{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# iqplot\n",
    "\n",
    "[Data set download](https://s3.amazonaws.com/bebi103.caltech.edu/data/gfmt_sleep.csv)\n",
    "\n",
    "<hr />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "editable": true,
    "nbsphinx": "hidden",
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Colab setup ------------------\n",
    "import os, sys, subprocess\n",
    "if \"google.colab\" in sys.modules:\n",
    "    cmd = \"pip install --upgrade iqplot colorcet watermark\"\n",
    "    process = subprocess.Popen(cmd.split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE)\n",
    "    stdout, stderr = process.communicate()\n",
    "    data_path = \"https://s3.amazonaws.com/bebi103.caltech.edu/data/\"\n",
    "else:\n",
    "    data_path = \"../data/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "  }\n",
       "\n",
       "const JS_MIME_TYPE = 'application/javascript';\n",
       "  const HTML_MIME_TYPE = 'text/html';\n",
       "  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
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       "\n",
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       "\n",
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       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  const NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
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       "\n",
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       "        if (callback != null)\n",
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       "      delete root._bokeh_onload_callbacks\n",
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       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
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       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error(url) {\n",
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       "\n",
       "    for (let i = 0; i < css_urls.length; i++) {\n",
       "      const url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < js_urls.length; i++) {\n",
       "      const url = js_urls[i];\n",
       "      const element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.2.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-3.2.1.min.js\"];\n",
       "  const css_urls = [];\n",
       "\n",
       "  const inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {\n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "          for (let i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      const cell = $(document.getElementById(\"cf839dae-5529-4b8b-8d5c-5dad4967cf13\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import iqplot\n",
    "\n",
    "import bokeh.io\n",
    "bokeh.io.output_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "\n",
    "I developed [iqplot](https://iqplot.github.io/), which generates Bokeh plots for data sets where exactly one variable is quantitative and all other variables of interest, if any, are categorical. This is where the name comes from; the first two letters of the package name are meant to indicate one (Roman number I) quantitative (Q) variable. The subclass of data sets that contain a single quantitative variable (and possibly several categorical variables) abound in the biological sciences.\n",
    "\n",
    "There are seven types of plots that iqplot can generate. As you will see, all of these modes of plotting are meant to give a picture about how the quantitative measurements are *distributed*.\n",
    "\n",
    "+ Box plots: `iqplot.box()`\n",
    "+ Strip plots: `iqplot.strip()`\n",
    "+ Spike plots: `iqplot.spike()`\n",
    "+ Strip-box plots (strip and box plots overlaid): `iqplot.stripbox()`\n",
    "+ Histograms: `iqplot.histogram()`\n",
    "+ Strip-histogram plots (strip and histograms overlaid): `iqplot.striphistogram()`\n",
    "+ ECDFs: `iqplot.ecdf()`\n",
    "    \n",
    "This first seven arguments are the same for all plots. They are:\n",
    "\n",
    "- `data`: A tidy data frame\n",
    "- `q`: The column of the data frame to be treated as the quantitative variable.\n",
    "- `cats`: A list of columns in the data frame that are to be considered as categorical variables in the plot. If `None`, a single box, strip, histogram, or ECDF is plotted.\n",
    "- `q_axis`: Along which axis, x or y that the quantitative variable varies. The default is `'x'`.\n",
    "- `palette`: A list of hex colors to use for coloring the markers for each category. By default, it uses the Glasbey Category 10 color palette from [colorcet](https://colorcet.holoviz.org/).\n",
    "- `order`: If specified, the ordering of the categories to use on the categorical axis and legend (if applicable). Otherwise, the order of the inputted data frame is used.\n",
    "- `p`: If specified, the `bokeh.plotting.Figure` object to use for the plot. If not specified, a new figure is created.\n",
    "\n",
    "If `data` is given as a Numpy array, it is the only required argument. If `data` is given as a Pandas DataFrame, `q` must also be supplied. All other arguments are optional and have reasonably set defaults. Any extra kwargs not in the function call signature are passed to `bokeh.plotting.figure()` when the figure is instantiated.\n",
    "\n",
