{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# ggplot2 绘图\n", "\n", "ggplot2 的语法与 R 原生的语法并不统一，但是熟悉起来也并不复杂。它主要通过“+”连接多个绘图函数，同时允许将绘图结果赋值给其他对象，因此使用起来更加灵活。\n", "\n", "ggplot2 最为人称道的一点是美观性；部分用户学习 R 甚至仅仅为了用 ggplot2 画出更好看的图像。" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*注：ggplot2 官方的函数索引教程在 https://ggplot2.tidyverse.org/reference/](https://ggplot2.tidyverse.org/reference/) 。本文的部分例子取自官方索引。*" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "library(ggplot2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 基础\n", "\n", "加载了 ggplot2 包后，里面自带了一个 mpg 数据集，共 234 条观测，是有关车辆燃料的。11 个变量如下：\n", "\n", "- 制造商：manufacturer\n", "- 模具型号：model\n", "- 排放量：displ (engine displacement, in litres)\n", "- 年份：year\n", "- 发动机数量：cyl (number of cylinders)\n", "- 变速器形式：trans (type of transmission)\n", "- 驱动形式：drv (f = front-wheel drive, r = rear wheel drive, 4 = 4wd)\n", "- 每加仑城市行驶距离：cty (city miles per gallon)\n", "- 每加仑公路行驶距离：hwy (highway miles per gallon)\n", "- 燃料：fl (e: ethenol E85, d: diesel, r: regular, p: premium, c: CNG)\n", "- 车辆类型：class\n", "\n", "这里将主要利用这个数据集进行绘图。" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Classes 'tbl_df', 'tbl' and 'data.frame':\t234 obs. of 11 variables:\n", " $ manufacturer: chr \"audi\" \"audi\" \"audi\" \"audi\" ...\n", " $ model : chr \"a4\" \"a4\" \"a4\" \"a4\" ...\n", " $ displ : num 1.8 1.8 2 2 2.8 2.8 3.1 1.8 1.8 2 ...\n", " $ year : int 1999 1999 2008 2008 1999 1999 2008 1999 1999 2008 ...\n", " $ cyl : int 4 4 4 4 6 6 6 4 4 4 ...\n", " $ trans : chr \"auto(l5)\" \"manual(m5)\" \"manual(m6)\" \"auto(av)\" ...\n", " $ drv : Factor w/ 3 levels \"4\",\"f\",\"r\": 2 2 2 2 2 2 2 1 1 1 ...\n", " $ cty : int 18 21 20 21 16 18 18 18 16 20 ...\n", " $ hwy : int 29 29 31 30 26 26 27 26 25 28 ...\n", " $ fl : Factor w/ 5 levels \"c\",\"d\",\"e\",\"p\",..: 4 4 4 4 4 4 4 4 4 4 ...\n", " $ class : Factor w/ 7 levels \"2seater\",\"compact\",..: 2 2 2 2 2 2 2 2 2 2 ...\n" ] } ], "source": [ "mpg$drv <- as.factor(mpg$drv)\n", "mpg$fl <- as.factor(mpg$fl)\n", "mpg$class <- as.factor(mpg$class)\n", "str(mpg)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "先来看一个简单的例子：" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "g1 <- ggplot(mpg, aes(x=class))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "上面这个例子**不会**输出任何结果。函数 ggplot() 的作用仅仅是指定一些全图适用的参数，比如绘图使用的数据集、x/y 轴将使用的列(上面用 aes 参数指定了)、分组、颜色等等。ggplot2 绘图分为几个类似图层的概念：\n", "\n", "1. **setup**: 指定初始化参数，一般是 ggplot() 函数。\n", "2. **geometries**：图形层。即绘图的主题，一般是以 `geom_` 开头的命令，比如 `geom_bar()`。\n", "3. **labels**：标签层，图像的 x/y 轴刻度，以及轴标题、图像总标题。\n", "4. **themes**：主题层。包括图像的图例、字体、配色等等。\n", "5. **faceting**：图形的分组控制命令。