docs/examples/jupyter-notebooks/y_orientation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "proud-butler",
   "metadata": {},
   "source": [
    "### The layer `orientation` property\n",
    "\n",
    "Some geoms treat each axis differently and, thus, can thus have two orientations.\n",
    "\n",
    "The `orientation` parameter specifies the axis that the layer' stat and geom should run along (x-axis by default). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "humanitarian-german",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"KT1XjV\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"library\">\n",
       "       if(!window.letsPlotCallQueue) {\n",
       "           window.letsPlotCallQueue = [];\n",
       "       }; \n",
       "       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@v2.5.1/js-package/distr/lets-plot.min.js\";\n",
       "           script.onload = function() {\n",
       "               window.letsPlotCall = function(f) {f();};\n",
       "               window.letsPlotCallQueue.forEach(function(f) {f();});\n",
       "               window.letsPlotCallQueue = [];\n",
       "               \n",
       "               \n",
       "           };\n",
       "           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",
       "               document.getElementById(\"KT1XjV\").appendChild(div);\n",
       "           };\n",
       "           var e = document.getElementById(\"KT1XjV\");\n",
       "           e.appendChild(script);\n",
       "       })();\n",
       "   </script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%useLatestDescriptors\n",
    "%use lets-plot\n",
    "// %use krangl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "registered-chance",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lets-Plot Kotlin API v.4.1.1. Frontend: Notebook with dynamically loaded JS. Lets-Plot JS v.2.5.1."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LetsPlot.getInfo() // This prevents Krangl from loading an obsolete version of Lets-Plot classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "thousand-filter",
   "metadata": {},
   "outputs": [],
   "source": [
    "%use krangl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "guilty-indian",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<html><body><table><tr><th style=\"text-align:left\"></th><th style=\"text-align:left\">manufacturer</th><th style=\"text-align:left\">model</th><th style=\"text-align:left\">displ</th><th style=\"text-align:left\">year</th><th style=\"text-align:left\">cyl</th><th style=\"text-align:left\">trans</th><th style=\"text-align:left\">drv</th><th style=\"text-align:left\">cty</th><th style=\"text-align:left\">hwy</th><th style=\"text-align:left\">fl</th><th style=\"text-align:left\">class</th></tr><tr><td style=\"text-align:left\" title=\"1\">1</td><td style=\"text-align:left\" title=\"audi\">audi</td><td style=\"text-align:left\" title=\"a4\">a4</td><td style=\"text-align:left\" title=\"1.8\">1.8</td><td style=\"text-align:left\" title=\"1999\">1999</td><td style=\"text-align:left\" title=\"4\">4</td><td style=\"text-align:left\" title=\"auto(l5)\">auto(l5)</td><td style=\"text-align:left\" title=\"f\">f</td><td style=\"text-align:left\" title=\"18\">18</td><td style=\"text-align:left\" title=\"29\">29</td><td style=\"text-align:left\" title=\"p\">p</td><td style=\"text-align:left\" title=\"compact\">compact</td></tr><tr><td style=\"text-align:left\" title=\"2\">2</td><td style=\"text-align:left\" title=\"audi\">audi</td><td style=\"text-align:left\" title=\"a4\">a4</td><td style=\"text-align:left\" title=\"1.8\">1.8</td><td style=\"text-align:left\" title=\"1999\">1999</td><td style=\"text-align:left\" title=\"4\">4</td><td style=\"text-align:left\" title=\"manual(m5)\">manual(m5)</td><td style=\"text-align:left\" title=\"f\">f</td><td style=\"text-align:left\" title=\"21\">21</td><td style=\"text-align:left\" title=\"29\">29</td><td style=\"text-align:left\" title=\"p\">p</td><td style=\"text-align:left\" title=\"compact\">compact</td></tr><tr><td style=\"text-align:left\" title=\"3\">3</td><td style=\"text-align:left\" title=\"audi\">audi</td><td style=\"text-align:left\" title=\"a4\">a4</td><td style=\"text-align:left\" title=\"2.0\">2.0</td><td style=\"text-align:left\" title=\"2008\">2008</td><td style=\"text-align:left\" title=\"4\">4</td><td style=\"text-align:left\" title=\"manual(m6)\">manual(m6)</td><td style=\"text-align:left\" title=\"f\">f</td><td style=\"text-align:left\" title=\"20\">20</td><td style=\"text-align:left\" title=\"31\">31</td><td style=\"text-align:left\" title=\"p\">p</td><td style=\"text-align:left\" title=\"compact\">compact</td></tr></table><p>Shape: 3 x 12. \n",
