{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8abf1a99-2b6f-499b-9680-da1a9df9c21b",
   "metadata": {},
   "source": [
    "# Customize Legend Appearance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6a81b6d2-6a4b-4448-8927-635122e0492a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:42.944443Z",
     "iopub.status.busy": "2024-11-01T20:11:42.944355Z",
     "iopub.status.idle": "2024-11-01T20:11:43.266184Z",
     "shell.execute_reply": "2024-11-01T20:11:43.265737Z"
    }
   },
   "outputs": [],
   "source": [
    "from IPython.display import Image\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "from lets_plot import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4fa2ab2d-c35e-4957-838f-a72969bd1ca5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.267490Z",
     "iopub.status.busy": "2024-11-01T20:11:43.267379Z",
     "iopub.status.idle": "2024-11-01T20:11:43.269869Z",
     "shell.execute_reply": "2024-11-01T20:11:43.269632Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <div id=\"TUF3wn\"></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@v4.5.1/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",
       "                    script.onerror = function(event) {\n",
       "                        window.letsPlotCall = function(f) {};    // noop\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(\"TUF3wn\").appendChild(div);\n",
       "                    };\n",
       "                    var e = document.getElementById(\"TUF3wn\");\n",
       "                    e.appendChild(script);\n",
       "                })()\n",
       "            </script>\n",
       "            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LetsPlot.setup_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e9eb4d18-e02d-41f9-afe6-f5530aae3d7b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.270744Z",
     "iopub.status.busy": "2024-11-01T20:11:43.270671Z",
     "iopub.status.idle": "2024-11-01T20:11:43.274991Z",
     "shell.execute_reply": "2024-11-01T20:11:43.274757Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(Image(\"images/theme_legend_scheme.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b1fe0b5c-22b0-4999-8bce-a230f9273ca3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.275853Z",
     "iopub.status.busy": "2024-11-01T20:11:43.275780Z",
     "iopub.status.idle": "2024-11-01T20:11:43.425878Z",
     "shell.execute_reply": "2024-11-01T20:11:43.425515Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(234, 12)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>manufacturer</th>\n",
       "      <th>model</th>\n",
       "      <th>displ</th>\n",
       "      <th>year</th>\n",
       "      <th>cyl</th>\n",
       "      <th>trans</th>\n",
       "      <th>drv</th>\n",
       "      <th>cty</th>\n",
       "      <th>hwy</th>\n",
       "      <th>fl</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>audi</td>\n",
       "      <td>a4</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1999</td>\n",
       "      <td>4</td>\n",
       "      <td>auto(l5)</td>\n",
       "      <td>f</td>\n",
       "      <td>18</td>\n",
       "      <td>29</td>\n",
       "      <td>p</td>\n",
       "      <td>compact</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>audi</td>\n",
       "      <td>a4</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1999</td>\n",
       "      <td>4</td>\n",
       "      <td>manual(m5)</td>\n",
       "      <td>f</td>\n",
       "      <td>21</td>\n",
       "      <td>29</td>\n",
       "      <td>p</td>\n",
       "      <td>compact</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>audi</td>\n",
       "      <td>a4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>manual(m6)</td>\n",
       "      <td>f</td>\n",
       "      <td>20</td>\n",
       "      <td>31</td>\n",
       "      <td>p</td>\n",
       "      <td>compact</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>audi</td>\n",
       "      <td>a4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>auto(av)</td>\n",
       "      <td>f</td>\n",
       "      <td>21</td>\n",
       "      <td>30</td>\n",
       "      <td>p</td>\n",
       "      <td>compact</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>audi</td>\n",
       "      <td>a4</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1999</td>\n",
       "      <td>6</td>\n",
       "      <td>auto(l5)</td>\n",
       "      <td>f</td>\n",
       "      <td>16</td>\n",
       "      <td>26</td>\n",
       "      <td>p</td>\n",
       "      <td>compact</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 manufacturer model  displ  year  cyl       trans drv  cty  hwy  \\\n",
       "0           1         audi    a4    1.8  1999    4    auto(l5)   f   18   29   \n",
       "1           2         audi    a4    1.8  1999    4  manual(m5)   f   21   29   \n",
       "2           3         audi    a4    2.0  2008    4  manual(m6)   f   20   31   \n",
       "3           4         audi    a4    2.0  2008    4    auto(av)   f   21   30   \n",
       "4           5         audi    a4    2.8  1999    6    auto(l5)   f   16   26   \n",