    "With this in mind, we will put iqplot to use on facial identification data set to demonstrate how we can make each of the seven kinds of plots. First, as we have become accustomed, we'll load in the data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "fname = os.path.join(data_path, \"gfmt_sleep.csv\")\n",
    "df = pd.read_csv(fname, na_values=\"*\")\n",
    "df[\"insomnia\"] = df[\"sci\"] <= 16\n",
    "df[\"sleeper\"] = df[\"insomnia\"].apply(lambda x: \"insomniac\" if x else \"normal\")\n",
    "df[\"gender\"] = df[\"gender\"].apply(lambda x: \"female\" if x == \"f\" else \"male\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All seven plots\n",
    "\n",
    "We now make plots of the percent correct insomniacs and normal sleepers so you can see how the syntax works."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Box plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1016\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1017\",\"attributes\":{\"axis\":{\"id\":\"p1013\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1022\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1018\"},\"grid_line_color\":null}}],\"frame_width\":375,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"2939a46a-0468-4e49-9767-2902900d3c47\",\"roots\":{\"p1002\":\"dc8494c9-4f6d-4669-99d5-480044d97f17\"},\"root_ids\":[\"p1002\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1002"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.box(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strip plot\n",
    "\n",
    "For this plot, I will add jitter, which is passed using the `spread='jitter'` kwarg."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"a5ce43a9-1f18-4cca-aa0d-ca391e7afa8f\" data-root-id=\"p1085\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"8bf599d3-a968-4c11-b863-b3ec3cacbd19\":{\"version\":\"3.2.1\",\"title\":\"Bokeh 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correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1099\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1100\",\"attributes\":{\"axis\":{\"id\":\"p1096\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1105\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1101\"},\"grid_line_color\":null}}],\"frame_width\":375,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"8bf599d3-a968-4c11-b863-b3ec3cacbd19\",\"roots\":{\"p1085\":\"a5ce43a9-1f18-4cca-aa0d-ca391e7afa8f\"},\"root_ids\":[\"p1085\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1085"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.strip(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    "    spread=\"jitter\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Spike plot\n",
    "\n",
    "Spike plots show the count of each value measured. They are only effective if the measurements take on discrete values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"c2eae5d6-119c-41d0-af7a-4cf6dffa4092\" data-root-id=\"p1129\" style=\"display: contents;\"></div>\n"
      ]
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     "metadata": {},
     "output_type": "display_data"
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       "(function(root) {\n",
       "  function embed_document(root) {\n",
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correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1143\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1144\",\"attributes\":{\"axis\":{\"id\":\"p1140\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1149\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1145\"}}}],\"frame_width\":375,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"9180b6d9-e62c-471c-a014-055eae317339\",\"roots\":{\"p1129\":\"c2eae5d6-119c-41d0-af7a-4cf6dffa4092\"},\"root_ids\":[\"p1129\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1129"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.spike(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that when the spikes are in the \"stacked\" arrangement as above (as is default), the count values cannot be ascertained, only compared. We can display the counts using the `arranged=\"overlay\"` keyword argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"c0cc3bfe-5eba-4f34-ba6b-bab4c9b45345\" data-root-id=\"p1218\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"8b4a0a5e-9cd9-4aa2-80b1-dd91e61b3b39\":{\"version\":\"3.2.1\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"Figure\",\"id\":\"p1218\",\"attributes\":{\"x_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1220\"},\"y_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1217\",\"attributes\":{\"start\":0}},\"x_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1227\"},\"y_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1228\"},\"title\":{\"type\":\"object\",\"name\":\"Title\",\"id\":\"p1225\"},\"renderers\":[{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1255\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1246\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1247\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1248\"},\"data\":{\"type\":\"map\",\"entries\":[[\"index\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"AAAAAAEAAAACAAAAAwAAAAQAAAAFAAAABgAAAAcAAAAIAAAACQAAAAoAAAALAAAADAAAAA0AAAAOAAAADwAAAA==\"},\"shape\":[16],\"dtype\":\"int32\",\"order\":\"little\"}],[\"percent 