{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.427565Z",
     "iopub.status.busy": "2025-11-05T13:44:08.427462Z",
     "iopub.status.idle": "2025-11-05T13:44:08.430675Z",
     "shell.execute_reply": "2025-11-05T13:44:08.430483Z"
    }
   },
   "outputs": [],
   "source": [
    "from lets_plot import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.431337Z",
     "iopub.status.busy": "2025-11-05T13:44:08.431264Z",
     "iopub.status.idle": "2025-11-05T13:44:08.432951Z",
     "shell.execute_reply": "2025-11-05T13:44:08.432777Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <div id=\"YpuYvZ\"></div>\n",
       "            <script type=\"text/javascript\" data-lets-plot-script=\"library\">\n",
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       "                    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@v4.8.0/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(\"YpuYvZ\").appendChild(div);\n",
       "                    };\n",
       "                    var e = document.getElementById(\"YpuYvZ\");\n",
       "                    e.appendChild(script);\n",
       "                })()\n",
       "            </script>\n",
       "            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LetsPlot.setup_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.446644Z",
     "iopub.status.busy": "2025-11-05T13:44:08.446523Z",
     "iopub.status.idle": "2025-11-05T13:44:08.451656Z",
     "shell.execute_reply": "2025-11-05T13:44:08.451453Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(400, 2)\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>cond</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>-1.085631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A</td>\n",
       "      <td>0.997345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A</td>\n",
       "      <td>0.282978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>A</td>\n",
       "      <td>-1.506295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>A</td>\n",
       "      <td>-0.578600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  cond    rating\n",
       "0    A -1.085631\n",
       "1    A  0.997345\n",
       "2    A  0.282978\n",
       "3    A -1.506295\n",
       "4    A -0.578600"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This example was found at: www.cookbook-r.com/Graphs/Plotting_distributions_(ggplot2)\n",
    "def get_data():\n",
    "    import numpy as np\n",
    "    import pandas as pd\n",
    "\n",
    "    np.random.seed(123)\n",
    "\n",
    "    return pd.DataFrame(dict(\n",
    "        cond=np.repeat([\"A\", \"B\"], 200),\n",
    "        rating=np.concatenate((np.random.normal(0, 1, 200), np.random.normal(.8, 1, 200)))\n",
    "    ))\n",
    "\n",
    "df = get_data()\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.452450Z",
     "iopub.status.busy": "2025-11-05T13:44:08.452377Z",
     "iopub.status.idle": "2025-11-05T13:44:08.481198Z",
     "shell.execute_reply": "2025-11-05T13:44:08.480992Z"
    }
   },
   "outputs": [
    {
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       "   const containerDiv = document.getElementById(\"884iHG\");\n",
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       "       if (fig === null) {\n",
       "           const plotSpec = {\n",
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       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"1\"\n",
       "};\n",
       "           window.letsPlotCall(function() { fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, containerDiv, sizing); });\n",
       "       } else {\n",
       "           fig.updateView({});\n",
       "       }\n",
       "   }\n",
       "   \n",
       "   const renderImmediately = \n",
       "       forceImmediateRender || (\n",
       "           sizing.width_mode === 'FIXED' && \n",
       "           (sizing.height_mode === 'FIXED' || sizing.height_mode === 'SCALED')\n",
       "       );\n",
       "   \n",
       "   if (renderImmediately) {\n",
       "       renderPlot();\n",
       "   }\n",
       "   \n",
       "   if (!renderImmediately || responsive) {\n",
       "       // Set up observer for initial sizing or continuous monitoring\n",
       "       var observer = new ResizeObserver(function(entries) {\n",
       "           for (let entry of entries) {\n",
       "               if (entry.contentBoxSize && \n",
       "                   entry.contentBoxSize[0].inlineSize > 0) {\n",
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       "                       observer.disconnect();\n",
       "                       observer = null;\n",
       "                   }\n",
       "                   renderPlot();\n",
       "                   if (!responsive) {\n",
       "                       break;\n",
       "                   }\n",
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       "       observer.observe(containerDiv);\n",
       "   }\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x744907eae740>"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Basic histogram of \"rating\"\n",
    "p = ggplot(df, aes(x=\"rating\")) + ggsize(500, 250)\n",
    "p + geom_histogram(binwidth=.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.482231Z",
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     "iopub.status.idle": "2025-11-05T13:44:08.496189Z",