       "\n",
       "  fl    class  \n",
       "0  p  compact  \n",
       "1  p  compact  \n",
       "2  p  compact  \n",
       "3  p  compact  \n",
       "4  p  compact  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv\")\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c46e1902-159d-43df-908a-486ad76c38e0",
   "metadata": {},
   "source": [
    "## Legend Position\n",
    "\n",
    "Parameters to customize the legend position and justification:\n",
    "\n",
    "- `legend_position` - the position of legends;\n",
    "\n",
    "- `legend_justification` - anchor point for positioning legend;\n",
    "\n",
    "- `legend_direction` - layout of items in legends."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "114d10a7-70c4-4617-8b9b-80b084a1cff7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.426935Z",
     "iopub.status.busy": "2024-11-01T20:11:43.426862Z",
     "iopub.status.idle": "2024-11-01T20:11:43.459587Z",
     "shell.execute_reply": "2024-11-01T20:11:43.459374Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"Bt0yLu\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   var containerDiv = document.getElementById(\"Bt0yLu\");\n",
       "   var observer = new ResizeObserver(function(entries) {\n",
       "       for (let entry of entries) {\n",
       "           var width = containerDiv.clientWidth\n",
       "           if (entry.contentBoxSize && width > 0) {\n",
       "           \n",
       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
       "               }\n",
       "\n",
       "               var plotSpec={\n",
       "\"data\":{\n",
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       "\"cty\":[18.0,21.0,20.0,21.0,16.0,18.0,18.0,18.0,16.0,20.0,19.0,15.0,17.0,17.0,15.0,15.0,17.0,16.0,14.0,11.0,14.0,13.0,12.0,16.0,15.0,16.0,15.0,15.0,14.0,11.0,11.0,14.0,19.0,22.0,18.0,18.0,17.0,18.0,17.0,16.0,16.0,17.0,17.0,11.0,15.0,15.0,16.0,16.0,15.0,14.0,13.0,14.0,14.0,14.0,9.0,11.0,11.0,13.0,13.0,9.0,13.0,11.0,13.0,11.0,12.0,9.0,13.0,13.0,12.0,9.0,11.0,11.0,13.0,11.0,11.0,11.0,12.0,14.0,15.0,14.0,13.0,13.0,13.0,14.0,14.0,13.0,13.0,13.0,11.0,13.0,18.0,18.0,17.0,16.0,15.0,15.0,15.0,15.0,14.0,28.0,24.0,25.0,23.0,24.0,26.0,25.0,24.0,21.0,18.0,18.0,21.0,21.0,18.0,18.0,19.0,19.0,19.0,20.0,20.0,17.0,16.0,17.0,17.0,15.0,15.0,14.0,9.0,14.0,13.0,11.0,11.0,12.0,12.0,11.0,11.0,11.0,12.0,14.0,13.0,13.0,13.0,21.0,19.0,23.0,23.0,19.0,19.0,18.0,19.0,19.0,14.0,15.0,14.0,12.0,18.0,16.0,17.0,18.0,16.0,18.0,18.0,20.0,19.0,20.0,18.0,21.0,19.0,19.0,19.0,20.0,20.0,19.0,20.0,15.0,16.0,15.0,15.0,16.0,14.0,21.0,21.0,21.0,21.0,18.0,18.0,19.0,21.0,21.0,21.0,22.0,18.0,18.0,18.0,24.0,24.0,26.0,28.0,26.0,11.0,13.0,15.0,16.0,17.0,15.0,15.0,15.0,16.0,21.0,19.0,21.0,22.0,17.0,33.0,21.0,19.0,22.0,21.0,21.0,21.0,16.0,17.0,35.0,29.0,21.0,19.0,20.0,20.0,21.0,18.0,19.0,21.0,16.0,18.0,17.0],\n",
       "\"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",
       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"displ\",\n",
       "\"y\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"color\":\"cty\",\n",
       "\"shape\":\"drv\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"size\":5.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"1\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489bc1a6b60>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p1 = ggplot(df, aes(\"displ\", \"hwy\")) + geom_point(aes(color=\"cty\", shape=\"drv\"), size=5)\n",
    "p1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c751cc74-daa2-4b4d-a541-5fa69a163347",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.460621Z",
     "iopub.status.busy": "2024-11-01T20:11:43.460544Z",
     "iopub.status.idle": "2024-11-01T20:11:43.465153Z",
     "shell.execute_reply": "2024-11-01T20:11:43.464961Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"vMmlZ0\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   var containerDiv = document.getElementById(\"vMmlZ0\");\n",
       "   var observer = new ResizeObserver(function(entries) {\n",
       "       for (let entry of entries) {\n",
       "           var width = containerDiv.clientWidth\n",
       "           if (entry.contentBoxSize && width > 0) {\n",
       "           \n",
       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
       "               }\n",
       "\n",
       "               var plotSpec={\n",
       "\"data\":{\n",
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       "},\n",
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       "\"y\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_position\":\"bottom\"\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"color\":\"cty\",\n",
       "\"shape\":\"drv\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"size\":5.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"2\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489bc1a7340>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Draw legend below the plot area\n",
    "p1 + theme(legend_position='bottom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "786274d7-5762-48e5-9c79-18304f4e6ddd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.466031Z",