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correct\"},\"y1\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"line_width\":{\"type\":\"value\",\"value\":2}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1265\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y0\":{\"type\":\"value\",\"value\":0},\"x1\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y1\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"line_width\":{\"type\":\"value\",\"value\":2}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1266\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y0\":{\"type\":\"value\",\"value\":0},\"x1\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y1\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"line_width\":{\"type\":\"value\",\"value\":2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1279\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1270\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1271\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1272\"},\"data\":{\"type\":\"map\",\"entries\":[[\"index\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"AAAAAAEAAAACAAAAAwAAAAQAAAAFAAAABgAAAAcAAAAIAAAACQAAAAoAAAALAAAADAAAAA0AAAAOAAAADwAAAA==\"},\"shape\":[16],\"dtype\":\"int32\",\"order\":\"little\"}],[\"percent 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correct\"},\"y\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#1f77b3\"},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b3\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1277\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#1f77b3\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b3\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1278\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#1f77b3\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b3\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1291\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1282\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1283\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1284\"},\"data\":{\"type\":\"map\",\"entries\":[[\"index\",{\"type\":\"ndarray\",\"array\":{\"type\":\"bytes\",\"data\":\"AAAAAAEAAAACAAAAAwAAAAQAAAAFAAAABgAAAAcAAAAIAAAACQAAAAoAAAALAAAADAAAAA0AAAAOAAAADwAAABAAAAARAAAAEgAAABMAAAA=\"},\"shape\":[20],\"dtype\":\"int32\",\"order\":\"little\"}],[\"percent 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correct\"},\"y\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"fill_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1289\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Circle\",\"id\":\"p1290\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"percent correct\"},\"y\":{\"type\":\"field\",\"field\":\"__count\"},\"line_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"value\",\"value\":\"#ff7e0e\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1226\",\"attributes\":{\"tools\":[{\"type\":\"object\",\"name\":\"PanTool\",\"id\":\"p1239\"},{\"type\":\"object\",\"name\":\"WheelZoomTool\",\"id\":\"p1240\"},{\"type\":\"object\",\"name\":\"BoxZoomTool\",\"id\":\"p1241\",\"attributes\":{\"overlay\":{\"type\":\"object\",\"name\":\"BoxAnnotation\",\"id\":\"p1242\",\"attributes\":{\"syncable\":false,\"level\":\"overlay\",\"visible\":false,\"left_units\":\"canvas\",\"right_units\":\"canvas\",\"bottom_units\":\"canvas\",\"top_units\":\"canvas\",\"line_color\":\"black\",\"line_alpha\":1.0,\"line_width\":2,\"line_dash\":[4,4],\"fill_color\":\"lightgrey\",\"fill_alpha\":0.5}}}},{\"type\":\"object\",\"name\":\"SaveTool\",\"id\":\"p1243\"},{\"type\":\"object\",\"name\":\"ResetTool\",\"id\":\"p1244\"},{\"type\":\"object\",\"name\":\"HelpTool\",\"id\":\"p1245\"}]}},\"toolbar_location\":\"above\",\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1234\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1235\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1236\"},\"axis_label\":\"count\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1237\"}}}],\"right\":[{\"type\":\"object\",\"name\":\"Legend\",\"id\":\"p1294\",\"attributes\":{\"location\":\"center\",\"click_policy\":\"hide\",\"items\":[{\"type\":\"object\",\"name\":\"LegendItem\",\"id\":\"p1295\",\"attributes\":{\"label\":{\"type\":\"value\",\"value\":\"insomniac\"},\"renderers\":[{\"id\":\"p1255\"},{\"id\":\"p1279\"}]}},{\"type\":\"object\",\"name\":\"LegendItem\",\"id\":\"p1296\",\"attributes\":{\"label\":{\"type\":\"value\",\"value\":\"normal\"},\"renderers\":[{\"id\":\"p1267\"},{\"id\":\"p1291\"}]}}]}}],\"below\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1229\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1230\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1231\"},\"axis_label\":\"percent correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1232\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1233\",\"attributes\":{\"axis\":{\"id\":\"p1229\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1238\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1234\"}}}],\"frame_width\":375,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"8b4a0a5e-9cd9-4aa2-80b1-dd91e61b3b39\",\"roots\":{\"p1218\":\"c0cc3bfe-5eba-4f34-ba6b-bab4c9b45345\"},\"root_ids\":[\"p1218\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1218"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.spike(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    "    arrangement=\"overlay\",\n",
    "    style=\"spike-dot\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strip-box plot\n",
    "\n",