       "</p></body></html>"
      ]
     },
     "execution_count": 4,
     "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": 5,
   "id": "ordinary-friend",
   "metadata": {},
   "outputs": [],
   "source": [
    "val base = letsPlot(mpg.toMap()) + ggsize(800, 300)\n",
    "val manufacturerMapping = asDiscrete(\"manufacturer\", orderBy = \"..count..\")\n",
    "val hideXLabel = theme(axisTitleX = \"blank\")\n",
    "val hideYLabel = theme(axisTitleY = \"blank\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pursuant-stamp",
   "metadata": {},
   "source": [
    "### geomBar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cleared-brooklyn",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"IVyIHR\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"ggsize\":{\n",
       "\"width\":800.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"x\":\"@as_discrete@manufacturer\",\n",
       "\"fill\":\"class\"\n",
       "},\n",
       "\"stat\":\"count\",\n",
       "\"color\":\"white\",\n",
       "\"position\":\"stack\",\n",
       "\"geom\":\"bar\",\n",
       "\"data_meta\":{\n",
       "\"mapping_annotations\":[{\n",
       "\"aes\":\"x\",\n",
       "\"annotation\":\"as_discrete\",\n",
       "\"parameters\":{\n",
       "\"label\":\"manufacturer\",\n",
       "\"order_by\":\"..count..\"\n",
       "}\n",
       "}]\n",
       "},\n",
       "\"data\":{\n",
       "\"..count..\":[15.0,2.0,4.0,12.0,14.0,3.0,5.0,7.0,7.0,5.0,7.0,7.0,9.0,7.0,9.0,8.0,4.0,3.0,4.0,4.0,6.0,8.0,5.0,11.0,19.0,7.0,7.0,9.0,9.0,7.0,4.0,6.0],\n",
       "\"class\":[\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"2seater\",\"minivan\",\"pickup\",\"pickup\",\"pickup\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\"],\n",
       "\"@as_discrete@manufacturer\":[\"audi\",\"nissan\",\"subaru\",\"toyota\",\"volkswagen\",\"audi\",\"chevrolet\",\"hyundai\",\"nissan\",\"pontiac\",\"toyota\",\"volkswagen\",\"chevrolet\",\"dodge\",\"ford\",\"jeep\",\"land rover\",\"lincoln\",\"mercury\",\"nissan\",\"subaru\",\"toyota\",\"chevrolet\",\"dodge\",\"dodge\",\"ford\",\"toyota\",\"ford\",\"honda\",\"hyundai\",\"subaru\",\"volkswagen\"]\n",
       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"axis_title_x\":\"blank\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"IVyIHR\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// orientation \"x\" (default) : \"manufacturer\" is mapped to the x-axis.\n",
    "\n",
    "val orientationX = base + geomBar(color = \"white\") {\n",
    "    x = manufacturerMapping\n",
    "    fill = \"class\"\n",
    "}\n",
    "orientationX + hideXLabel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "experimental-storm",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"TmcIO1\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "},\n",
       "\"coord\":{\n",
       "\"name\":\"flip\",\n",
       "\"flip\":true\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"ggsize\":{\n",
       "\"width\":800.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"x\":\"@as_discrete@manufacturer\",\n",
       "\"fill\":\"class\"\n",
       "},\n",
       "\"stat\":\"count\",\n",
       "\"color\":\"white\",\n",
       "\"position\":\"stack\",\n",
       "\"geom\":\"bar\",\n",
       "\"data_meta\":{\n",
       "\"mapping_annotations\":[{\n",
       "\"aes\":\"x\",\n",
       "\"annotation\":\"as_discrete\",\n",
       "\"parameters\":{\n",
       "\"label\":\"manufacturer\",\n",
       "\"order_by\":\"..count..\"\n",
       "}\n",
       "}]\n",
       "},\n",
       "\"data\":{\n",
       "\"..count..\":[15.0,2.0,4.0,12.0,14.0,3.0,5.0,7.0,7.0,5.0,7.0,7.0,9.0,7.0,9.0,8.0,4.0,3.0,4.0,4.0,6.0,8.0,5.0,11.0,19.0,7.0,7.0,9.0,9.0,7.0,4.0,6.0],\n",
       "\"class\":[\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"2seater\",\"minivan\",\"pickup\",\"pickup\",\"pickup\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\"],\n",
       "\"@as_discrete@manufacturer\":[\"audi\",\"nissan\",\"subaru\",\"toyota\",\"volkswagen\",\"audi\",\"chevrolet\",\"hyundai\",\"nissan\",\"pontiac\",\"toyota\",\"volkswagen\",\"chevrolet\",\"dodge\",\"ford\",\"jeep\",\"land rover\",\"lincoln\",\"mercury\",\"nissan\",\"subaru\",\"toyota\",\"chevrolet\",\"dodge\",\"dodge\",\"ford\",\"toyota\",\"ford\",\"honda\",\"hyundai\",\"subaru\",\"volkswagen\"]\n",
       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"axis_title_x\":\"blank\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"TmcIO1\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Same but flipped coordinate system.\n",
    "\n",
