{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "awful-desktop",
   "metadata": {},
   "source": [
    "### Marginal Plots\n",
    "\n",
    "A marginal plot is a scatterplot (sometimes a density plot or other bivariate plot) that has histograms, boxplots, or other distribution visualization layers in the margins of the x- and y-axes. \n",
    "\n",
    "It allows studying the relationship between 2 numeric variables. \n",
    "\n",
    "You can use the `ggmarginal()` function to add marginal layers to a plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "satisfied-grenada",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "           window.letsPlotCallQueue = [];\n",
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       "       window.letsPlotCall = function(f) {\n",
       "           window.letsPlotCallQueue.push(f);\n",
       "       };\n",
       "       (function() {\n",
       "           var script = document.createElement(\"script\");\n",
       "           script.type = \"text/javascript\";\n",
       "           script.src = \"https://cdn.jsdelivr.net/gh/JetBrains/lets-plot@v4.0.0/js-package/distr/lets-plot.min.js\";\n",
       "           script.onload = function() {\n",
       "               window.letsPlotCall = function(f) {f();};\n",
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       "               \n",
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       "           script.onerror = function(event) {\n",
       "               window.letsPlotCall = function(f) {};\n",
       "               window.letsPlotCallQueue = [];\n",
       "               var div = document.createElement(\"div\");\n",
       "               div.style.color = 'darkred';\n",
       "               div.textContent = 'Error loading Lets-Plot JS';\n",
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       "           };\n",
       "           var e = document.getElementById(\"tBf78H\");\n",
       "           e.appendChild(script);\n",
       "       })();\n",
       "   </script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%useLatestDescriptors\n",
    "%use lets-plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "tender-tutorial",
   "metadata": {},
   "outputs": [],
   "source": [
    "@file:DependsOn(\"org.apache.commons:commons-math3:3.6.1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "norman-point",
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.apache.commons.math3.distribution.MultivariateNormalDistribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "mexican-terror",
   "metadata": {},
   "outputs": [],
   "source": [
    "val cov0 : Array<DoubleArray> = arrayOf(doubleArrayOf(1.0, -.8),\n",
    "                                        doubleArrayOf(-.8, 1.0))\n",
    "\n",
    "val cov1 : Array<DoubleArray> = arrayOf(doubleArrayOf(10.0, .1),\n",
    "                                        doubleArrayOf(.1, .1))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "revolutionary-munich",
   "metadata": {},
   "outputs": [],
   "source": [
    "val n = 200\n",
    "\n",
    "val means0 : DoubleArray = doubleArrayOf(-2.0, 0.0)\n",
    "val means1 : DoubleArray = doubleArrayOf(0.0, 1.0)\n",
    "\n",
    "val xy0 = MultivariateNormalDistribution(means0, cov0).sample(n)\n",
    "val xy1 = MultivariateNormalDistribution(means1, cov1).sample(n)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "sunrise-skating",
   "metadata": {},
   "outputs": [],
   "source": [
    "val dat = mapOf(\n",
    "    \"x\" to (xy0.map { it[0] } + xy1.map { it[0] }).toList(),\n",
    "    \"y\" to (xy0.map { it[1] } + xy1.map { it[1] }).toList(),\n",
    "    \"c\" to List(n){\"A\"} + List(n){\"B\"},\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "material-village",
   "metadata": {},
   "outputs": [],
   "source": [
    "// The default plot theme and palette.\n",
    "LetsPlot.theme = themeLight()\n",
    "val paletteColors = listOf(\"#394449\", \"#F7C443\")\n",
    "val palette = scaleColorManual(values = paletteColors) + scaleFillManual(values = paletteColors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "passing-suicide",
   "metadata": {},
   "outputs": [
    {
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       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"color\",\n",
       "\"values\":[\"#394449\",\"#F7C443\"]\n",
       "},{\n",
       "\"aesthetic\":\"fill\",\n",
       "\"values\":[\"#394449\",\"#F7C443\"]\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"point\",\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"GWcEma\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val p = letsPlot(dat.toMap()){x = \"x\"; y = \"y\"; color = \"c\"; fill = \"c\"} + geomPoint() + palette\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "straight-locator",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"r2tisq\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Add marginal layers to any side on the plot: \n",