     "shell.execute_reply": "2025-11-05T13:44:08.496004Z"
    }
   },
   "outputs": [
    {
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       "       width_mode: \"MIN\",\n",
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       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"2\"\n",
       "};\n",
       "           window.letsPlotCall(function() { fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, containerDiv, sizing); });\n",
       "       } else {\n",
       "           fig.updateView({});\n",
       "       }\n",
       "   }\n",
       "   \n",
       "   const renderImmediately = \n",
       "       forceImmediateRender || (\n",
       "           sizing.width_mode === 'FIXED' && \n",
       "           (sizing.height_mode === 'FIXED' || sizing.height_mode === 'SCALED')\n",
       "       );\n",
       "   \n",
       "   if (renderImmediately) {\n",
       "       renderPlot();\n",
       "   }\n",
       "   \n",
       "   if (!renderImmediately || responsive) {\n",
       "       // Set up observer for initial sizing or continuous monitoring\n",
       "       var observer = new ResizeObserver(function(entries) {\n",
       "           for (let entry of entries) {\n",
       "               if (entry.contentBoxSize && \n",
       "                   entry.contentBoxSize[0].inlineSize > 0) {\n",
       "                   if (!responsive && observer) {\n",
       "                       observer.disconnect();\n",
       "                       observer = null;\n",
       "                   }\n",
       "                   renderPlot();\n",
       "                   if (!responsive) {\n",
       "                       break;\n",
       "                   }\n",
       "               }\n",
       "           }\n",
       "       });\n",
       "       \n",
       "       observer.observe(containerDiv);\n",
       "   }\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x74490492b7c0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Histogram overlaid with kernel density curve\n",
    "#  - histogram with density instead of count on y-axis\n",
    "#  - overlay with transparent density plot\n",
    "p + \\\n",
    "    geom_histogram(aes(y='..density..'), binwidth=.5, colour=\"black\", fill=\"white\") + \\\n",
    "    geom_density(alpha=.2, color=\"#de2d26\", fill=\"#ff6666\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.497146Z",
     "iopub.status.busy": "2025-11-05T13:44:08.497074Z",
     "iopub.status.idle": "2025-11-05T13:44:08.500461Z",
     "shell.execute_reply": "2025-11-05T13:44:08.500269Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"5iPB6a\"></div>\n",
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       "   const responsive = false;\n",
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      ],
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       "<lets_plot.plot.core.PlotSpec at 0x74490492bf70>"
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     },
     "execution_count": 6,
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   ],
   "source": [
    "p + \\\n",
    "    geom_histogram(binwidth=.5, colour=\"black\", fill=\"white\") + \\\n",
    "    geom_vline(xintercept=df[\"rating\"].mean(), \\\n",
    "               color=\"red\", linetype='dashed', size=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histogram and density plots with multiple groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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     "shell.execute_reply": "2025-11-05T13:44:08.504776Z"
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    "p1 = ggplot(df, aes(x=\"rating\", fill=\"cond\")) + ggsize(500, 250)\n",
    "\n",
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    "p1 + geom_histogram(binwidth=.5)"
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  {
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     "shell.execute_reply": "2025-11-05T13:44:08.509348Z"
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   "outputs": [
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   "source": [
    "# Overlaid histograms\n",
    "p1 + geom_histogram(binwidth=.5, alpha=.7, position=\"identity\")"
   ]
  },
  {
   "cell_type": "code",
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       "   \n",
       "   if (!renderImmediately || responsive) {\n",
       "       // Set up observer for initial sizing or continuous monitoring\n",
       "       var observer = new ResizeObserver(function(entries) {\n",
       "           for (let entry of entries) {\n",
       "               if (entry.contentBoxSize && \n",
       "                   entry.contentBoxSize[0].inlineSize > 0) {\n",
       "                   if (!responsive && observer) {\n",
       "                       observer.disconnect();\n",
       "                       observer = null;\n",
       "                   }\n",
       "                   renderPlot();\n",
       "                   if (!responsive) {\n",
       "                       break;\n",
       "                   }\n",
       "               }\n",
       "           }\n",
       "       });\n",
       "       \n",
       "       observer.observe(containerDiv);\n",
       "   }\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x74490492bb20>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Interleaved histograms\n",
