45 Coordinates and Faceting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Coordinates and Faceting\n",
    "Learning how to deal with coordinates will allow us to size our plots correctly. Faceting will allow us to place several plots next to each other, these plots are usually related by the same dataset.\n",
    "\n",
    "Let's build our understanding of these ideas by going through some simple examples:\n",
    "\n",
    "## Basic Plot and Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(ggplot2)"
   ]
  },
  {
   "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         : chr  \"f\" \"f\" \"f\" \"f\" ...\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          : chr  \"p\" \"p\" \"p\" \"p\" ...\n",
      " $ class       : chr  \"compact\" \"compact\" \"compact\" \"compact\" ...\n"
     ]
    },
    {
     "data": {
      "image/png": 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HH98Ndnm1/UFZwBAykD7A7YDSl+/UUe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\nGAzB+D9c4DyAyp1d4AAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl <- ggplot(mpg, aes(x= displ, y=hwy))+geom_jitter()\n",
    "str(mpg)\n",
    "pl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting x and y limits\n",
    "You can use + scale_x_continuous and scale_y_continuous with an additional limits=c(low,high) argument to set the scale. A sometimes nicer way to do this is by adding + coord_cartesian() with xlim and ylim arguments and pass in numeric vectors. For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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gIizQGl6s48Wt9GpDmgVN2Xh5+4ItIcUKruCyLlo1K1MuXfRIqkftoHREpGpWpd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\nJEICgkiEBASRCAkIIhESEEQiJCD/B56Eu/RxRkM7AAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl + coord_cartesian(xlim = c(1,4), ylim= c(15,30))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Aspect Ratios\n",
    "You can use the coord_fixed() method to change the aspect ratio of a plot (default is 1:1). For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KBQp55I/3nLZP8i0vROF5VImZyehI9F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\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl + coord_fixed(ratio = 1/3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Facets\n",
