0.14 0.02\n#6 0.54 0.39 0.17 0.04\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u53ef\u4ee5\u901a\u8fc7\u6307\u5b9a\u9644\u52a0\u5230\u65e7\u53d8\u91cf\u540d\u79f0\u7684\u65b0\u540d\u79f0\u6765\u5c06\u5176\u4ed6\u53d8\u91cf\u6dfb\u52a0\u5230\u6570\u636e\u6846\u4e2d\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong>data2 %&gt;% <span style=\"color: #800080;\">mutate_all<\/span> (funs(mod = .\/10))\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Sepal.Length_mod\n#1 5.1 3.5 1.4 0.2 0.51\n#2 4.9 3.0 1.4 0.2 0.49\n#3 4.7 3.2 1.3 0.2 0.47\n#4 4.6 3.1 1.5 0.2 0.46\n#5 5.0 3.6 1.4 0.2 0.50\n#6 5.4 3.9 1.7 0.4 0.54\n# Sepal.Width_mod Petal.Length_mod Petal.Width_mod\n#1 0.35 0.14 0.02\n#2 0.30 0.14 0.02\n#3 0.32 0.13 0.02\n#4 0.31 0.15 0.02\n#5 0.36 0.14 0.02\n#6 0.39 0.17 0.04\n<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>mutate_at()<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\"><strong>mutate_at()<\/strong>\u51fd\u6570\u6309\u540d\u79f0\u4fee\u6539\u7279\u5b9a\u53d8\u91cf\u3002\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u4f7f\u7528<strong>mutate_at()<\/strong>\u5c06\u4e24\u4e2a\u7279\u5b9a\u53d8\u91cf\u9664\u4ee5 10\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong>data2 %&gt;% <span style=\"color: #800080;\">mutate_at<\/span> (c(\"Sepal.Length\", \"Sepal.Width\"), funs(mod = .\/10))\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Sepal.Length_mod\n#1 5.1 3.5 1.4 0.2 0.51\n#2 4.9 3.0 1.4 0.2 0.49\n#3 4.7 3.2 1.3 0.2 0.47\n#4 4.6 3.1 1.5 0.2 0.46\n#5 5.0 3.6 1.4 0.2 0.50\n#6 5.4 3.9 1.7 0.4 0.54\n# Sepal.Width_mod\n#1 0.35\n#2 0.30\n#3 0.32\n#4 0.31\n#5 0.36\n#6 0.39<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>mutate_if()<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\"><strong>mutate_if()<\/strong>\u51fd\u6570\u4fee\u6539\u6ee1\u8db3\u7279\u5b9a\u6761\u4ef6\u7684\u6240\u6709\u53d8\u91cf\u3002\u4ee5\u4e0b\u4ee3\u7801\u8bf4\u660e\u4e86\u5982\u4f55\u4f7f\u7528<strong>mutate_if()<\/strong>\u51fd\u6570\u5c06\u4efb\u4f55\u7c7b\u578b\u4e3a<em>Factor<\/em>\u7684\u53d8\u91cf\u8f6c\u6362\u4e3a\u7c7b\u578b\u4e3a<em>character<\/em> \uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#find variable type of each variable in a data frame<\/span>\ndata &lt;- head(iris)\nsapply(data, class)\n\n#Sepal.Length Sepal.Width Petal.Length Petal.Width Species \n# \"numeric\" \"numeric\" \"numeric\" \"numeric\" \"factor\" \n\n<span style=\"color: #008080;\">#convert any variable of type <em>factor<\/em> to type <em>character<\/em><\/span>\nnew_data &lt;- data %&gt;% mutate_if(is.factor, as.character)\nsapply(new_data, class)\n\n#Sepal.Length Sepal.Width Petal.Length Petal.Width Species \n# \"numeric\" \"numeric\" \"numeric\" \"numeric\" \"character\"<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u4f7f\u7528<strong>mutate_if()<\/strong>\u51fd\u6570\u5c06\u6240\u6709<em>\u6570\u503c<\/em>\u53d8\u91cf\u56db\u820d\u4e94\u5165\u5230\u5c0f\u6570\u70b9\u540e\u4e00\u4f4d\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data as first six rows of <em>iris<\/em> dataset<\/span>\ndata &lt;- head(iris)\n\n<span style=\"color: #008080;\">#view data<\/span>\ndata\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n#1 5.1 3.5 1.4 0.2 setosa\n#2 4.9 3.0 1.4 0.2 setosa\n#3 4.7 3.2 1.3 0.2 setosa\n#4 4.6 3.1 1.5 0.2 setosa\n#5 5.0 3.6 1.4 0.2 setosa\n#6 5.4 3.9 1.7 0.4 setosa\n\n<span style=\"color: #008080;\">#round any variables of type <em>numeric<\/em> to one decimal place<\/span>\ndata %&gt;% mutate_if(is.numeric, round, digits = 0)\n\n# Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n#1 5 4 1 0 setosa\n#2 5 3 1 0 setosa\n#3 5 3 1 0 setosa\n#4 5 3 2 0 setosa\n#5 5 4 1 0 setosa\n#6 5 4 2 0 setosa\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u8fdb\u4e00\u6b65\u9605\u8bfb\uff1a<br \/> <a href=\"https:\/\/statorials.org\/cn\/\u5728-r-\u4e2d\u5e94\u7528-lapply-sapply-\u548c-tapply-\u7684\u6307\u5357\/\" target=\"_blank\" rel=\"noopener noreferrer\">R \u4e2d apply()\u3001lapply()\u3001sapply() \u548c tapply() \u6307\u5357<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u7ec4\u7ec7\u7ebf\u6761-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u5728R\u4e2d\u6392\u5217\u884c<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u8fc7\u6ee4\u884c-r\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u5982\u4f55\u5728 R \u4e2d\u8fc7\u6ee4\u884c<\/a><br \/><\/strong><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684mutate()\u51fd\u6570\u5411\u6570\u636e\u6846\u6dfb\u52a0\u65b0\u53d8\u91cf\u3002 \u5728 R \u4e2d\u6dfb\u52a0\u65b0\u53d8\u91cf \u4ee5\u4e0bdplyr\u5e93\u51fd [&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":[],"class_list":["post-516","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u4f7f\u7528 Mutate \u5728 R \u4e2d\u521b\u5efa\u65b0\u53d8\u91cf - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684 mutate 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