    "p1 + geom_histogram(binwidth=.5, position=\"dodge\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.514432Z",
     "iopub.status.busy": "2025-11-05T13:44:08.514364Z",
     "iopub.status.idle": "2025-11-05T13:44:08.530945Z",
     "shell.execute_reply": "2025-11-05T13:44:08.530744Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   const forceImmediateRender = false;\n",
       "   const responsive = false;\n",
       "   \n",
       "   let sizing = {\n",
       "       width_mode: \"MIN\",\n",
       "       height_mode: \"SCALED\",\n",
       "       width: null, \n",
       "       height: null \n",
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       "   \n",
       "   const preferredWidth = document.body.dataset.letsPlotPreferredWidth;\n",
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       "       sizing = {\n",
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       "   \n",
       "   function renderPlot() {\n",
       "       if (fig === null) {\n",
       "           const plotSpec = {\n",
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       "}\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"7\"\n",
       "};\n",
       "           window.letsPlotCall(function() { fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, containerDiv, sizing); });\n",
       "       } else {\n",
       "           fig.updateView({});\n",
       "       }\n",
       "   }\n",
       "   \n",
       "   const renderImmediately = \n",
       "       forceImmediateRender || (\n",
       "           sizing.width_mode === 'FIXED' && \n",
       "           (sizing.height_mode === 'FIXED' || sizing.height_mode === 'SCALED')\n",
       "       );\n",
       "   \n",
       "   if (renderImmediately) {\n",
       "       renderPlot();\n",
       "   }\n",
       "   \n",
       "   if (!renderImmediately || responsive) {\n",
       "       // Set up observer for initial sizing or continuous monitoring\n",
       "       var observer = new ResizeObserver(function(entries) {\n",
       "           for (let entry of entries) {\n",
       "               if (entry.contentBoxSize && \n",
       "                   entry.contentBoxSize[0].inlineSize > 0) {\n",
       "                   if (!responsive && observer) {\n",
       "                       observer.disconnect();\n",
       "                       observer = null;\n",
       "                   }\n",
       "                   renderPlot();\n",
       "                   if (!responsive) {\n",
       "                       break;\n",
       "                   }\n",
       "               }\n",
       "           }\n",
       "       });\n",
       "       \n",
       "       observer.observe(containerDiv);\n",
       "   }\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x7449049556f0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Density plot\n",
    "p2 = ggplot(df, aes(x=\"rating\", color=\"cond\")) + ggsize(500, 250)\n",
    "p2 + geom_density()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.531897Z",
     "iopub.status.busy": "2025-11-05T13:44:08.531818Z",
     "iopub.status.idle": "2025-11-05T13:44:08.551047Z",
     "shell.execute_reply": "2025-11-05T13:44:08.550854Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"byJz4X\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   const forceImmediateRender = false;\n",
       "   const responsive = false;\n",
       "   \n",
       "   let sizing = {\n",
       "       width_mode: \"MIN\",\n",
       "       height_mode: \"SCALED\",\n",
       "       width: null, \n",
       "       height: null \n",
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       "   \n",
       "   const preferredWidth = document.body.dataset.letsPlotPreferredWidth;\n",
       "   if (preferredWidth !== undefined) {\n",
       "       sizing = {\n",
       "           width_mode: 'FIXED',\n",
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       "           width: parseFloat(preferredWidth)\n",
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       "   \n",
       "   const containerDiv = document.getElementById(\"byJz4X\");\n",
       "   let fig = null;\n",
       "   \n",
       "   function renderPlot() {\n",
       "       if (fig === null) {\n",
       "           const plotSpec = {\n",
       "\"data\":{\n",
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       "\"mapping\":{\n",
       "\"x\":\"rating\",\n",
       "\"color\":\"cond\"\n",
       "},\n",
       "\"data_meta\":{\n",
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       "\"type\":\"str\",\n",
       "\"column\":\"cond\"\n",
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       "\"type\":\"float\",\n",
       "\"column\":\"rating\"\n",
       "}]\n",
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       "\"width\":500.0,\n",
       "\"height\":250.0\n",
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       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"density\",\n",
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       "\"alpha\":0.7,\n",
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       "           window.letsPlotCall(function() { fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, containerDiv, sizing); });\n",
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      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x744907eae710>"
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     "execution_count": 11,