    "orientationX + coordFlip() + hideXLabel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "referenced-cliff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"NxzKfv\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"ggsize\":{\n",
       "\"width\":800.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"y\":\"@as_discrete@manufacturer\",\n",
       "\"fill\":\"class\"\n",
       "},\n",
       "\"stat\":\"count\",\n",
       "\"orientation\":\"y\",\n",
       "\"color\":\"white\",\n",
       "\"position\":\"stack\",\n",
       "\"geom\":\"bar\",\n",
       "\"data_meta\":{\n",
       "\"mapping_annotations\":[{\n",
       "\"aes\":\"y\",\n",
       "\"annotation\":\"as_discrete\",\n",
       "\"parameters\":{\n",
       "\"label\":\"manufacturer\",\n",
       "\"order_by\":\"..count..\"\n",
       "}\n",
       "}]\n",
       "},\n",
       "\"data\":{\n",
       "\"..count..\":[15.0,2.0,4.0,12.0,14.0,3.0,5.0,7.0,7.0,5.0,7.0,7.0,9.0,7.0,9.0,8.0,4.0,3.0,4.0,4.0,6.0,8.0,5.0,11.0,19.0,7.0,7.0,9.0,9.0,7.0,4.0,6.0],\n",
       "\"class\":[\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"2seater\",\"minivan\",\"pickup\",\"pickup\",\"pickup\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\"],\n",
       "\"@as_discrete@manufacturer\":[\"audi\",\"nissan\",\"subaru\",\"toyota\",\"volkswagen\",\"audi\",\"chevrolet\",\"hyundai\",\"nissan\",\"pontiac\",\"toyota\",\"volkswagen\",\"chevrolet\",\"dodge\",\"ford\",\"jeep\",\"land rover\",\"lincoln\",\"mercury\",\"nissan\",\"subaru\",\"toyota\",\"chevrolet\",\"dodge\",\"dodge\",\"ford\",\"toyota\",\"ford\",\"honda\",\"hyundai\",\"subaru\",\"volkswagen\"]\n",
       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"axis_title_y\":\"blank\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"NxzKfv\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "// Orientation \"y\".\n",
    "// The \"manufacturer\" is mapped to the y-axis.\n",
    "\n",
    "val baseY = base + hideYLabel\n",
    "baseY + geomBar(color = \"white\", orientation=\"y\") {\n",
    "    y = manufacturerMapping\n",
    "    fill = \"class\"\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prime-looking",
   "metadata": {},
   "source": [
    "### geomBoxplot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "combined-kingston",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"IiHKrm\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"ggsize\":{\n",
       "\"width\":800.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"x\":\"cty\",\n",
       "\"y\":\"manufacturer\"\n",
       "},\n",
       "\"stat\":\"boxplot\",\n",
       "\"orientation\":\"y\",\n",
       "\"width\":0.7,\n",
       "\"position\":\"dodge\",\n",
       "\"geom\":\"boxplot\",\n",
       "\"data\":{\n",
       "\"..middle..\":[17.5,13.0,11.0,13.0,19.0,17.0,14.0,19.0,18.0,NaN,NaN,NaN,21.0,NaN,15.0,NaN,NaN,24.0,18.5,14.0,11.5],\n",
       "\"..upper..\":[18.5,15.0,11.5,13.5,19.0,18.0,15.0,20.0,21.0,NaN,NaN,NaN,21.0,NaN,16.5,NaN,NaN,25.0,19.5,15.0,12.0],\n",
       "\"..ymax..\":[21.0,18.0,12.0,14.0,23.0,18.0,18.0,21.0,28.0,NaN,NaN,NaN,22.0,NaN,19.0,NaN,NaN,26.0,21.0,17.0,12.0],\n",
       "\"..lower..\":[16.0,11.0,11.0,13.0,15.0,16.0,13.0,19.0,15.0,NaN,NaN,NaN,18.5,NaN,13.5,NaN,NaN,24.0,18.0,12.0,11.0],\n",
       "\"cty\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,33.0,35.0,29.0,NaN,22.0,NaN,28.0,21.0,NaN,NaN,NaN,NaN],\n",
       "\"..ymin..\":[15.0,9.0,11.0,13.0,12.0,16.0,11.0,18.0,11.0,NaN,NaN,NaN,16.0,NaN,11.0,NaN,NaN,23.0,16.0,9.0,11.0],\n",
       "\"manufacturer\":[\"audi\",\"dodge\",\"lincoln\",\"mercury\",\"nissan\",\"pontiac\",\"ford\",\"subaru\",\"toyota\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"volkswagen\",\"chevrolet\",\"chevrolet\",\"honda\",\"honda\",\"honda\",\"hyundai\",\"jeep\",\"land rover\"]\n",
       "}\n",
       "}],\n",
       "\"theme\":{\n",
       "\"axis_title_y\":\"blank\"\n",
       "}\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"IiHKrm\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "baseY + geomBoxplot(width = 0.7, orientation = \"y\") {\n",
    "    y = \"manufacturer\"\n",
    "    x = \"cty\" \n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "interpreted-mileage",
   "metadata": {},
   "source": [
    "### `geomViolin()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "elementary-dutch",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"8QNuTW\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"x\":\"cty\",\n",
       "\"y\":\"drv\",\n",
       "\"fill\":\"drv\"\n",
       "},\n",
       "\"stat\":\"ydensity\",\n",
       "\"orientation\":\"y\",\n",
       "\"trim\":false,\n",
       "\"position\":\"dodge\",\n",
       "\"geom\":\"violin\",\n",
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       "\"..upper..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,21.0,NaN,16.0,15.0],\n",