    "// - [l]eft \n",
    "// - [r]ight \n",
    "// - [t]op \n",
    "// - [b]ottom \n",
    "\n",
    "p + ggmarginal(\"tr\", layer = geomHistogram(color = \"white\")) +\n",
    "    ggmarginal(\"lb\", layer = geomDensity(size = 0))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "smooth-lingerie",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"kat13g\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "\"x\":\"x\",\n",
       "\"y\":\"y\",\n",
       "\"color\":\"c\",\n",
       "\"fill\":\"c\"\n",
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       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"kat13g\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Set constant colors to disable the grouping.\n",
    "\n",
    "val pHist = p +\n",
    "            ggmarginal(\"tr\", layer=geomHistogram(fill = \"gray\", color = \"white\")) +\n",
    "            ggmarginal(\"tr\", layer=geomDensity(fill = \"rgba(0,0,0,0)\", color = \"red\"))\n",
    "pHist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "unexpected-puppy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"v214vN\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "\"x\":\"x\",\n",
       "\"y\":\"y\",\n",
       "\"color\":\"c\",\n",
       "\"fill\":\"c\"\n",
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       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"v214vN\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Add marginal boxplots.\n",
    "// Make margins smaller using the parameter `size`.\n",
    "\n",
    "pHist + ggmarginal(\"lb\", size=0.03, layer=geomBoxplot(fill = \"white\", color = \"black\")) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "grave-dragon",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"twhVBF\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
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       "\"y\":\"y\",\n",
       "\"color\":\"c\",\n",
       "\"fill\":\"c\"\n",
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       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"twhVBF\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Combine marginal violin and boxplot.\n",
    "// Make margins much larger.\n",
    "\n",
    "p + ggmarginal(\"rb\", size=0.4, layer=geomViolin(trim = false, color = \"black\")) +\n",
    "    ggmarginal(\"rb\", layer=geomBoxplot(mapping = {group = \"c\"}, fill = \"white\", color = \"white\", \n",
    "                                        alpha = .25, outlierColor = \"red\", width = .2))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "north-worthy",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"SdqVYy\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "\"x\":\"x\",\n",
       "\"y\":\"y\"\n",
       "},\n",
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       "\"name\":\"cartesian\",\n",
       "\"flip\":false\n",
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       "\"data\":{\n",
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       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"fill\":\"..level..\"\n",
       "},\n",
       "\"stat\":\"density2df\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"density2df\",\n",
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       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"SdqVYy\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Show marginal densities on a 2D-density plot.\n",
    "\n",
    "letsPlot(dat) {x = \"x\"; y = \"y\"} + geomDensity2DFilled {fill = \"..level..\"} + coordCartesian() +\n",
    " ggmarginal(\"tr\", layer = geomArea(stat = Stat.density()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bizarre-longer",
   "metadata": {},
   "outputs": [
    {
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     "data": {
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       "    --background: #303030;\n",
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       "\n",
       "table.dataframe th.complex {\n",
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       "    border-right-color: var(--inner-border-color);\n",
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       "\n",
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       "}\n",
       "\n",
       "table.dataframe .expanderSvg {\n",
       "    width: 8px;\n",
       "    height: 8px;\n",
       "    margin-right: 3px;\n",
       "}\n",
       "\n",
       "table.dataframe .expander {\n",
       "    display: flex;\n",
       "    align-items: center;\n",
       "}\n",
       "\n",
       "/* formatting */\n",
       "\n",
       "table.dataframe .null {\n",
       "    color: var(--text-color-pale);\n",
       "}\n",
       "\n",
       "table.dataframe .structural {\n",
       "    color: var(--text-color-medium);\n",
       "    font-weight: bold;\n",
       "}\n",