    "The best way to set up a facet grid (multiple plots) is to use facet_grid(), the main part of this function is the use of the facet argument:\n",
    "\n",
    "    A formula with the rows (of the tabular display) on the LHS and the columns (of the tabular display) on the RHS; the dot in the formula is used to indicate there should be no faceting on this dimension (either row or column). The formula can also be provided as a string instead of a classical formula object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SqJtQaSSiggSSWx1kBSCQWk8LqdWTum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\njAIDSAxGgQEkBqPAABKDUWD8HxATHLj7Z9nfAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl + facet_grid(. ~ cyl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oEEpLw+0iYgOftIm4AUIpCMfbQIJCDl\n9ZE2AcnZR9oEpBCBZOyjxY0hXe/FAQlI4wik5R89+O4QkIA0jkBa/NHD1ysACUjjCKTFHz31\nzyjWbAJSiEAy9tHilpAm/z3Smk1AChFIxj5aBBKQ8vpIm4C09KOBlPVnAan6mdgSEjcbsv4s\nIFU/E5tC4vZ30p8FpOpnYltIpggkILV2JoAEpLw+0iYgOftIm4AUIpCMfbQIJCDl9ZE2AcnZ\nR9oEpBCBZOyjRSABKa+PtAlIzj7SpkxIDMPEARLDGAZIDGMYIDGMYYDEMIYBEsMYBkgMYxgg\nMYxhgMQwhgESwxiGlwjV6SNt2u7Q8xKhkHmtXYhAMvbRIpCAlNdH2gQkZx9pE5BCBJKxjxaB\nxDCvPlyRQgztq/eRNm136LkihQykEIFk7KNFIAEpr4+0CUjOPtKmbSF9/GzL1k5fiEAy9tEi\nkJZCOv6U2NZOX4hAMvbRIpAWQhr+3HLrg3BGIBn7aBFIQMrrI20CkrOPtAlIIQLJ2EeLQFoI\niedItgik1s7EppC4a+eKQGrtTGwLKelBOCOQjH20CCQg5fWRNgHJ2UfaBKQQgWTso0UgASmv\nj7QJSM4+0iYghQgkYx8tAglIeX2kTUBy9pE2ASlEIBn7aBFIQMrrI20CkrOPtAlIIQLJ2EeL\nQAJSXh9pE5CcfaRNQAoRSMY+WgQSkPL6SJuA5OwjbQJSiEAy9tEikICU10faBCRnH2kTkEIE\nkrGPFoG0FNLxn8e2dvpCBJKxjxaBtBDS5z80b+30hQgkYx8tAmkZpNOPbGjt9IUIJGMfLQIJ\nSHl9pE1AcvaRNtkg9cdf3gdIG0QgtXYmXJCOgPqLqMmzyXMkWwRSa2fCBKk/LIDEXTtbBFJr\nZ8IDqT8sgpT1IJwRSMY+WgTSBKSv7/PodzDMU40FUn/gipTVR9q03aHnihSyA9LFD5C2ikBq\n7UxYIH0OkKp/4gLJ2Ufa5HmOdOCKlNVH2gQkZx9pE5BCBJKxjxaBdPHz8JUNeQ/CGYFk7KNF\nIN2ZzR6EMwLJ2EeLQAJSXh9pE5CcfaRNQAoRSMY+WgQSkPL6SJuA5OwjbQJSiEAy9tEikICU\n10faBCRnH2kTkEIEkrGPFoEEpLw+0iYgOftIm4AUIpCMfbQIpGWQjv8+tr3TFyKQjH20CKRF\nkD5/YkN7py9EIBn7aBFISyCdfoZQe6cvRCAZ+2gRSEDK6yNtApKzj7QJSCECydhHi0BaAonn\nSECaiUBaBIm7dkB6HIG0DFLeg3BGIBn7aBFIQMrrI20CkrOPtIkv7UIEkrGPFoG0CBI3G4D0\nOAJpCSRufwNpJgIJSHl9pE1AcvaRNgEpRCAZ+2gRSEsg8RwJSDMRSIsgcdcOSI8jkJZBynsQ\nzggkYx8tAmkRpNMFqbnTFyKQjH20CKQlkM5PkZo7fSECydhHi0BaMKebduv+EIZpdba6InXc\n/uaKNBPXHPrqZwJIIQLJ2EeLQFoAiW/IAmkuAmkJJL4hC6SZCKRFkN64IvkikFo7Extfkd4l\ntXb6QgSSsY8WgQSkvD7SJiA5+0ibtoH0AQhIQHocgTQH6VMQz5F8EUitnYktIHXXyXkQzggk\nYx8tAmk5JK5Ingik1s4EkEIEkrGPFoE0A+kNSO4IpNbOxCaQrnftch6EMwLJ2EeLQJqD9CmI\nf4/ki0Bq7Uxs9hxpusjwHeUPwhmBZOyjRSA9hnS9831TZEys+EE4I5CMfbQIpFJI4T3FD8IZ\ngWTso0UgPYTUAckfgdTamdgM0lQRIJVGILV2JqpC4jlSaQRSa2eiLiTu2hVGILV2JipDau9w\nAcnYR4tAKoR0+wypgcMFJGMfLQLpIaT4ROhSJN7OK38QzggkYx8tAukxpMMQy/V/j/6R0roH\n4YxAMvbRIpBmIA22DuAAaUUEUmtnYltIQzlAWhGB1NqZqAeJ50grIpBaOxP1IRkehDMCydhH\ni0A69O8z/O/dszmkA6TyCKTWzkQRpG9/D97x4ef0S38Jd89muIPXda0dLiAZ+2jx9SC9f/73\nf/2rQuqG/072/BauSEURSK2diSJI//3vxweB7//7M74sPYT0qWbua7vqhwtIxj5afD1IH/Pv\nz/4dwbfrdWkM6ev7jD6+G87oLQeG2f0UQzr8+Xlk8P0YPm8yPLoijSCN3rL+bwNnDO0f/6ZV\n7bkihSgd+me5Iv3+cbwc/fre/Ti9ZeZLuy7MM9y1W/ftZCCF+IKQ/v1++aru8qWZCOnyhZ3h\nQTijcDZv/yao/YkLJGcfaVMRpG9d9+P3+e39ort29xwBqShuAEm62AKpCFL38/dhOHOQ7ira\nNaSJ53hPBEl7aEAqg9QNv4t0mHtlwyNHzR0uGVJyn+mYDunmwQHp8aYiSMfvIv3433+Hx3Pa\n9NBRc4cLSMcBkripCNLh8PufD0zf/7cKku1BOKNwNp/5SzsgiZsKIX3Mx/eRSiFdn8q2driA\ndBzxoQGpFNKvjxc2fPt7CaSp50jeB+GMy8/m7WN5HkiDR9Yt+X8iAqQiSMeXBy1+jnQY/j81\nt37uNQEpuc90TIY0eGjn/wGkx5uinC9LIL0f2p9zim7OJpD2Aml4mi7/C0iPN10FXWYe0q/P\nK9Lwtd/zkI7zTJDW/sDlViF1QCrYNHFF+jIL6Wzp28+XhrTyBy43Cmn8dQOQkiEdDv/93S27\nazcF6fop2NrhWnM2nwvSIJb20eJTQVp0s+Fw+P339+7m9Q3LIQ1OVGuHC0ins3N+L3ftFm0q\ngvRXP6/oztm8kdTa4Xp5SNd/yry+jxZfD9ISRffOZne9FX4MrR0uIHWXU3SOxX20+HqQlih6\ndDYHz5R2/Q/76p++ENdCGvwtN7ptV9pHi68H6XD8eQ1dwc2Gt/OF6Oa50poH4YyvDKmLw127\nxZuKIP28HGkV0uBKBKQVMQXSjSMgLd9UBKnvHr/I7u7ZvD1VQCqK20B6A9LiTUWQFv4IrdvN\n59MCpJXRAKmL3ymauBS98RwpFdLPbsEr7R7+EP17juofrleBdDn2N5eh4dvfuGuXCenw4/vc\n6+xmIF1Da4frRSBN/ZU2+ost/jUHpMebdEijo74C0vlPMDwIZwTS8P3XCxSQHm+qAmn4JUVr\nh+vlIU19vVfaR4svBmn5TGwenBkgrYirId1/jjT9xAlIM5s2hnT7by9bO1yvAuly1w5Ie4f0\ntuAEAUnapEA6xylHE1/bAenxppqQbA/CGV8d0vmd3ek+w/mNQHq8aWtI4o/CBZK0qQTS+GVb\ntx/cvc5du0UPtRVI2g9nB5K0qQjS6IXEb8O3re6jxdqQll18K0Bi9jTHT6PJ8CJz+quk8Hdv\nf0XK/3t5VQztq/eRNq069OPrUSd95VD90Bv6LLyv0syXdkAyxAxIgwgkeROQQgTS7R284j5a\nrAyp3edIKx6T9iCc8QUhjW9WTTt6BUg7u2sHJEP0Qbqi+XzvHUcvAWnNJiCF+GKQbl67sO6Z\nwqoIpFJIHa+1K4wuSLevarj8byBJm2pC+rxtb3gQzvjKkEY/7RtI0qaKkAq+FAfS43evhTT8