47-2  ggplot2 Training Exercise - Answer Sheet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ggplot2 Exercises\n",
    "Recreate the following plots shown below. Don't worry if they don't match exactly to what is shown below, as long as you have a general understanding of ggplot2 and the grammar of graphics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(ggplot2)\n",
    "library(ggthemes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1) Create a histogram of hwy mpg values using the mpg dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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HO7hOSkwr7DRIRkbpeQnFTYd5iIkMzt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\nNvD/0nYsPTZY8UYAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl <- ggplot(mpg, aes(x = hwy))\n",
    "pl + geom_histogram(\n",
    "    fill = 'red',\n",
    "    alpha = 0.5,\n",
    "    bins=20\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2) Create a bar graph per manufacturer with color fill defined by cyl count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9UcpM8zvV9I/uMnIH2iKUiFQDJtmYJU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\nCggkKSCQpIBAkgICSQoIJCmg/we3GuHLdOTxGQAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl <- ggplot(mpg,aes(x = manufacturer))\n",
    "pl + geom_bar(\n",
    "    aes(fill = factor(cyl))\n",
    ") + theme_minimal()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now switch to the txhousing dataset that comes with ggplot2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A tibble: 6 × 9</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>city</th><th scope=col>year</th><th scope=col>month</th><th scope=col>sales</th><th scope=col>volume</th><th scope=col>median</th><th scope=col>listings</th><th scope=col>inventory</th><th scope=col>date</th></tr>\n",
       "\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>Abilene</td><td>2000</td><td>1</td><td> 72</td><td> 5380000</td><td>71400</td><td>701</td><td>6.3</td><td>2000.000</td></tr>\n",
       "\t<tr><td>Abilene</td><td>2000</td><td>2</td><td> 98</td><td> 6505000</td><td>58700</td><td>746</td><td>6.6</td><td>2000.083</td></tr>\n",
       "\t<tr><td>Abilene</td><td>2000</td><td>3</td><td>130</td><td> 9285000</td><td>58100</td><td>784</td><td>6.8</td><td>2000.167</td></tr>\n",
       "\t<tr><td>Abilene</td><td>2000</td><td>4</td><td> 98</td><td> 9730000</td><td>68600</td><td>785</td><td>6.9</td><td>2000.250</td></tr>\n",
       "\t<tr><td>Abilene</td><td>2000</td><td>5</td><td>141</td><td>10590000</td><td>67300</td><td>794</td><td>6.8</td><td>2000.333</td></tr>\n",
       "\t<tr><td>Abilene</td><td>2000</td><td>6</td><td>156</td><td>13910000</td><td>66900</td><td>780</td><td>6.6</td><td>2000.417</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A tibble: 6 × 9\n",
       "\\begin{tabular}{lllllllll}\n",
       " city & year & month & sales & volume & median & listings & inventory & date\\\\\n",
       " <chr> & <int> & <int> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t Abilene & 2000 & 1 &  72 &  5380000 & 71400 & 701 & 6.3 & 2000.000\\\\\n",
       "\t Abilene & 2000 & 2 &  98 &  6505000 & 58700 & 746 & 6.6 & 2000.083\\\\\n",
       "\t Abilene & 2000 & 3 & 130 &  9285000 & 58100 & 784 & 6.8 & 2000.167\\\\\n",
       "\t Abilene & 2000 & 4 &  98 &  9730000 & 68600 & 785 & 6.9 & 2000.250\\\\\n",
       "\t Abilene & 2000 & 5 & 141 & 10590000 & 67300 & 794 & 6.8 & 2000.333\\\\\n",
       "\t Abilene & 2000 & 6 & 156 & 13910000 & 66900 & 780 & 6.6 & 2000.417\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A tibble: 6 × 9\n",
       "\n",
       "| city &lt;chr&gt; | year &lt;int&gt; | month &lt;int&gt; | sales &lt;dbl&gt; | volume &lt;dbl&gt; | median &lt;dbl&gt; | listings &lt;dbl&gt; | inventory &lt;dbl&gt; | date &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| Abilene | 2000 | 1 |  72 |  5380000 | 71400 | 701 | 6.3 | 2000.000 |\n",
       "| Abilene | 2000 | 2 |  98 |  6505000 | 58700 | 746 | 6.6 | 2000.083 |\n",
       "| Abilene | 2000 | 3 | 130 |  9285000 | 58100 | 784 | 6.8 | 2000.167 |\n",
       "| Abilene | 2000 | 4 |  98 |  9730000 | 68600 | 785 | 6.9 | 2000.250 |\n",
       "| Abilene | 2000 | 5 | 141 | 10590000 | 67300 | 794 | 6.8 | 2000.333 |\n",
       "| Abilene | 2000 | 6 | 156 | 13910000 | 66900 | 780 | 6.6 | 2000.417 |\n",
       "\n"
      ],
      "text/plain": [
       "  city    year month sales volume   median listings inventory date    \n",
       "1 Abilene 2000 1      72    5380000 71400  701      6.3       2000.000\n",
       "2 Abilene 2000 2      98    6505000 58700  746      6.6       2000.083\n",
       "3 Abilene 2000 3     130    9285000 58100  784      6.8       2000.167\n",
       "4 Abilene 2000 4      98    9730000 68600  785      6.9       2000.250\n",
       "5 Abilene 2000 5     141   10590000 67300  794      6.8       2000.333\n",
       "6 Abilene 2000 6     156   13910000 66900  780      6.6       2000.417"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(txhousing)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3) Create a scatterplot of volume verses sales. Afterwards, play around with the alpha and color arguments to clarify information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"Removed 568 rows containing missing values (geom_point).\""
     ]
    },
    {
     "data": {
      "image/png": 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7ksHv8uc5GXfNoFJG926FsYFI7+hvhJIr2ZRXor//VW/wKRTGGbleaKr7yPPr2n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\nYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl <- ggplot(data=txhousing,aes(x = sales,y=volume)) \n",
    "pl + geom_point(alpha = 0.2, color = \"blue\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4) Add a smooth fit line to the scatterplot from above. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = \"cs\")'\n",
      "Warning message:\n",
      "\"Removed 568 rows containing non-finite values (stat_smooth).\"Warning message:\n",
      "\"Removed 568 rows containing missing values (geom_point).\""
     ]
    },
    {
     "data": {
      "image/png": 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zgetT8uQNpf3tK85umP7gfa8mJViHNmdUxP+B4DhMF9l30UtT8uQNpd3ta8ZumP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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pl + geom_point(alpha = 0.2, color = \"blue\") + geom_smooth(color = 'red')"
   ]
  },
  {
   "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
}