       "\n",
       "table.dataframe .dataFrameCaption {\n",
       "    font-weight: bold;\n",
       "}\n",
       "\n",
       "table.dataframe .numbers {\n",
       "    color: var(--text-color-dark);\n",
       "}\n",
       "\n",
       "table.dataframe td:hover .formatted .structural, .null {\n",
       "    color: var(--text-color-dark);\n",
       "}\n",
       "\n",
       "table.dataframe tr:hover .formatted .structural, .null {\n",
       "    color: var(--text-color-dark);\n",
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       "\n",
       "\n",
       "                </style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "// A marginal plot with a significant number of groups on margins. \n",
    "\n",
    "\n",
    "%use dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "stainless-throat",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/kotlindataframe+json": "{\"nrow\":3,\"ncol\":12,\"columns\":[\"untitled\",\"manufacturer\",\"model\",\"displ\",\"year\",\"cyl\",\"trans\",\"drv\",\"cty\",\"hwy\",\"fl\",\"class\"],\"kotlin_dataframe\":[{\"untitled\":1,\"manufacturer\":\"audi\",\"model\":\"a4\",\"displ\":1.8,\"year\":1999,\"cyl\":4,\"trans\":\"auto(l5)\",\"drv\":\"f\",\"cty\":18,\"hwy\":29,\"fl\":\"p\",\"class\":\"compact\"},{\"untitled\":2,\"manufacturer\":\"audi\",\"model\":\"a4\",\"displ\":1.8,\"year\":1999,\"cyl\":4,\"trans\":\"manual(m5)\",\"drv\":\"f\",\"cty\":21,\"hwy\":29,\"fl\":\"p\",\"class\":\"compact\"},{\"untitled\":3,\"manufacturer\":\"audi\",\"model\":\"a4\",\"displ\":2.0,\"year\":2008,\"cyl\":4,\"trans\":\"manual(m6)\",\"drv\":\"f\",\"cty\":20,\"hwy\":31,\"fl\":\"p\",\"class\":\"compact\"}]}",
      "text/html": [
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       "}\n",
       "\n",
       ":root[theme=\"dark\"], :root [data-jp-theme-light=\"false\"], .dataframe_dark{\n",
       "    --background: #303030;\n",
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       "    --link-color-pale: #97e1fb;\n",
       "    --link-hover: #00688e;\n",
       "}\n",
       "\n",
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       "    color: var(--text-color-dark);\n",
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       "\n",
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       "\n",
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       "    border: 1px solid var(--background);\n",
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       "\n",
       "table.dataframe .expander {\n",
       "    display: flex;\n",
       "    align-items: center;\n",
       "}\n",
       "\n",
       "/* formatting */\n",
       "\n",
       "table.dataframe .null {\n",
       "    color: var(--text-color-pale);\n",
       "}\n",
       "\n",
       "table.dataframe .structural {\n",
       "    color: var(--text-color-medium);\n",
       "    font-weight: bold;\n",
       "}\n",
       "\n",
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       "    font-weight: bold;\n",
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       "\n",
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       "\n",
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       "<table class=\"dataframe\" id=\"df_-905969664\"></table>\n",
       "\n",
       "<p class=\"dataframe_description\">DataFrame: rowsCount = 3, columnsCount = 12</p>\n",
       "        </body>\n",
       "        <script>\n",
       "            \n",
       "/*<!--*/\n",
       "call_DataFrame(function() { DataFrame.addTable({ cols: [{ name: \"<span title=\\\"untitled: Int\\\">untitled</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">3</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"manufacturer: String\\\">manufacturer</span>\", children: [], rightAlign: false, values: [\"audi\",\"audi\",\"audi\"] }, \n",
       "{ name: \"<span title=\\\"model: String\\\">model</span>\", children: [], rightAlign: false, values: [\"a4\",\"a4\",\"a4\"] }, \n",
       "{ name: \"<span title=\\\"displ: Double\\\">displ</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1.8</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1.8</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2.0</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"year: Int\\\">year</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1999</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1999</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2008</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"cyl: Int\\\">cyl</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"trans: String\\\">trans</span>\", children: [], rightAlign: false, values: [\"auto(l5)\",\"manual(m5)\",\"manual(m6)\"] }, \n",
       "{ name: \"<span title=\\\"drv: String\\\">drv</span>\", children: [], rightAlign: false, values: [\"f\",\"f\",\"f\"] }, \n",