       "\"..ymax..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,25.0,NaN,20.0,18.0],\n",
       "\"..lower..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,18.0,NaN,13.0,12.0],\n",
       "\"cty\":[11.0,28.0,26.0,26.0,28.0,26.0,33.0,35.0,29.0,NaN,21.0,NaN,NaN],\n",
       "\"drv\":[\"f\",\"f\",\"f\",\"f\",\"f\",\"f\",\"f\",\"f\",\"f\",\"f\",\"4\",\"4\",\"r\"],\n",
       "\"..ymin..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,15.0,NaN,9.0,11.0]\n",
       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"8QNuTW\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letsPlot(mpg.toMap()) + geomViolin(trim = false, orientation = \"y\") { y=\"drv\"; x = \"cty\"; fill = \"drv\"} +\n",
    "                        geomBoxplot(fill = \"white\", alpha =  0.5, width = 0.3, orientation = \"y\") { \n",
    "                            y = \"drv\"\n",
    "                            x = \"cty\"  \n",
    "                        }\n",
    "                        "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "blond-gallery",
   "metadata": {},
   "source": [
    "## Continuous variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "homeless-madagascar",
   "metadata": {},
   "outputs": [],
   "source": [
    "@file:DependsOn(\"org.apache.commons:commons-math3:3.6.1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "virtual-minimum",
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.apache.commons.math3.distribution.MultivariateNormalDistribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "secret-vaccine",
   "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": 14,
   "id": "basic-teaching",
   "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": 15,
   "id": "hearing-prerequisite",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "},\n",
       "\"ggsize\":{\n",
       "\"width\":600.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"point\",\n",
       "\"data\":{\n",
       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"VekGSa\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "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",
    "\n",
    "val p = letsPlot(dat) {x = \"x\"; y = \"y\"; color = \"c\"} + ggsize(600,300) +\n",
    "        geomPoint()\n",
    "p"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "photographic-monster",
   "metadata": {},
   "source": [
    "### `geomDensity()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "numeric-turtle",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"PQCIeG\"></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",
       "},\n",
       "\"data\":{\n",
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       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"PQCIeG\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomDensity(size = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "opened-glance",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"Uyjic1\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomDensity(size = 2, orientation = \"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "banner-mustang",
   "metadata": {},
   "source": [
    "### `geomHistogram()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "jewish-fluid",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"RMHGXS\"></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",
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       "           var plotContainer = document.getElementById(\"RMHGXS\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
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       "   </script>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomHistogram(fill = \"rgba(0,0,0,0)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "neural-saint",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "},\n",
       "\"ggsize\":{\n",
       "\"width\":600.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"point\",\n",
       "\"data\":{\n",
       "}\n",
       "},{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"bin\",\n",
       "\"orientation\":\"y\",\n",
       "\"position\":\"stack\",\n",
       "\"geom\":\"histogram\",\n",
       "\"fill\":\"rgba(0,0,0,0)\",\n",
       "\"data\":{\n",
       "\"c\":[\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\"],\n",
       "\"x\":[1.0,1.0,1.0,1.0,2.0,3.0,4.0,3.0,6.0,7.0,6.0,12.0,8.0,9.0,12.0,15.0,20.0,15.0,15.0,6.0,14.0,13.0,11.0,5.0,5.0,2.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,14.0,34.0,42.0,56.0,38.0,8.0,3.0,3.0,0.0,0.0,0.0,0.0],\n",
