{"id":2268,"date":"2023-07-23T00:28:27","date_gmt":"2023-07-23T00:28:27","guid":{"rendered":"https:\/\/statorials.org\/cn\/ggplot-%e6%89%8b%e5%86%8c%e5%9b%be%e4%be%8b\/"},"modified":"2023-07-23T00:28:27","modified_gmt":"2023-07-23T00:28:27","slug":"ggplot-%e6%89%8b%e5%86%8c%e5%9b%be%e4%be%8b","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/ggplot-%e6%89%8b%e5%86%8c%e5%9b%be%e4%be%8b\/","title":{"rendered":"\u5982\u4f55\u5728 ggplot2 \u4e2d\u521b\u5efa\u624b\u52a8\u56fe\u4f8b\uff08\u5e26\u6709\u793a\u4f8b\uff09"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u901a\u5e38\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u4f7f\u7528\u81ea\u5b9a\u4e49\u989c\u8272\u3001\u6807\u7b7e\u3001\u6807\u9898\u7b49\u5411 ggplot2 \u4e2d\u7684\u7ed8\u56fe\u6dfb\u52a0\u624b\u52a8\u56fe\u4f8b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5e78\u8fd0\u7684\u662f\uff0c\u4f7f\u7528<strong>scale_color_manual()<\/strong>\u51fd\u6570\u53ef\u4ee5\u5f88\u7b80\u5355\u5730\u505a\u5230\u8fd9\u4e00\u70b9\uff0c\u4e0b\u9762\u7684\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u505a\u5230\u8fd9\u4e00\u70b9\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u5728 ggplot2 \u4e2d\u521b\u5efa\u624b\u52a8\u56fe\u4f8b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u4f7f\u7528\u81ea\u5b9a\u4e49\u624b\u52a8\u56fe\u4f8b\u5728 ggplot2 \u56fe\u4e2d\u7ed8\u5236\u4e09\u4e2a\u62df\u5408\u56de\u5f52\u7ebf\uff1a<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">library<\/span> (ggplot2)\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (x=c(1, 2, 2, 3, 5, 6, 8, 8, 9, 9, 10, 11, 12, 15, 15),\n                 y=c(2, 3, 3, 4, 5, 5, 6, 7, 8, 8, 9, 10, 16, 19, 28))\n\n<span style=\"color: #008080;\">#create plot with three fitted regression models\n<\/span>ggplot(df, aes(x, y)) +\n  geom_point() +\n  geom_smooth(se= <span style=\"color: #008000;\">FALSE<\/span> , aes(color=' <span style=\"color: #ff0000;\">Linear<\/span> ')) +\n  geom_smooth(formula=y~poly(x, 2), se= <span style=\"color: #008000;\">FALSE<\/span> , aes(color=' <span style=\"color: #ff0000;\">Quadratic<\/span> ')) +\n  geom_smooth(formula=y~poly(x, 3), se= <span style=\"color: #008000;\">FALSE<\/span> , aes(color=' <span style=\"color: #ff0000;\">Cubic<\/span> ')) +\n  scale_color_manual(name=' <span style=\"color: #ff0000;\">Regression Model<\/span> ',\n                     breaks=c(' <span style=\"color: #ff0000;\">Linear<\/span> ', ' <span style=\"color: #ff0000;\">Quadratic<\/span> ', ' <span style=\"color: #ff0000;\">Cubic<\/span> '),\n                     values=c(' <span style=\"color: #ff0000;\">Cubic<\/span> '=' <span style=\"color: #ff0000;\">pink<\/span> ', ' <span style=\"color: #ff0000;\">Quadratic<\/span> '=' <span style=\"color: #ff0000;\">blue<\/span> ', ' <span style=\"color: #ff0000;\">Linear<\/span> '=' <span style=\"color: #ff0000;\">purple<\/span> '))<\/span><\/span><\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-20673 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/manuel1.png\" alt=\"\" width=\"653\" height=\"438\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u4f7f\u7528<strong>scale_color_manual()<\/strong>\u51fd\u6570\uff0c\u6211\u4eec\u80fd\u591f\u6307\u5b9a\u56fe\u4f8b\u7684\u4ee5\u4e0b\u65b9\u9762\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>name<\/strong> : \u56fe\u4f8b\u7684\u6807\u9898<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>Breaks<\/strong> : \u56fe\u4f8b\u4e2d\u7684\u6807\u7b7e<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>value<\/strong> \uff1a\u56fe\u4f8b\u4e2d\u7684\u989c\u8272<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u6211\u4eec\u8fd8\u53ef\u4ee5\u4f7f\u7528<strong>theme()<\/strong>\u51fd\u6570\u6765\u66f4\u6539\u56fe\u4f8b\u5143\u7d20\u7684\u5b57\u4f53\u5927\u5c0f\uff1a<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">library<\/span> (ggplot2)\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>df &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (x=c(1, 2, 2, 3, 5, 6, 8, 8, 9, 9, 10, 11, 12, 15, 15),\n                 y=c(2, 3, 3, 4, 5, 5, 6, 7, 8, 8, 9, 10, 16, 19, 28))\n\n<span style=\"color: #008080;\">#create plot with three fitted regression models\n<\/span>ggplot(df, aes(x, y)) +\n  geom_point() +\n  geom_smooth(se= <span style=\"color: #008000;\">FALSE<\/span> , aes(color=' <span style=\"color: #ff0000;\">Linear<\/span> ')) +\n  geom_smooth(formula=y~poly(x, 2), se= <span style=\"color: #008000;\">FALSE<\/span> , aes(color=' <span style=\"color: #ff0000;\">Quadratic<\/span> ')) +\n  geom_smooth(formula=y~poly(x, 3), se= <span style=\"color: #008000;\">FALSE<\/span> , aes(color=' <span style=\"color: #ff0000;\">Cubic<\/span> ')) +\n  scale_color_manual(name=' <span style=\"color: #ff0000;\">Regression Model<\/span> ',\n                     breaks=c(' <span style=\"color: #ff0000;\">Linear<\/span> ', ' <span style=\"color: #ff0000;\">Quadratic<\/span> ', ' <span style=\"color: #ff0000;\">Cubic<\/span> '),\n                     values=c(' <span style=\"color: #ff0000;\">Cubic<\/span> '=' <span style=\"color: #ff0000;\">pink<\/span> ', ' <span style=\"color: #ff0000;\">Quadratic<\/span> '=' <span style=\"color: #ff0000;\">blue<\/span> ', ' <span style=\"color: #ff0000;\">Linear<\/span> '=' <span style=\"color: #ff0000;\">purple<\/span> '))+\n theme(legend. <span style=\"color: #3366ff;\">title<\/span> =element_text(size= <span style=\"color: #008000;\">20<\/span> ),\n       legend. <span style=\"color: #3366ff;\">text<\/span> =element_text(size= <span style=\"color: #008000;\">14<\/span> ))\n<\/span><\/span><\/strong><\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-20677 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/manuel3.png\" alt=\"\" width=\"660\" height=\"443\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\"><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u6807\u9898\u548c\u8bf4\u660e\u6807\u7b7e\u7684\u5b57\u4f53\u5927\u5c0f\u5df2\u589e\u52a0\u3002<\/span><\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u6559\u7a0b\u89e3\u91ca\u4e86\u5982\u4f55\u5728ggplot2\u4e2d\u6267\u884c\u5176\u4ed6\u5e38\u89c1\u64cd\u4f5c\uff1a<\/span><\/p>\n<p><a href=\"https:\/\/statorials.org\/cn\/ggplot-\u56fe\u4f8b\u4f4d\u7f6e\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u66f4\u6539ggplot2\u4e2d\u7684\u56fe\u4f8b\u4f4d\u7f6e<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/ggplot2\u56fe\u4f8b\u7684\u5927\u5c0f\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u66f4\u6539ggplot2\u4e2d\u7684\u56fe\u4f8b\u5927\u5c0f<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u66f4\u6539\u56fe\u4f8b\u6807\u9898-ggplot2\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u66f4\u6539ggplot2\u4e2d\u7684\u56fe\u4f8b\u6807\u9898<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/ggplot-\u56fe\u4f8b\u6807\u7b7e\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u66f4\u6539ggplot2\u4e2d\u7684\u56fe\u4f8b\u6807\u7b7e<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u901a\u5e38\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u4f7f\u7528\u81ea\u5b9a\u4e49\u989c\u8272\u3001\u6807\u7b7e\u3001\u6807\u9898\u7b49\u5411 ggplot2 \u4e2d\u7684\u7ed8\u56fe\u6dfb\u52a0\u624b\u52a8\u56fe\u4f8b\u3002 \u5e78\u8fd0\u7684\u662f\uff0c\u4f7f\u7528scal [&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-2268","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\u5728 ggplot2 \u4e2d\u521b\u5efa\u624b\u52a8\u56fe\u4f8b\uff08\u5e26\u6709\u793a\u4f8b\uff09-Stattorials<\/title>\n<meta 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