       "{ name: \"<span title=\\\"cty: Int\\\">cty</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">18</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">21</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">20</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"hwy: Int\\\">hwy</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">29</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">29</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">31</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"fl: String\\\">fl</span>\", children: [], rightAlign: false, values: [\"p\",\"p\",\"p\"] }, \n",
       "{ name: \"<span title=\\\"class: String\\\">class</span>\", children: [], rightAlign: false, values: [\"compact\",\"compact\",\"compact\"] }, \n",
       "], id: -905969664, rootId: -905969664, totalRows: 3 } ) });\n",
       "/*-->*/\n",
       "\n",
       "call_DataFrame(function() { DataFrame.renderTable(-905969664) });\n",
       "\n",
       "\n",
       "        </script>\n",
       "        </html>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "var mpg = DataFrame.readCSV(\"https://raw.githubusercontent.com/JetBrains/lets-plot-kotlin/master/docs/examples/data/mpg.csv\")\n",
    "mpg.head(3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "combined-diagram",
   "metadata": {},
   "outputs": [
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       "\"hwy\":[29.0,29.0,31.0,30.0,26.0,26.0,27.0,26.0,25.0,28.0,27.0,25.0,25.0,25.0,25.0,24.0,25.0,23.0,20.0,15.0,20.0,17.0,17.0,26.0,23.0,26.0,25.0,24.0,19.0,14.0,15.0,17.0,27.0,30.0,26.0,29.0,26.0,24.0,24.0,22.0,22.0,24.0,24.0,17.0,22.0,21.0,23.0,23.0,19.0,18.0,17.0,17.0,19.0,19.0,12.0,17.0,15.0,17.0,17.0,12.0,17.0,16.0,18.0,15.0,16.0,12.0,17.0,17.0,16.0,12.0,15.0,16.0,17.0,15.0,17.0,17.0,18.0,17.0,19.0,17.0,19.0,19.0,17.0,17.0,17.0,16.0,16.0,17.0,15.0,17.0,26.0,25.0,26.0,24.0,21.0,22.0,23.0,22.0,20.0,33.0,32.0,32.0,29.0,32.0,34.0,36.0,36.0,29.0,26.0,27.0,30.0,31.0,26.0,26.0,28.0,26.0,29.0,28.0,27.0,24.0,24.0,24.0,22.0,19.0,20.0,17.0,12.0,19.0,18.0,14.0,15.0,18.0,18.0,15.0,17.0,16.0,18.0,17.0,19.0,19.0,17.0,29.0,27.0,31.0,32.0,27.0,26.0,26.0,25.0,25.0,17.0,17.0,20.0,18.0,26.0,26.0,27.0,28.0,25.0,25.0,24.0,27.0,25.0,26.0,23.0,26.0,26.0,26.0,26.0,25.0,27.0,25.0,27.0,20.0,20.0,19.0,17.0,20.0,17.0,29.0,27.0,31.0,31.0,26.0,26.0,28.0,27.0,29.0,31.0,31.0,26.0,26.0,27.0,30.0,33.0,35.0,37.0,35.0,15.0,18.0,20.0,20.0,22.0,17.0,19.0,18.0,20.0,29.0,26.0,29.0,29.0,24.0,44.0,29.0,26.0,29.0,29.0,29.0,29.0,23.0,24.0,44.0,41.0,29.0,26.0,28.0,29.0,29.0,29.0,28.0,29.0,26.0,26.0,26.0],\n",
       "\"manufacturer\":[\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"audi\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"chevrolet\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"dodge\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"ford\",\"honda\",\"honda\",\"honda\",\"honda\",\"honda\",\"honda\",\"honda\",\"honda\",\"honda\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"hyundai\",\"jeep\",\"jeep\",\"jeep\",\"jeep\",\"jeep\",\"jeep\",\"jeep\",\"jeep\",\"land rover\",\"land rover\",\"land rover\",\"land rover\",\"lincoln\",\"lincoln\",\"lincoln\",\"mercury\",\"mercury\",\"mercury\",\"mercury\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"nissan\",\"pontiac\",\"pontiac\",\"pontiac\",\"pontiac\",\"pontiac\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"subaru\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"toyota\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\"]\n",
       "},\n",
       "\"ggsize\":{\n",
       "\"width\":900.0,\n",
       "\"height\":700.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"color\":\"black\",\n",
       "\"shape\":21.0,\n",
       "\"size\":7.0,\n",
       "\"alpha\":0.5,\n",
       "\"position\":\"jitter\",\n",
       "\"geom\":\"point\",\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"name\":\"light\",\n",
       "\"plot_background\":{\n",
       "\"fill\":\"#eaeaea\",\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_background\":{\n",
       "\"fill\":\"#eaeaea\",\n",
       "\"blank\":false\n",
       "}\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"K6ULka\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val plotSettings = ggsize(900, 700) +\n",
    "                   theme(plotBackground = elementRect(fill = \"#eaeaea\"), \n",
    "                         legendBackground = elementRect(fill = \"#eaeaea\"))\n",
    "\n",
    "(letsPlot(mpg.toMap()) {x = \"cty\"; y = \"hwy\"; fill = \"manufacturer\"}\n",
    "    + geomPoint( size = 7, shape = 21, alpha = .5, color = \"black\", position=positionJitter())\n",
    "    + ggmarginal(\"tr\", size = 0.3, \n",
    "                 layer = geomBoxplot(width=0.5) {\n",
    "                     fill = asDiscrete(\"manufacturer\", orderBy = \"..lower..\")\n",
    "                 })\n",
    "    + plotSettings) \n",
    "                   "
   ]
  }
 ],
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