\n", "\n", "图像必须有图形层才能显示主体，例如：" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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QoQKVmXGoVIlSwjKlaASMm61ChEqmQZUbECRErWpUYhUiXLiIoVIFKyLjVqgYsz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\nEImQgiASIQVBJEIKgkiEFOT/Ae9U7RKTqtZjAAAAAElFTkSuQmCC", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "g1 + geom_bar() # 注意到赋值的对象直接可以使用在“+”运算中" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "或许对于 ggplot() 函数与其 aes 参数还有诸多不解之处，在下面将逐渐提到。我们常用的 aes 参数有：\n", "\n", "- x= / y= ：这是基本参数。\n", "- fill= / color= ：一般指定一个因子，让 ggplot2 自动根据因子的水平数分配颜色并绘图。\n", "- shape= ：类似上，不过是自动分配点样式。\n", "\n", "## 绘图命令\n", "\n", "### 条形图：geom_bar()\n", "\n", "上面给出了很简单的一个条形图的例子，下面展示更多的用法：" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 纵轴数值：aes(stat=)\n", "\n", "默认纵轴是 x 轴上各离散类的计数（Count），对应的默认参数是 `geom_bar(stat=\"count\")`。如果想用其他值代替，需要在 ggplot() 中指定 aes(y=) 参数，并且在条形图函数中改动为 `geom_bar(stat=\"identity\")`。" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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tRxe21mWh1USBv3ljN13F6bmVYHFdLG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\nTkSuQmCC", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 以各类内部的排放量作为对应的 y 值，进行累加\n", "ggplot(mpg, aes(x=class, y=displ)) +\n", " geom_bar(stat=\"identity\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 权重：aes(weight=)\n", "\n", "下面的语句完成了同样的任务，只不过权重相当于使用了乘法。" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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NGRKDWG0pEQKVBFR6LUGEpHQqRAFR2JUmMoHQmRAlV0JEqNoXQkRApU0ZEoNYbS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\nP6k5VjoAAAAASUVORK5CYII=", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 权重。计算每个 class 内的排放总量\n", "ggplot(mpg, aes(class)) +\n", " geom_bar(aes(weight=displ))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 填充：aes(fill=)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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HPF9WiQBKl1jWBDSQaZK65HgyRIrWsE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\ndQvpCEjnn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bLEjP7vltFs+D9AtYb338\n1x1+HslFt/68yZMenqnp+MCLQLpuG8+43w1I5+Gbp2cygnS+oNSXtlTfGS7lmS8PvNFiPMOn\n085P/9OrHX4J83Dtp3Y/y3jy5D+Gjz+kHXrgp+/ZsI1n3C/+AYwQ+etIT782PHxbBZ9/vO2C\nI3z6BdeHsenHTg8/H+QtDo9H/jrtmYhvzPDE4dc7/NHVz7e83eSlL3//HP7WL3//8p78Np5x\nvxeQbqegfm+v/TLguu5jG4L0u0uQWiRIv7sEqUW/JUhKdUuQlJogQVJqggRJqQkSJKUmSJCU\nmiBBUmqCBClFJ1exstxeigRpabm9FAnS0nJ7t9anD6fzx4cNpH8+nOp7D3+eT+/+evSKSpYg\n3Vifz6cv+lAg/X36pi8kffz2yl/DKypagnRjfTz98fDPV4i+/vPu9N+Hh3/re5++vPk8vKKi\nJUg31rvT53qlfo706e8/33997Xz64+9vb/7xioqWIN1YP77G8O2V9/W53ZdP8r58xvfu08Pw\nioqWIN1Yj0D64/Tur78/1Zv+fXc6//PoFRUsQbqxHn1q9w2hz9/Z+uuXV1Ss3NCN9fH08fuX\nF77+88/D5+3nSP98efN5eEVFS5BurE/fvvz9rkCqr3X/fO3P4RUVLUG6tf798hHoj0/bp3V/\nnE7vv30x/OHj+XT+hs+PV1SyBEmpCRIkpSZIkJSaIEFSaoIESakJEiSlJkiQlJogQVJqggRJ\nqQn6/yckj4YqSH+oAAAAAElFTkSuQmCC", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 