\ncSfhgx/fxKt+6KufCSCF+PKQzneBh+dp9iWS1Q999TMBpBBfC9Lka7+70XdTbt4t9NEikMog\n8RypPNogvZ2F3PyldvrgW2dCHy0CqRASd+2KoxtSd/t6byBJm6pCcj0IZ3xZSHc+eNoRkGIG\nUohACh88fcECUshACvHVIF2fHN374IfMltUFEpBq95E2FR3687Wm+pkAEpDy+kibPId+ySUI\nSCEDKcSXh3R+znR+78wXfis2xQgkIOX1kTYZDv3lDt3QVWkfLQIJSHl9pE3rD30XIHXxAiX1\n0SKQgJTXR9oEJGcfaROQQgTSSA6QgASkkhXx+7M8RwISkEpWjL+txBUJSEAybAQSkIAEpPwI\nJCAtijxHAhKQHBt5ZcOiTUAKEUjGPloE0qF/n+F/gZQcgdTambBA6k+/9JcApNwIpNbOBJBC\nBJKxjxaBdNYEpK0ikFo7E1mQvr7P3O9gmKcZG6T+wBWp+hVgu0PPFSlkIIUIJGMfLQJpZAhI\nG0QgtXYmTJD6oAlIuRFIrZ0JD6R+8B8gbRCB1NqZsEDq+9NLGnhlw0YRSK2dCddzpKnZ7EE4\nI5CMfbQIJCDl9ZE2AcnZR9oEpBCBZOyjRSABKa+PtAlIzj7SJiCFCCRjHy0CCUh5faRNQHL2\nkTYBKUQgGftoEUhAyusjbQKSs4+0CUghAsnYR4tAAlJeH2kTkJx9pE1AChFIxj5aBBKQ8vpI\nmyyHftEPsgNSyEAK8eUhLfvRqkAKGUghvjqkhT/sG0ghAylEIAGpZBOQQgQSkEo2ASnEV4fE\ncyQgVT+bTwGJu3ZAqn02nwOSsY8WgQSkvD7SJiA5+0ibgBQikIx9tAgkIOX1kTYBydlH2gSk\nEIFk7KNFIAEpr4+0CUjOPtImIIUIJGMfLQIJSHl9pE1AcvaRNgEpRCAZ+2gRSEDK6yNtApKz\nj7QpExLDvMxwRQoxtK/eR9q03aHnihQykEIEkrGPFoEEpLw+0iYgOftIm4AUIpCMfbQIJCDl\n9ZE2AcnZR9oEpBCBZOyjRSABKa+PtAlIzj7SJiCFCCRjHy0CCUh5faRNQHL2kTYBKUQgGfto\nEUhAyusjbQKSs4+0CUghAsnYR4tAAlJeH2kTkJx9pE1AChFIxj5aBBKQ8vpIm4Dk7CNtAlKI\nQDL20SKQgJTXR9oEJGcfaROQQgSSsY8WgQSkvD7SJiA5+0ibgBQikIx9tAgkIOX1kTYBydlH\n2gSkEIFk7KNFIAEpr4+0CUjOPtImIIUIJGMfLQIJSHl9pE1AcvaRNgEpRCAZ+2gRSEDK6yNt\nApKzj7QJSCECydhHi0ACUl4faROQnH2kTUAKEUjGPloEEsMwCwdIDGMYIDGMYYDEMIYBEsMY\nBkgMYxggMYxhgMQwhgESwxiGVzbU6SNt2u7Q88qGkHmJUIhAMvbRIpCAlNdH2gQkZx9pE5BC\nBJKxjxaBxDCvPlyRQgztq/eRNm136LkihQykEIFk7KNFIAEpr4+0CUjOPtImIIUIJGMfLQIJ\nSHl9pE1AcvaRNgEpRCAZ+2gRSEDK6yNtApKzj7QJSCECydhHi0ACUl4faROQnH2kTUAKEUjG\nPloEEpDy+kibgOTsI20CUohAMvbRIpCAlNdH2gQkZx9pE5BCBJKxjxaBBKS8PtImIDn7SJuA\nFCKQjH20CCQg5fWRNgHJ2UfaBKQQgWTso0UgASmvj7QJSM4+0iYghQgkYx8tAglIeX2kTUBy\n9pE2ASlEIBn7aBFIQMrrI20CkrOPtAlIIQLJ2EeLQAJSXh9pE5CcfaRNQAoRSMY+WgQSkPL6\nSJuA5OwjbQJSiEAy9tEikICU10faBCRnH2kTkEIEkrGPFoH0Mf3xl/cB0gYRSK2dCRekI6D+\nIgpIuRFIrZ0JE6T+AKScPtImIDn7SJs8kPoDkJL6SJuA5OwjbcqC9PV9Hv0OhnmqsUDqD1yR\nsvpIm7Y79FyRQnZAuvgB0lYRSK2dCQukzwFS9U9cIDn7SJs8z5EOXJGy+kibgOTsI20CUohA\nMvbRIpAufnhlw0YRSK2dCRukidnsQTgjkIx9tAgkIOX1kTYBydlH2gSkEIFk7KNFIAEpr4+0\nCUjOPtImIIUIJGMfLQIJSHl9pE1AcvaRNgEpRCAZ+2gRSEDK6yNtApKzj7QJSCECydhHi0AC\nUl4faROQnH2kTUAKEUjGPloEEpDy+