       "\"y\":[-3.183392332679905,-2.981365577017536,-2.779338821355166,-2.577312065692797,-2.375285310030428,-2.1732585543680583,-1.971231798705689,-1.7692050430433197,-1.5671782873809503,-1.365151531718581,-1.1631247760562116,-0.9610980203938424,-0.7590712647314732,-0.5570445090691036,-0.35501775340673447,-0.15299099774436486,0.0490357579180043,0.25106251358037346,0.45308926924274306,0.6551160249051122,0.8571427805674818,1.059169536229851,1.2611962918922202,1.4632230475545893,1.6652498032169585,1.8672765588793285,2.0693033145416977,2.271330070204067,2.473356825866436,2.675383581528805,-3.183392332679905,-2.981365577017536,-2.779338821355166,-2.577312065692797,-2.375285310030428,-2.1732585543680583,-1.971231798705689,-1.7692050430433197,-1.5671782873809503,-1.365151531718581,-1.1631247760562116,-0.9610980203938424,-0.7590712647314732,-0.5570445090691036,-0.35501775340673447,-0.15299099774436486,0.0490357579180043,0.25106251358037346,0.45308926924274306,0.6551160249051122,0.8571427805674818,1.059169536229851,1.2611962918922202,1.4632230475545893,1.6652498032169585,1.8672765588793285,2.0693033145416977,2.271330070204067,2.473356825866436,2.675383581528805]\n",
       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"3pRdoF\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomHistogram(fill = \"rgba(0,0,0,0)\", orientation = \"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "controversial-james",
   "metadata": {},
   "source": [
    "### `geomFreqpoly()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "fifteen-latin",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"t2yFf8\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
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       "\"data\":{\n",
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       "           var plotContainer = document.getElementById(\"t2yFf8\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
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      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomFreqpoly(size = 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "brief-tolerance",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "},\n",
       "\"ggsize\":{\n",
       "\"width\":600.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"point\",\n",
       "\"data\":{\n",
       "}\n",
       "},{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"bin\",\n",
       "\"orientation\":\"y\",\n",
       "\"size\":2.0,\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"line\",\n",
       "\"data\":{\n",
       "\"c\":[\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"A\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\",\"B\"],\n",
       "\"x\":[1.0,1.0,1.0,1.0,2.0,3.0,4.0,3.0,6.0,7.0,6.0,12.0,8.0,9.0,12.0,15.0,20.0,15.0,15.0,6.0,14.0,13.0,11.0,5.0,5.0,2.0,1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2.0,14.0,34.0,42.0,56.0,38.0,8.0,3.0,3.0,0.0,0.0,0.0,0.0],\n",
       "\"y\":[-3.183392332679905,-2.981365577017536,-2.779338821355166,-2.577312065692797,-2.375285310030428,-2.1732585543680583,-1.971231798705689,-1.7692050430433197,-1.5671782873809503,-1.365151531718581,-1.1631247760562116,-0.9610980203938424,-0.7590712647314732,-0.5570445090691036,-0.35501775340673447,-0.15299099774436486,0.0490357579180043,0.25106251358037346,0.45308926924274306,0.6551160249051122,0.8571427805674818,1.059169536229851,1.2611962918922202,1.4632230475545893,1.6652498032169585,1.8672765588793285,2.0693033145416977,2.271330070204067,2.473356825866436,2.675383581528805,-3.183392332679905,-2.981365577017536,-2.779338821355166,-2.577312065692797,-2.375285310030428,-2.1732585543680583,-1.971231798705689,-1.7692050430433197,-1.5671782873809503,-1.365151531718581,-1.1631247760562116,-0.9610980203938424,-0.7590712647314732,-0.5570445090691036,-0.35501775340673447,-0.15299099774436486,0.0490357579180043,0.25106251358037346,0.45308926924274306,0.6551160249051122,0.8571427805674818,1.059169536229851,1.2611962918922202,1.4632230475545893,1.6652498032169585,1.8672765588793285,2.0693033145416977,2.271330070204067,2.473356825866436,2.675383581528805]\n",
       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"GzwaPj\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomFreqpoly(size = 2, orientation = \"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "answering-friendly",
   "metadata": {},
   "source": [
    "### `geomSmooth()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "unique-consciousness",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"CpkEMP\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
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       "\"x\":\"x\",\n",
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       "},\n",
       "\"data\":{\n",