     "iopub.status.busy": "2024-11-01T20:11:43.465960Z",
     "iopub.status.idle": "2024-11-01T20:11:43.470184Z",
     "shell.execute_reply": "2024-11-01T20:11:43.470016Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"AMR1NU\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
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       "   var containerDiv = document.getElementById(\"AMR1NU\");\n",
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       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
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       "\"column\":\"cty\"\n",
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       "\"column\":\"hwy\"\n",
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       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
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       "\"column\":\"class\"\n",
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       "\"theme\":{\n",
       "\"legend_position\":[1.0,1.0],\n",
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       "\"legend_direction\":\"horizontal\"\n",
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       "\"kind\":\"plot\",\n",
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       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"size\":5.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"3\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489b0945450>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Specify position, justification and orientation\n",
    "p1 + theme(legend_position=[1, 1], legend_justification=[1, 1], legend_direction='horizontal')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c5b978f-ac88-4efe-adad-8b939c226328",
   "metadata": {},
   "source": [
    "## Legend Spacing and Margins\n",
    "\n",
    "Parameters to customize the legend spacing and margins:\n",
    "\n",
    "- `legend_box` - arrangement of multiple legends (\"horizontal\" or \"vertical\");\n",
    "\n",
    "- `legend_box_just` - justification of each legend within the overall bounding box (\"top\", \"bottom\", \"left\", \"right\", \"center\");\n",
    "\n",
    "- `legend_box_spacing` - spacing between plotting area and legend box;\n",
    "\n",
    "- `legend_margin` - margin around each legend;\n",
    "\n",
    "- `legend_spacing` - spacing between legends, `legend_spacing_x`/`legend_spacing_y` - in the horizontal/vertical direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9eb5fb7a-fe09-44ed-bfff-f332d419d85a",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-11-01T20:11:43.475832Z"
    }
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   "outputs": [
    {
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       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"displ\",\n",
       "\"y\":\"cty\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
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       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
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       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_background\":{\n",
       "\"size\":1.0,\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_position\":\"bottom\"\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"size\",\n",
       "\"breaks\":[15.0,30.0,40.0],\n",
       "\"range\":[1.0,10.0]\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"fill\":\"drv\",\n",
       "\"size\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"shape\":21.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"4\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489b0959390>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p2 = ggplot(df, aes('displ', 'cty')) + \\\n",
    "    geom_point(aes(fill='drv', size='hwy'), shape=21) + \\\n",
    "    scale_size(range=[1, 10], breaks=[15, 30, 40]) + \\\n",
    "    theme(legend_position='bottom', legend_background=element_rect(size=1))\n",
    "p2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "67abb1ea-5a3b-4f29-aab7-8186060d7d88",
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    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.476858Z",
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     "iopub.status.idle": "2024-11-01T20:11:43.481232Z",
     "shell.execute_reply": "2024-11-01T20:11:43.481062Z"
    }
   },
   "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",
       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"displ\",\n",
       "\"y\":\"cty\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_background\":{\n",
       "\"size\":1.0,\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_position\":\"bottom\",\n",
       "\"legend_margin\":[10.0,20.0]\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"size\",\n",
       "\"breaks\":[15.0,30.0,40.0],\n",
       "\"range\":[1.0,10.0]\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"fill\":\"drv\",\n",
       "\"size\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"shape\":21.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"5\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489bc1a6a70>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# legend_margin\n",