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   "source": [
    "# Density plot with semi-transparent fill\n",
    "p2 + geom_density(aes(fill=\"cond\"), alpha=.7)"
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  {
   "cell_type": "code",
   "execution_count": 12,
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     "iopub.status.busy": "2025-11-05T13:44:08.551914Z",
     "iopub.status.idle": "2025-11-05T13:44:08.555466Z",
     "shell.execute_reply": "2025-11-05T13:44:08.555273Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<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",
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       "\n",
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cond</th>\n",
       "      <th>rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A</td>\n",
       "      <td>0.003787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B</td>\n",
       "      <td>0.685638</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  cond    rating\n",
       "0    A  0.003787\n",
       "1    B  0.685638"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "# Find the mean of each group\n",
    "cdf = df.groupby([\"cond\"], as_index=False).mean()\n",
    "cdf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.556389Z",
     "iopub.status.busy": "2025-11-05T13:44:08.556316Z",
     "iopub.status.idle": "2025-11-05T13:44:08.561532Z",
     "shell.execute_reply": "2025-11-05T13:44:08.561357Z"
    }
   },
   "outputs": [
    {
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     "execution_count": 13,
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   ],
   "source": [
    "# Overlaid histograms with means\n",
    "p2 + \\\n",
    "    geom_histogram(aes(fill=\"cond\"), alpha=.5, position=\"identity\", size=0) + \\\n",
    "    geom_vline(data=cdf, \\\n",
    "               mapping=aes(xintercept=\"rating\",  color=\"cond\"), \\\n",
    "               linetype='dashed', size=1)"
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   "source": [
    "# Use frqpoly instead of histogram\n",
    "p2 + \\\n",
    "    geom_freqpoly(aes(fill=\"cond\")) + \\\n",
    "    geom_vline(data=cdf, \\\n",
    "               mapping=aes(xintercept=\"rating\",  color=\"cond\"), \\\n",
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       "}\n",
       "},{\n",
       "\"geom\":\"vline\",\n",
       "\"data\":{\n",
       "\"cond\":[\"A\",\"B\"],\n",
       "\"rating\":[0.0037867557901067606,0.6856382988765608]\n",
       "},\n",
       "\"mapping\":{\n",
       "\"xintercept\":\"rating\",\n",
       "\"color\":\"cond\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"cond\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"rating\"\n",
       "}]\n",
       "},\n",
       "\"linetype\":\"dashed\",\n",
       "\"size\":1.0\n",
       "}],\n",
       "\"metainfo_list\":[],\n",
       "\"spec_id\":\"11\"\n",
       "};\n",
       "           window.letsPlotCall(function() { fig = LetsPlot.buildPlotFromProcessedSpecs(plotSpec, containerDiv, sizing); });\n",
       "       } else {\n",
       "           fig.updateView({});\n",
       "       }\n",
       "   }\n",
       "   \n",
       "   const renderImmediately = \n",
       "       forceImmediateRender || (\n",
       "           sizing.width_mode === 'FIXED' && \n",
       "           (sizing.height_mode === 'FIXED' || sizing.height_mode === 'SCALED')\n",
       "       );\n",
       "   \n",
       "   if (renderImmediately) {\n",
       "       renderPlot();\n",
       "   }\n",
       "   \n",
       "   if (!renderImmediately || responsive) {\n",
       "       // Set up observer for initial sizing or continuous monitoring\n",
       "       var observer = new ResizeObserver(function(entries) {\n",
       "           for (let entry of entries) {\n",
       "               if (entry.contentBoxSize && \n",
       "                   entry.contentBoxSize[0].inlineSize > 0) {\n",
       "                   if (!responsive && observer) {\n",
       "                       observer.disconnect();\n",
       "                       observer = null;\n",
       "                   }\n",
       "                   renderPlot();\n",
       "                   if (!responsive) {\n",
       "                       break;\n",
       "                   }\n",
       "               }\n",
       "           }\n",
       "       });\n",
       "       \n",
       "       observer.observe(containerDiv);\n",
       "   }\n",
       "   \n",
       "   // ----------\n",
       "   })();\n",
       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x744904957250>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Density plots with means\n",
    "p2 + \\\n",
    "    geom_density() + \\\n",
    "    geom_vline(data=cdf, \\\n",
    "               mapping=aes(xintercept=\"rating\", color=\"cond\"), \\\n",
    "               linetype='dashed', size=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using facets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.586350Z",
     "iopub.status.busy": "2025-11-05T13:44:08.586278Z",
     "iopub.status.idle": "2025-11-05T13:44:08.590878Z",
     "shell.execute_reply": "2025-11-05T13:44:08.590697Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"x6Tc41\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "   \n",
       "   (function() {\n",