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       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"CpkEMP\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomSmooth()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "individual-selling",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"NWiCI2\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomSmooth(orientation = \"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "alternate-violence",
   "metadata": {},
   "source": [
    "### `geomBoxplot()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "certain-olive",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"F6fkep\"></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",
       "},\n",
       "\"data\":{\n",
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       "},\n",
       "\"ggsize\":{\n",
       "\"width\":600.0,\n",
       "\"height\":300.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"point\",\n",
       "\"data\":{\n",
       "}\n",
       "},{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"boxplot\",\n",
       "\"color\":\"black\",\n",
       "\"x\":-10.0,\n",
       "\"position\":\"dodge\",\n",
       "\"geom\":\"boxplot\",\n",
       "\"data\":{\n",
       "\"..middle..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,0.7765845011623187],\n",
       "\"..upper..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,1.0971569267808294],\n",
       "\"..x..\":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],\n",
       "\"..ymax..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,2.6412835240443933],\n",
       "\"..lower..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,0.008478114348914378],\n",
       "\"y\":[-2.391526273682267,-1.9079727248236624,-1.772635809344339,-2.267393465756497,-2.16635660601926,-2.053530050926925,-2.4755133256526562,-1.872965810698164,-2.1404649498544437,-2.0238454471407206,-1.6845067498501896,-2.505959429869678,-2.718143664243563,-1.656979710436063,-1.8617431158579758,-3.149292275195492,-2.9389404839732682,-1.625779912691197,NaN],\n",
       "\"..ymin..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,-1.58185377641718]\n",
       "}\n",
       "},{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"boxplot\",\n",
       "\"orientation\":\"y\",\n",
       "\"color\":\"black\",\n",
       "\"y\":-3.0,\n",
       "\"position\":\"dodge\",\n",
       "\"geom\":\"boxplot\",\n",
       "\"data\":{\n",
       "\"..middle..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,-1.517392590297997],\n",
       "\"..upper..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,0.3453213694257402],\n",
       "\"..x..\":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0],\n",
       "\"..ymax..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,4.420878029505543],\n",
       "\"..lower..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,-2.4560858190003794],\n",
       "\"x\":[4.720284391522764,5.59735849865201,-7.163905739913419,5.027366055061018,-8.475818122092468,5.16292028150107,9.456722662316428,4.968166389633092,4.736353126321572,5.457541611272286,4.744187239857836,4.7879221578904145,5.041369419156643,NaN],\n",
       "\"..ymin..\":[NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,NaN,-6.541022496305511]\n",
       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"F6fkep\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomBoxplot(x = -10, color = \"black\") +\n",
    "    geomBoxplot(y = -3, color = \"black\", orientation = \"y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "european-forty",
   "metadata": {},
   "source": [
    "### `geomViolin()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "expanded-protection",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"N5wJki\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
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       "},\n",
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       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"N5wJki\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomViolin(x = -10, color = \"black\", alpha = 0) +\n",
    "    geomViolin(y = -3, color = \"black\", alpha = 0, orientation = \"y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "split-rwanda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"CMs1zx\"></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",
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       "}\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"CMs1zx\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + geomViolin(mapping = {fill = \"c\"}, y = -2, color = \"black\", \n",
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    "               orientation=\"y\", trim = false)"
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