    "p2 + theme(legend_margin=[10, 20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8a0092c2-a7be-47c6-86c3-24869e2c17af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.482091Z",
     "iopub.status.busy": "2024-11-01T20:11:43.482018Z",
     "iopub.status.idle": "2024-11-01T20:11:43.486487Z",
     "shell.execute_reply": "2024-11-01T20:11:43.486321Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"9HcOCn\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   var containerDiv = document.getElementById(\"9HcOCn\");\n",
       "   var observer = new ResizeObserver(function(entries) {\n",
       "       for (let entry of entries) {\n",
       "           var width = containerDiv.clientWidth\n",
       "           if (entry.contentBoxSize && width > 0) {\n",
       "           \n",
       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
       "               }\n",
       "\n",
       "               var plotSpec={\n",
       "\"data\":{\n",
       "\"displ\":[1.8,1.8,2.0,2.0,2.8,2.8,3.1,1.8,1.8,2.0,2.0,2.8,2.8,3.1,3.1,2.8,3.1,4.2,5.3,5.3,5.3,5.7,6.0,5.7,5.7,6.2,6.2,7.0,5.3,5.3,5.7,6.5,2.4,2.4,3.1,3.5,3.6,2.4,3.0,3.3,3.3,3.3,3.3,3.3,3.8,3.8,3.8,4.0,3.7,3.7,3.9,3.9,4.7,4.7,4.7,5.2,5.2,3.9,4.7,4.7,4.7,5.2,5.7,5.9,4.7,4.7,4.7,4.7,4.7,4.7,5.2,5.2,5.7,5.9,4.6,5.4,5.4,4.0,4.0,4.0,4.0,4.6,5.0,4.2,4.2,4.6,4.6,4.6,5.4,5.4,3.8,3.8,4.0,4.0,4.6,4.6,4.6,4.6,5.4,1.6,1.6,1.6,1.6,1.6,1.8,1.8,1.8,2.0,2.4,2.4,2.4,2.4,2.5,2.5,3.3,2.0,2.0,2.0,2.0,2.7,2.7,2.7,3.0,3.7,4.0,4.7,4.7,4.7,5.7,6.1,4.0,4.2,4.4,4.6,5.4,5.4,5.4,4.0,4.0,4.6,5.0,2.4,2.4,2.5,2.5,3.5,3.5,3.0,3.0,3.5,3.3,3.3,4.0,5.6,3.1,3.8,3.8,3.8,5.3,2.5,2.5,2.5,2.5,2.5,2.5,2.2,2.2,2.5,2.5,2.5,2.5,2.5,2.5,2.7,2.7,3.4,3.4,4.0,4.7,2.2,2.2,2.4,2.4,3.0,3.0,3.5,2.2,2.2,2.4,2.4,3.0,3.0,3.3,1.8,1.8,1.8,1.8,1.8,4.7,5.7,2.7,2.7,2.7,3.4,3.4,4.0,4.0,2.0,2.0,2.0,2.0,2.8,1.9,2.0,2.0,2.0,2.0,2.5,2.5,2.8,2.8,1.9,1.9,2.0,2.0,2.5,2.5,1.8,1.8,2.0,2.0,2.8,2.8,3.6],\n",
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       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"displ\",\n",
       "\"y\":\"cty\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_background\":{\n",
       "\"size\":1.0,\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_position\":\"bottom\",\n",
       "\"legend_box\":\"horizontal\"\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"size\",\n",
       "\"breaks\":[15.0,30.0,40.0],\n",
       "\"range\":[1.0,10.0]\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"fill\":\"drv\",\n",
       "\"size\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"shape\":21.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"6\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489b0959570>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# legend_box\n",
    "p2 + theme(legend_box='horizontal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "36f75815-f356-49df-9743-8db0fc502120",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.487339Z",
     "iopub.status.busy": "2024-11-01T20:11:43.487270Z",
     "iopub.status.idle": "2024-11-01T20:11:43.492188Z",
     "shell.execute_reply": "2024-11-01T20:11:43.491928Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"m81nPd\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   var containerDiv = document.getElementById(\"m81nPd\");\n",
       "   var observer = new ResizeObserver(function(entries) {\n",
       "       for (let entry of entries) {\n",
       "           var width = containerDiv.clientWidth\n",
       "           if (entry.contentBoxSize && width > 0) {\n",
       "           \n",
       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
       "               }\n",
       "\n",
       "               var plotSpec={\n",
       "\"data\":{\n",
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       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"displ\",\n",
       "\"y\":\"cty\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
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       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_background\":{\n",
       "\"size\":1.0,\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_position\":\"bottom\",\n",
       "\"legend_box_just\":\"center\"\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"size\",\n",
       "\"breaks\":[15.0,30.0,40.0],\n",
       "\"range\":[1.0,10.0]\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"fill\":\"drv\",\n",
       "\"size\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"shape\":21.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"7\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489b095a2c0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# legend_box_just\n",
    "p2 + theme(legend_box_just='center')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0eebd0e5-d542-452b-ad25-e117d0c68127",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.493084Z",
     "iopub.status.busy": "2024-11-01T20:11:43.493009Z",
     "iopub.status.idle": "2024-11-01T20:11:43.497548Z",