每个 class 下，按照 drv 的水平（三个）分别计数\n", "ggplot(mpg, aes(class)) +\n", " geom_bar(aes(fill=drv))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### 并列 / 等高：geom_bar(position=)\n", "\n", "默认的参数是 `position=stack`：" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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MKRApGG9kekMQEQaUGkPoiESEoUv1QD\nkRBp+9F2+f7x9Oki0un07/nD6cPlkx9O/yISIiHSy0fb48f5dDp9WkX6ePr86fT9Ua5fPiES\nIiHS86Pt8eX08eHHx1WkLw8P/zz+8POT/yASIiHSq0fb48PjW9D3VaTHN6MPl38R77xbg0iI\nhEivbTj9/nH96Ovp28O309+IhEiI9PrRIiL9OH3++ZXdD0RCJER6/Wh7tF/aXT7x+fT99Eny\nAZGG9kekMQEGifT36eOPh4+NSN9Op59f3SESIiHS60fbo/329/qZD9L3vhFpdH9EGhNg2D+Q\n/fT0D2TXT3w9/QeREAmR/ny0QSDS0P6INCYAIi2I1AeREEmJ4pdqIBIibT/aIBBpaH9EGhMA\nkRZE6oNIiKRE8Us1EAmRth9tEIg0tD8ijQmASAsi9UGkO4m0M/G/iIRIb2HOAIi0IFIfROqB\nSAsi9UGkHoi0IFIfROqBSAsi9UGkHoi0IFIfROqBSAsi9UGkHoi0IFIfROqBSAsi9UGkHvcU\n6boyrz77+9+w7f+heHYSROqCSD3uKNLGH7HffvbxT354ApEy+iPSmAD3E+kkvCN9bTz6ikgZ\n/RFpTIC7iXQKfmnXx06CSF0Qqcf0IunYSRCpCyL1uJdIp01lXn/2y5m/R0rsj0hjAtxJpNM1\nZa6K9IVvNqT2R6QxAe4l0rYbrz557n+XAZEQ6e4BDvPPkRAppz8ijQkwvUiftP8zGERCpLsG\nmF6k7+eP3xEprz8ijQkw/e+143c25PZHpDEBEGlBpD6I1GN6kXTsJIjUBZF6INKCSH0Qqcf0\nIvGlXW5/RBoTAJEWROqDSD0GifTfHWIirXz/+HfPI0RCpDsGOIhIDz9OXZPsJIjUBZHuJNIb\n2PgSji/tcvoj0pgAg0TaeSG9d6T/nPgzG1L6I9KYANOL9PS9hi+IlNEfkcYEOIpI565HiIRI\ndwwwvUg6dhJE6oJIiKRE8Us1EAmRth/tRiL9+PLhdPrwpf9vJdlJEKkLIh1epO+//uyTc/ff\nSrKTIFIXRDq8SJ9Pj/9i3/ePp8+IlNEfkcYEmF6k3/8gVv+zGyYkcOej+3sDLAaJNGeAQY/Q\nF2lTDFsk+y8JvCN14R2pK5L1WJdHe5NI21rwpd3Q/og0JsD0IvHNhtz+iDQmwJ1E2vn3i/j2\n99D+iDQmwPTvSDp2EkTqgkiIpETxSzUQCZG2H+1GIn1a/8D9D/w9Ukp/RBoTYHqRvqx/M3Xi\nu3Y5/RFpTIDpRTqfvj3+9C//HCmnPyKNCTC9SPwD2dz+iDQmwPQifTp9/vH4PfDTR0TK6I9I\nYwJM/3vtnv6B7L+IlNEfkcYEmF6k3/9Atv//7WInQaQuiHR8kWTsJIjUBZEQSYnil2ogEiJt\nPxoiySASIm0/GiLJIBIibT/aHul/9jciJfVHpDEBBon0BhBpaH9EGhOAd6QFkfog0p1E+t9t\nEAmREKl9NESSQSRE2n40RJJBJETafjREkkEkRNp+NESSQSRE2n40RJJBJETafjREkkEkRNp+\nNESSQSRE2n40RJJBJETafjREkkEkRNp+NESSQSRE2n40RJJBJETafrQ3iXTa/PO1EGlof0Qa\nE+BuIm36gkhD+yPSmAD3e0dCJERCpAWRIiASIm0/GiLJIBIibT8aIskgEiJtPxoiySASIm0/\nGiLJIBIibT/am0TaBpGG9i8jUsISECkaxS/VQCRE2gSRdBAJkTZBJB1EQqRNEEkHkRBpE0TS\nQSRE2mT3qPkji1+ASIi0iXvvPRBpaH9EQqQOdhJE6oJIiKRE8Us1EAmRNsmUpwWRhvZHJETq\nYCdBpC6IhEhKFL9UA5EQaZNMeVoQaWh/REKkDnYSROqCSIikRPFLNRAJkTbJlKcFkYb2RyRE\n6mAnQaQuiIRIShS/VAOREGmTTHlaEGlof0RCpA52EkTqgkiIpETxSzUQCZE2yZSnBZGG9kck\nROpgJ0GkLoj0LkU6/6T9GZEQ6Q8Qqe/Rrx/OT79AJER6DSIh0sj+iIRIL0Akrz8iIdILXoj0\n1yOjHiiBwJ2P7u8NsBgkkjg9YQkDnuqGaCKdH3hHsvrzjqQvISSSs6ELQyx6QKTB/REJkRrO\nL3+4YCdBpC6I9D5FOj//iEix/oiESE+cm58QKdYfkRDpN+fzr9/SwO9siPdHJETqYCdBpC6I\nhEhKFL9UA5EQaZNMeVoQaWh/REKkDnYSROqCSIikRPFLNRAJkTbJlKcFkYb2RyRE6mAnQaQu\niIRIShS/VAOREGmTTHlaEGlof0RCpA52EkTqgkiIpETxSzUQCZE2yZSnBZGG9kckROpgJ0Gk\nLoiESEoUv1QDkRBpk0x5WhBpaH9EQqQOdhJE6oJIiKRE8Us1EAmRNsmUpwWRhvZHJETqYCdB\npC6IhEhKFL9UA5EQaZNMeVoQaWh/REKkDnYSROqCSIikRPFLNRAJkTbJlKcFkYb2RyRE6mAn\nQaQuiIRIShS/VAOREGmTTHlaEGlof0RCpA52EkTqgkiIpETxSzUQCZE2yZSnBZGG9kckROpg\nJ0GkLoiESEoUv1QDkRBpk0x5WhBpaH9EQqQOdhJE6oJIiKRE8Us1EAmRNsmUpwWRhvZHJETq\nYCdBpC6IhEhKFL9UA5EQaZNMeVoQaWh/REKkDnYSROqCSIikRPFLNRAJkTbJlKcFkYb2RyRE\n6mAnQaQuiIRIShS/VAOREGmTTHlaEGlof0RCpA52EkTqgkiIpETxSzUQCZE2yZSnBZGG9kck\nROpgJ0GkLoiESEoUv1QDkRBpk0x5WhBpaH9EQqQOdhJE6oJIiKRE8Us1EAmRNsmUpwWRhvZH\nJETqYCdBpC6IhEhKFL9UA5EQaZNMeVoQaWh/REKkDnYSROqCSIikRPFLNRAJkTbJlKcFkYb2\nRyRE6mAnQaQuiIRIShS/VAOREGmTTHlaEGlof0RCpOMSuPPR/b0BFoNEEqcnLGHAU90Q3pGG\n9ucdSV9CSCRnQxcy5WlBpKH9EQmROthJEKkLIiGSEsUv1UAkRNokU54WRBraH5EQqYOdBJG6\nIBIiKVH8Ug1EQqRNMuVpQaSh/REJkTrYSRCpCyIhkhLFL9VAJETaJFOeFkQa2h+REKmDnQSR\nuiASIilR/FINREKkTTLlaUGkof0RCZE62EkQqQsiIZISxS/VQCRE2iRTnhZEGtofkRCpg50E\nkbogEiIpUfxSDURCpE0y5WlBpKH9EQmROthJEKkLIiGSEsUv1UAkRNokU54WRBraH5EQqYOd\nBJG6IBIiKVH8Ug1EQqRNMuVpQaSh/REJkTrYSRCpCyIhkhLFL9VAJETaJFOeFkQa2h+REKmD\nnQSRuiASIilR/FINREKkTTLlaUGkof0RCZE62EkQqQsiIZISxS/VQCRE2iRTnhZEGtofkRCp\ng50EkbogEiIpUfxSDURCpE0y5WlBpKH9EQmROthJEKkLIiGSEsUv1UAkRNokU56Wo4gU2TIi\nJSJORyS30E6CSF0QqQciLYjUB5F6INKCSH0QqQciLYjUB5F6INKCSH0QqQciLYjUB5F6INKC\nSH0QqQciLYjUB5F6INKCSH0QqQciLYjUB5F6INKCSH0QqQciLYjUB5F6INKCSH0QqQciLVVF\nihRZAWJ+yGTsRGsRear/1Xk1JVOeFkSKYx16pMgKEPNDJmMnWovIUyHSgkipeBsKkLETrUXk\nqRBpQaRUvA0FyNiJ1iLyVIi0IFIq3oYCZOxEaxF5KkRaECkVb0MBMnaitYg8FSItiJSKt6EA\nGTvRWkSeCpEWRErF21CAjJ1oLSJPhUgLIqXibShAxk60FpGnQqQFkVLxNhQgYydai8hTHVSk\n8/rjT54/Jy74CoiUiLehABk70VpEnuqYIq3+PP9wQVzwFRApEW9DATJ2orWIPNUhRTo/INIL\nrEOPFFkBYn7IZOxEaxF5qkOK9IBIL7EOPVJkBYj5IZOxE61F5Kneh0h/PTLqgTaIbDlwh9az\nRA7dKrICxPyQydiJ1iLyVAGR9Nf1TfCOFCdy6FaRFSDmh0zGTrQWkad6H+9IF8QFXwGREvE2\nFCBjJ1qLyFMh0oJIqXgbCpCxE61F5KkQaUGkVLwNBcjYidYi8lSItCBSKt6GAmTsRGsReaoj\ni8TvbPiNdeiRIitAzA+ZjJ1oLSJPdVCRriEu+AqIlIi3oQAZO9FaRJ4KkRZESsXbUICMnWgt\nIk+FSAsipeJtKEDGTrQWkadCpAWRUvE2FCBjJ1qLyFMh0oJIqXgbCpCxE61F5KkQaUGkVLwN\nBcjYidYi8lSItCBSKt6GAmTsRGsReSpEWhApFW9DATJ2oh165KkQaUGkVLwNBcjYCSLtYJ3g\nGsUpimzZusMA1qFHiqwAMT9kMnaCSDtYJ7hGcYoiW7buMIB16JEiK0DMD5mMnSDSDtYJrlGc\nosiWrTsMYB16pMgKEPNDJmMniLSDdYJrFKcosmXrDgNYhx4psgLE/JDJ2Aki7WCd4BrFKYps\n2brDANahR4qsADE/ZDJ2gkg7WCe4RnGKIlu27jCAdeiRIitAzA+ZjJ0g0g7WCa5RnKLIlq07\nDGAdeqTIChDzQyZjJ4i0g3WCaxSnKLJl6w4DWIceKbICxPyQydgJIu1gneAaxSmKbNm6wwDW\noUeKrAAxP2QydoJIO1gnuEZxiiJbtu4wgHXokSIrQMwPmYydINIO1gmuUZyiyJatOwxgHXqk\nyAoQ80MmYyeItIN1gmsUpyiyZesOA1iHHimyAsT8kMnYCSLtYJ3gGsUpimzZusMA1qFHiqwA\nMT9kMnaCSDtYJ7hGcYoiW7buMIB16JEiK0DMD5mMnSDSDtYJrlGcosiWrTsMYB16pMgKEPND\nJmMniLSDd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"text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(mpg, aes(class)) +\n", " geom_bar(aes(fill=drv), position=\"dodge\")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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P6pOaBIJ4eZjYermJ2+INL7R5FODjMb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", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(mpg, aes(class)) +\n", " geom_bar(aes(fill=drv), position=\"fill\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 