       "   // ----------\n",
       "   \n",
       "   const forceImmediateRender = false;\n",
       "   const responsive = false;\n",
       "   \n",
       "   let sizing = {\n",
       "       width_mode: \"MIN\",\n",
       "       height_mode: \"SCALED\",\n",
       "       width: null, \n",
       "       height: null \n",
       "   };\n",
       "   \n",
       "   const preferredWidth = document.body.dataset.letsPlotPreferredWidth;\n",
       "   if (preferredWidth !== undefined) {\n",
       "       sizing = {\n",
       "           width_mode: 'FIXED',\n",
       "           height_mode: 'SCALED',\n",
       "           width: parseFloat(preferredWidth)\n",
       "       };\n",
       "   }\n",
       "   \n",
       "   const containerDiv = document.getElementById(\"x6Tc41\");\n",
       "   let fig = null;\n",
       "   \n",
       "   function renderPlot() {\n",
       "       if (fig === null) {\n",
       "           const plotSpec = {\n",
       "\"data\":{\n",
       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"rating\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
       "\"type\":\"str\",\n",
       "\"column\":\"cond\"\n",
       "},{\n",
       "\"type\":\"float\",\n",
       "\"column\":\"rating\"\n",
       "}]\n",
       "},\n",
       "\"facet\":{\n",
       "\"name\":\"grid\",\n",
       "\"x\":\"cond\",\n",
       "\"x_order\":1.0,\n",
       "\"y_order\":1.0\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"histogram\",\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[]\n",
       "},\n",
       "\"binwidth\":0.5,\n",
       "\"colour\":\"black\",\n",
       "\"fill\":\"white\",\n",
       "\"data\":{\n",
       "\"..count..\":[1.0,1.0,3.0,8.0,17.0,26.0,39.0,41.0,23.0,20.0,14.0,6.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,11.0,28.0,32.0,45.0,33.0,27.0,11.0,6.0,1.0,1.0,0.0],\n",
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       "           (sizing.height_mode === 'FIXED' || sizing.height_mode === 'SCALED')\n",
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       "       renderPlot();\n",
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       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x744904981840>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ggplot(df, aes(x=\"rating\")) + \\\n",
    "    geom_histogram(binwidth=.5, colour=\"black\", fill=\"white\") + \\\n",
    "    facet_grid(\"cond\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
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    {
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       "   const responsive = false;\n",
       "   \n",
       "   let sizing = {\n",
       "       width_mode: \"MIN\",\n",
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     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# With mean lines, using 'cdat' computed earlier.\n",
    "ggplot(df, aes(x=\"rating\")) + \\\n",
    "    geom_histogram(binwidth=.5, colour=\"black\", fill=\"white\") + \\\n",
    "    geom_vline(data=cdf, \\\n",
    "               mapping=aes(xintercept=\"rating\"), \\\n",
    "               linetype='dashed', size=1, colour=\"red\") + \\\n",
    "    facet_grid(None, \"cond\") + \\\n",
    "    ggsize(500, 250)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Box plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
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     "shell.execute_reply": "2025-11-05T13:44:08.600337Z"
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   "outputs": [
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       "\"spec_id\":\"14\"\n",
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       "   \n",
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       "   \n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x744904957c10>"
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     },
     "execution_count": 18,
     "metadata": {},
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    }
   ],
   "source": [
    "# A basic box plot\n",
    "p3 = ggplot(df, aes(x=\"cond\", y=\"rating\")) + ggsize(400, 300)\n",
    "p3 + geom_boxplot()"
   ]
  },
  {
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    {
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      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# A basic box with the conditions colored\n",
    "p3 + geom_boxplot(aes(fill=\"cond\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-11-05T13:44:08.606572Z",
     "iopub.status.busy": "2025-11-05T13:44:08.606495Z",
     "iopub.status.idle": "2025-11-05T13:44:08.609963Z",
     "shell.execute_reply": "2025-11-05T13:44:08.609776Z"
    }
   },
   "outputs": [
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       "\"data\":{\n",
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       "\"mapping\":{\n",
       "\"x\":\"cond\",\n",
       "\"y\":\"rating\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"series_annotations\":[{\n",
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       "\"column\":\"rating\"\n",
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      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x744904957e80>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Style outliers\n",
    "p3 + geom_boxplot(outlier_color=\"red\", outlier_shape=8, outlier_size=1.5)"
   ]
  }
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