     "shell.execute_reply": "2024-11-01T20:11:43.497380Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"lWcpLz\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   var containerDiv = document.getElementById(\"lWcpLz\");\n",
       "   var observer = new ResizeObserver(function(entries) {\n",
       "       for (let entry of entries) {\n",
       "           var width = containerDiv.clientWidth\n",
       "           if (entry.contentBoxSize && width > 0) {\n",
       "           \n",
       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
       "               }\n",
       "\n",
       "               var plotSpec={\n",
       "\"data\":{\n",
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       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"displ\",\n",
       "\"y\":\"cty\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_background\":{\n",
       "\"size\":1.0,\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_position\":\"bottom\",\n",
       "\"legend_box\":\"horizontal\",\n",
       "\"legend_box_spacing\":50.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"size\",\n",
       "\"breaks\":[15.0,30.0,40.0],\n",
       "\"range\":[1.0,10.0]\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"geom\":\"point\",\n",
       "\"mapping\":{\n",
       "\"fill\":\"drv\",\n",
       "\"size\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"shape\":21.0,\n",
       "\"data\":{\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"8\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489b098b340>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# legend_box_spacing\n",
    "p2 + theme(legend_box='horizontal',  legend_box_spacing=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a4d86f96-9160-4aea-9f39-f66593294fbb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.498417Z",
     "iopub.status.busy": "2024-11-01T20:11:43.498344Z",
     "iopub.status.idle": "2024-11-01T20:11:43.503150Z",
     "shell.execute_reply": "2024-11-01T20:11:43.502975Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"8iaXaD\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   var containerDiv = document.getElementById(\"8iaXaD\");\n",
       "   var observer = new ResizeObserver(function(entries) {\n",
       "       for (let entry of entries) {\n",
       "           var width = containerDiv.clientWidth\n",
       "           if (entry.contentBoxSize && width > 0) {\n",
       "           \n",
       "               // Render plot\n",
       "               if (observer) {\n",
       "                   observer.disconnect();\n",
       "                   observer = null;\n",
       "               }\n",
       "\n",
       "               var plotSpec={\n",
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       "},\n",
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       "\"x\":\"displ\",\n",
       "\"y\":\"cty\"\n",
       "},\n",
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       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
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       "\"column\":\"hwy\"\n",
       "},{\n",
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       "\"column\":\"fl\"\n",
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       "};\n",
       "               window.letsPlotCall(function() {\n",
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       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
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       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489b095a470>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# legend_spacing\n",
    "p2 + theme(legend_box='horizontal', legend_spacing_x=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26d9d1a1-9651-4432-8b76-09b4300c626a",
   "metadata": {},
   "source": [
    "## Legend Key Parameters\n",
    "\n",
    "Parameters to customize the legend key:\n",
    "\n",
    "- `legend_key` - background underneath legend keys, set with `element_rect()`;\n",
    "\n",
    "- `legend_key_size` - size of legend keys;\n",
    "\n",
    "- `legend_key_width` - key background width;\n",
    "\n",
    "- `legend_key_height` - key background height;\n",
    "\n",
    "- `legend_key_spacing` - spacing between legend keys;\n",
    "\n",
    "- `legend_key_spacing_x` - spacing in the horizontal direction;\n",
    "\n",
    "- `legend_key_spacing_y` - spacing in the vertical direction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e61aba29-a6c7-4751-b32e-ef0bc96df51d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-01T20:11:43.504019Z",
     "iopub.status.busy": "2024-11-01T20:11:43.503951Z",
     "iopub.status.idle": "2024-11-01T20:11:43.509521Z",
     "shell.execute_reply": "2024-11-01T20:11:43.509353Z"
    }
   },
   "outputs": [
    {
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       "               // Render plot\n",
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       "\n",
       "               var plotSpec={\n",
       "\"data\":{\n",
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       "\"mapping\":{\n",
       "\"x\":\"hwy\"\n",