箱形图：geom_boxplot()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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kZI9RkxJD8he4OQ6hMb0ire8mLb79lQ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\nyduZdQAAAABJRU5ErkJggg==", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(mpg, aes(class, hwy)) + \n", " geom_boxplot(varwidth = TRUE)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "箱形图主题用 fill 参数指定填充颜色，color 参数指定边框颜色。\n", "\n", "对于箱形图外侧的异常点，可以用 outlier 开头的参数进行控制。以下是它们的默认值：\n", "\n", "- outlier.shape = 19 点样式\n", "- outlier.size = 1.5 点大小\n", "- outlier.stroke = 0.5 边线宽\n", "- outlier.color = NULL 边线颜色\n", "- outlier.fill 填充颜色（需要点样式支持）" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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ebdH+0W32knpPVUSxFS46mmxVw/A33+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\nAABJRU5ErkJggg==", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(mpg, aes(class, hwy)) + \n", " geom_boxplot(fill = \"white\", color = \"darkgreen\", \n", " outlier.shape=21, outlier.size=4, outlier.stroke = 1,\n", " outlier.color = \"blue\", outlier.fill = \"orange\")" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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"text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 并列箱形图的画法。注意只有 subcompact 类型的车辆有三种 drv 数据\n", "ggplot(mpg, aes(class, hwy)) + \n", " geom_boxplot(aes(color = drv), fill=\"white\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 散点图：geom_point()\n", "\n", "最简单的一类图像。" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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BKUAQPerUjHi2S/IxLgPQU32t47pJFI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\nF/ZVpmqPN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"text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 根据驱动方式，填充不同颜色；根据发动机数量，选择不同点大小。\n", "# 在数据量大或有重复点时，更改 alpha 值是不错的选择\n", "ggplot(mpg, aes(cty, hwy)) +\n", " geom_point(aes(color = drv, size=cyl), shape=19, alpha=0.5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 折线图：geom_line()" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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"text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dt <- data.frame(Data = 1:40, \n", " x.value = rep(paste(\"X\", 11:30, sep=\"\"), 2),\n", " categ = c(rep(\"Categ 1\", 20), rep(\"Categ 2\", 20)))\n", "\n", "# 若不指定 group，无法用离散数据作为 x 轴来正确作图\n", "# 有时候可以通过 group=1 来强制连接所有的点成线\n", "ggplot(dt, aes(x=x.value, y=Data, group=categ, color=categ)) +\n", " geom_line()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 直方图：geom_histogram()\n", "\n", "参数 bins 指定组的个数， binwidth 则指定每个组的宽度。" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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42Y6YmnDki3mn3VY7Pcww/30vNhI2Z64qkD0q1mX/XYLPfww730fNiImZ546oB0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\nPYLL6qESVwAAAABJRU5ErkJggg==", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(mpg, aes(cty, fill=drv)) + \n", " geom_histogram(bins=20)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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0AC0pSTw6P+z6BbIB2/bRcllb0T5wPS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", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(mpg, aes(cty, fill=drv)) + \n", " geom_histogram(binwidth=2.5)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 矩形图：geom_rect() / geom_tile()\n", "\n", "两者功能相同，但参数有区别。前者指定 xmin/xmax/ymin/ymax 四个角点，后者指定矩形中心坐标 x,y 以及矩形的宽与高 width/height。" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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rv1h5OoKQIkz/HJZ7f+cBI1RYDkOT757NYfTqKmCJA8xyef3frDSdQUAZLn+OSz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\nCAIkQgQBEiGCAIkQQYBEiCBAIkSQ/wfGfBjOUyVYcAAAAABJRU5ErkJggg==", "text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dt <- data.frame(x=1:5, y=(6:10)/10, w=rep(2, 5), h=rep(0.08, 5), z=factor(c(1,1,2,3,2)))\n", "\n", "ggplot(dt, aes(x, y)) +\n", " geom_tile(aes(fill=z))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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vpQWyL99svH5/9Z5w+//AuRSh4078eR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\nSGJNASLt4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"text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ggplot(dt, aes(x, y, width = w, height = h)) +\n", " geom_tile(aes(fill=z))" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": {}, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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"text/plain": [ "plot without title" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# 改用 geom_rect 绘制\n", "ggplot(dt, aes(xmin = x - w / 2, xmax = x + w / 2, ymin = y - h / 2, ymax = y + h / 2, width = w, height = h)) +\n", " geom_rect()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 主题命令：theme()\n", "\n", "略。这其中的部分功能也可以由 guide() 命令代完成。" ] } ], "metadata": { "kernelspec": { "display_name": "R", "language": "R", "name": "ir" }, "language_info": { "codemirror_mode": "r", "file_extension": ".r", "mimetype": "text/x-r-source", "name": "R", "pygments_lexer": "r", "version": "4.0.0" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": true, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": false } }, "nbformat": 4, "nbformat_minor": 2 }