kibgOTsI20CUohAMvbRIpCAlNdH2gQkZx9pE5BCBJKx\njxaBBKS8PtImIDn7SJuAFCKQjH20CCQg5fWRNgHJ2UfaBKQQgWTso0UgASmvj7QJSM4+0iYg\nhQgkYx8tAglIeX2kTUBy9pE2ASlEIBn7aBFIQMrrI20CkrOPtAlIIQLJ2EeLQAJSXh9pE5Cc\nfaRNQAoRSMY+WgQSkPL6SJuA5OwjbcqExDAvM1yRQgztq/eRNm136LkihQykEIFk7KNFIAEp\nr4+0CUjOPtImIIUIJGMfLQIJSHl9pE1AcvaRNgEpRCAZ+2gRSEDK6yNtApKzj7QJSCECydhH\ni0ACUl4faROQnH2kTUAKEUjGPloEEpDy+kibgOTsI20CUohAMvbRIpCAlNdH2gQkZx9pE5BC\nBJKxjxaBBKS8PtImIDn7SJuAFCKQjH20CCQg5fWRNgHJ2UfaBKQQgWTso0UgASmvj7QJSM4+\n0iYghQgkYyc+KP8AAAovSURBVB8tAglIeX2kTUBy9pE2ASlEIBn7aBFIQMrrI20CkrOPtAlI\nIQLJ2EeLQAJSXh9pE5CcfaRNQAoRSMY+WgQSkPL6SJuA5OwjbQJSiEAy9tEikICU10faBCRn\nH2mTB1L/PsP/Aik5Aqm1M2GB1J9+6S8BSLkRSK2dCSCFCCRjHy0C6awJSFtFILV2JrIgfX2f\nud/BME8zJkifNxm4Im0VuSK1dib40i5EIBn7aBFIQMrrI20CkrOPtMkCibt2eX2kTUBy9pE2\nASlEIBn7aBFIvLIhr4+0CUjOPtIm33Ok29nsQTgjkIx9tAgkIOX1kTYBydlH2gSkEIFk7KNF\nIAEpr4+0CUjOPtImIIUIJGMfLQIJSHl9pE1AcvaRNgEpRCAZ+2jxOSB9OQ2QgGTro8XngHTi\nxBUJSL4+WnwmSFESkGr3kTYBydlH2gSkEIFk7KPFp4LEl3ZA8vXRIpCAlNdH2gQkZx9pE5BC\nBJKxjxaBBKS8PtImIDn7SJuAFCKQjH20CCQg5fWRNmUc+q7rivtoEUhAyusjbUo49F33KQlI\njzcBKUQgjWLXnSSdLkxaHy02Deny+IEEpBWQzhcmrY8WW4Z0ffxAAlI5pMuFSeujxYYhDR4/\nkIBUEgcXpNeCNPpaDkhyBFKI52dILwZp/LUckOQIpMn4as+RohyeI6kRSNPxxe7a3VyCuGsn\nRiAZ+2ixaUhzm4AUIpBifM1vyN48R5rZBKQQgRTi6TPq1SCNvpYbPkOsAIl5gjl9jVO7RtVZ\ncgy4IoUY2lfvI21KOPTnJwsvd0UaxNHNf760AxKQyuIDSJc3AylEIIX4qs+RhvHuc6TrO4AU\nIpBifM27duN4567d4FIFpBCBZOyjxYYh3YlAuh+BNBnDCxuAdBwg3Y9AmorxpXZA+hyeIwGp\n8G9eqY8WN4U0fDiOKzWQQgTSRHw+SKPHM/nB975xdGcTkEIE0kR8OkjjBzT1wXf/3QSQgFQe\nn+050iwkXv29NgJpMj7ZXTsgpf1ZQKp+JjaENPscCUhrI5CMfbS4JaTZu3Y8R1oZgWTso8VN\nIc1G7tqti0Ay9tFiW5DETUAKEUjGPloEEpDy+kibgLT4o02vbAASkJo7E1tCmn9lg7gJSCEC\nydhHixtCmn9lg7oJSCECydhHi0ACUl4faROQlr27A1LanwWk6mdic0ir2oYMpBCBZOyjRSAB\nKa+PtAlIy94NpOkH4YxAMvbRIpCAlNdH2gSkhR89/vdVQALSOAJp6UeP/n0VkIA0jkBy9pE2\nASlEIBn7aLE2pGX/ACkVUv8+w/8CKTkCyd9n4T+JzYTUn37pLwFIuRFI9j7dZYBU+2xW/8QF\nUnmBK6Ru/oNvs+85EpDqf+ICqbxAd09SXUhf32fudzBMQzOAVPC7bZD6A1ek6leA7Q79812R\nhtekgk1AChFIxj5arA0p/usKaZMLUj/+BUi5EUgpfWrftTvrAdJWEUitnQkPpH7wHyBtEIHU\n2pmwQOr700saeGXDRhFIrZ0J13OkqdnsQTgjkIx9tAgkIOX1kTYBydlH2gSkEIFk7KNFIAEp\nr4+0CUir+1S+/Q2krD7SJiCt7VP9G7JASuojbQLSyj4NvEQISDl9pE1AWtkHSLYIJGMfLQIJ\nSHl9pE1AWtkHSLYIJGMfLTYA6XqzYemP2AcSkFo7Ew1Aurz6e3BhAhKQavfR4