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       "\"hwy\":[23.5,25.5,27.5,29.5,31.0,33.0,35.0,37.0,44.0,23.5,25.5,27.5,29.5,31.5,12.0,14.5,16.5,18.5,20.0,22.5,24.5,26.5,23.5,25.5,17.0,21.5,23.5,12.0,15.5,17.5,19.5,22.0,20.5,22.5,24.5,26.5,28.5,32.5,34.0,36.0,41.0,44.0],\n",
       "\"class\":[\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"2seater\",\"2seater\",\"minivan\",\"minivan\",\"minivan\",\"pickup\",\"pickup\",\"pickup\",\"pickup\",\"pickup\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\"]\n",
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       "   \n",
       "   </script>"
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       "<lets_plot.plot.core.PlotSpec at 0x7489b09a27a0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p3 = ggplot(df, aes(x='hwy')) + \\\n",
    "    geom_dotplot(aes(fill='class'), color='pen') + \\\n",
    "    theme(legend_background=element_rect(size=0.5))\n",
    "p3"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7f677e7-ed4c-4843-a012-5745ba8ca908",
   "metadata": {},
   "source": [
    "Add background underneath legend keys:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bf00c2e2-38b9-464f-8102-e57560d16bf7",
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     "shell.execute_reply": "2024-11-01T20:11:43.514632Z"
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   },
   "outputs": [
    {
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       "               var plotSpec={\n",
       "\"data\":{\n",
       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"hwy\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"Unnamed: 0\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"manufacturer\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"model\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"displ\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"year\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cyl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"trans\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"drv\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"cty\"\n",
       "},{\n",
       "\"type\":\"int\",\n",
       "\"column\":\"hwy\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"fl\"\n",
       "},{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"class\"\n",
       "}]\n",
       "},\n",
       "\"theme\":{\n",
       "\"legend_background\":{\n",
       "\"size\":0.5,\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_key\":{\n",
       "\"fill\":\"#efedf5\",\n",
       "\"color\":\"#756bb1\",\n",
       "\"blank\":false\n",
       "},\n",
       "\"legend_key_width\":80.0,\n",
       "\"legend_key_height\":20.0,\n",
       "\"legend_key_spacing_y\":10.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"dotplot\",\n",
       "\"mapping\":{\n",
       "\"fill\":\"class\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"color\":\"pen\",\n",
       "\"data\":{\n",
       "\"..count..\":[3.0,14.0,8.0,14.0,3.0,1.0,2.0,1.0,1.0,2.0,18.0,9.0,7.0,5.0,2.0,8.0,21.0,17.0,7.0,2.0,3.0,2.0,2.0,3.0,1.0,4.0,6.0,3.0,9.0,13.0,7.0,1.0,2.0,3.0,5.0,9.0,7.0,4.0,1.0,2.0,1.0,1.0],\n",
       "\"..binwidth..\":[1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667,1.0666666666666667],\n",
       "\"hwy\":[23.5,25.5,27.5,29.5,31.0,33.0,35.0,37.0,44.0,23.5,25.5,27.5,29.5,31.5,12.0,14.5,16.5,18.5,20.0,22.5,24.5,26.5,23.5,25.5,17.0,21.5,23.5,12.0,15.5,17.5,19.5,22.0,20.5,22.5,24.5,26.5,28.5,32.5,34.0,36.0,41.0,44.0],\n",
       "\"class\":[\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"compact\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"midsize\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"suv\",\"2seater\",\"2seater\",\"minivan\",\"minivan\",\"minivan\",\"pickup\",\"pickup\",\"pickup\",\"pickup\",\"pickup\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\",\"subcompact\"]\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"14\"\n",
       "};\n",
       "               window.letsPlotCall(function() {\n",
       "       \n",
       "               var toolbar = null;\n",
       "               var plotContainer = containerDiv;               \n",
       "               \n",
       "                   var options = {\n",
       "                       sizing: {\n",
       "                           width_mode: \"min\",\n",
       "                           height_mode: \"scaled\",\n",
       "                           width: width\n",
       "                       }\n",
       "                   };\n",
       "                   var fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer, options);\n",
       "                   if (toolbar) {\n",
       "                     toolbar.bind(fig);\n",
       "                   }\n",
       "               });\n",
       "               \n",
       "               break;\n",
       "           }\n",
       "       }\n",
       "   });\n",
       "   \n",
       "   observer.observe(containerDiv);\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7489bc1a47f0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p5 + theme(legend_key_spacing_y=10)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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