qaQJn/S6ief\nw/hLPCABqXYfLW4JafJnf19/itAQUnjOBCQgNX4mNoQ0vqkQIHUjSPHuA5CA1PiZaAZSN77p\nMJYEJCA1fiaqQxr+0IbBF3ZAKolAMvbR4oaQpp8jTX0fCUhAqt9Hi1tCmr5r9zbx/VieIwGp\neh8tbgppMk69sIG7dkCq3keLjUJatglIIQLJ2EeLQAJSXh9pE5BW9rm8REjeBKQQgWTso8UG\nIL2dXiKkbwJSiEAy9tFiC5CKNwEpRCAZ+2ixNqRlr1IFEpAaPxOVIV3uMwCp9tms/okLpPIC\n1zt2zUFimP3M+d9QFA5XpBBD++p9pE3bHXquSCEDKUQgGftosS4kniN5I5CMfbRYGRJ37awR\nSMY+WqwNadUmIIUIJGMfLQIJSHl9pE1AcvaRNgEpRCAZ+2gRSEDK6yNtApKzj7QJSCECydhH\ni0ACUl4faROQnH2kTUAKEUjGPloEEpDy+kibgOTsI20CUohAMvbRIpCAlNdH2gQkZx9pE5BC\nBJKxjxaBBKS8PtImIDn7SJuAFCKQjH20CCQg5fWRNgHJ2UfaBKQQgWTso0UgASmvj7QJSM4+\n0iYghQgkYx8tAglIeX2kTUBy9pE2ASlEIBn7aBFIQMrrI20CkrOPtAlIIQLJ2EeLQAJSXh9p\nE5CcfaRNQAoRSMY+WgQSkPL6SJuA5OwjbQJSiEAy9tEikICU10faBCRnH2kTkEIEkrGPFoEk\nzde092b+0bULrFpcvUD+oa9Xb1n76wCpagEgtVoPSNIfXbsAkFqtByTpj65dAEit1qsGiWFe\neYDEMIYBEsMYBkgMYxggMYxhgMQwhjFB6t+n9L0fHzDzR99//+w7ZzbP/hnr2q8o72m/60M/\n/0fUPfTD8UDqL7/o7/1438N3li+e//0L/oxV7deWX9t+14d+fkPdQz+aFiD1j091+eLZdy75\nM1a1T/9UfOZDP/+3QN1DPxrjc6TSXv3MqS7fuewjlnxYYfvVp8rSfteH/nG/+of+PO1Devyl\n7mHma9mlhyMJ0rrypva7PvTFkDY69OfxQXr8lfjjvzrm/lq8f/Wf+d2WvxXL268s72i/60P/\n+I7Aw9+80aG/zDaQHrx7wVer676MXjSlBZa0Ly+f/HXpLg79iqO3xaG/jA1S8afikluNxQfE\n5GhV+9qfivs+9A8uKg0c+uu4IM2WKuU/c4le8rtnZ75bYft15Q3td33oF1xzKh/6wbi+ITv7\nzjVns/RwLTweC87VCkjl5Q3td33oV0PKPvTDMX0fac23kQ8zD2nNN7+XHI+5LxHWvrKh/E82\ntN/1oV/9yobS91b80o5hXnqAxDCGARLDGAZIDGMYIDGMYYDEMIYBEsMYBkgMYxggtTxd9/l/\nd97FtDOcjpYHSLsZTkfL80ALkNoaTkej8+d79+N6Rfq77779cziGH933PwcgtTacjjbnv77r\nuh9nSD+7j/nnI/z1/j/6/4DU2nA62pyf3ffDf9/PkLruz+FX13/8j+//Hb53P4HU2nA62pxv\n73QOf86Q+u6vf49v7rrfH2/+BqTWhtPR5nw6OUP69/0LvW9/bt7MtDOcjjYnivn9ret/Aand\n4XS0OeMv7T7mn/OTpfc3fwdSa8PpaHP+/ryrcHmO9Ovw+3Sz4eMexN9Aam04HW3O1O3vI5/v\nH7e/D0BqbTgdjc6fH8NvyP7su/7d0ceXdt+7v/iGbHvD6djVwKfV4cTsaoDU6nBidjVAanU4\nMbsaILU6nBiGMQyQGMYwQGIYwwCJYQwDJIYxzP8BO7UbaReyL/IAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl + facet_grid(drv ~ cyl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rTbFBaWAJK0QTUL9wLJmkhKGHaTwowSQJI26GbhmvdI8gbn9jBu2E8K0yWAJG1Q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\nQgoCJIQUBEgIKej/AUJBKCJT43QEAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl + facet_wrap(vars(model))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}