    "For a strip-box plot, a strip plot and box plot are overlaid with reasonable defaults for the box plot to enable visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"e6150bb4-0895-4643-9ac9-60be7804c115\" data-root-id=\"p1310\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
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       "  const render_items = [{\"docid\":\"e75dd331-fbc1-45ba-998e-181ac415707b\",\"roots\":{\"p1310\":\"e6150bb4-0895-4643-9ac9-60be7804c115\"},\"root_ids\":[\"p1310\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1310"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.stripbox(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    "    spread=\"jitter\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histogram\n",
    "\n",
    "For histograms, the number of bins are automatically chosen using the [Freedman-Diaconis rule](https://en.wikipedia.org/wiki/Freedman–Diaconis_rule)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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     "metadata": {},
     "output_type": "display_data"
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       "  const render_items = [{\"docid\":\"26f7d063-df48-4775-9915-9b5df3c0cf01\",\"roots\":{\"p1418\":\"a93f2ce1-4caa-449a-873a-a5eeee389212\"},\"root_ids\":[\"p1418\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1418"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.histogram(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strip-histogram\n",
    "\n",
    "Strip plots may also be combined with histograms. By default, the histograms are normalized and mirrored, similar to a [violin plot](https://en.wikipedia.org/wiki/Violin_plot)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
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       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
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       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
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       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
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     },
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      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1599"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.striphistogram(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    "    spread=\"swarm\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ECDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"b8e0601c-a9a2-4026-a188-cfe03a729ea0\" data-root-id=\"p1682\" style=\"display: contents;\"></div>\n"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
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       "  const render_items = [{\"docid\":\"5648ef0e-063c-4134-8970-5179e08c1a60\",\"roots\":{\"p1682\":\"b8e0601c-a9a2-4026-a188-cfe03a729ea0\"},\"root_ids\":[\"p1682\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1682"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.ecdf(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=\"sleeper\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the ECDFs show a clear difference. Insomniacs have a distribution that is shifted leftward. This is most clearly revealed in the ECDF."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Customization with iqplot\n",
    "\n",
    "You may have noticed in the above plots that I occasionally used keyword arguments beyond the seven arguments that are present in all of the function signatures. For example in the ECDF above, I used `style='staircase'`. These are plot-type-specific kwargs which enable customization.\n",
    "\n",
    "You can find out what kwargs are available for each function by reading their doc strings, e.g., with\n",
    "\n",
    "```python\n",
    "iqplot.box?\n",
    "```\n",
    "\n",
    "of by reading [the documentation](https://iqplot.github.io/). Any kwargs not in the function call signature are passed to `bokeh.plotting.figure()` when the figure is instantiated.\n",
    "\n",
    "In our examples of customization, we will use both gender and sleeper status as keyword arguments."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Customizing box plots\n",
    "\n",
    "We can also have vertical box plots using the `q_axis` kwarg."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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       "  const render_items = [{\"docid\":\"75a6e8e6-375c-44d0-94b5-01925d9bb36f\",\"roots\":{\"p1772\":\"e120dece-5a24-4334-bd29-77ea10736578\"},\"root_ids\":[\"p1772\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1772"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.box(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=[\"gender\", \"sleeper\"],\n",
    "    q_axis=\"y\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can independently specify properties of the marks using `box_kwargs`, `whisker_kwargs`, `median_kwargs`, and `outlier_kwargs`. For example, say we wanted our colors to be [Betancourt red](https://betanalpha.github.io/assets/case_studies/principled_bayesian_workflow.html#step_four:_build_a_generative_model19), and that we wanted the outliers to also be that color and use diamond glyphs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"ca6ec01b-5150-422e-ad5d-c9f36e4e5c0a\" data-root-id=\"p1855\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "  const docs_json = {\"fd636ccf-01e2-4132-9feb-4b7c21c72124\":{\"version\":\"3.2.1\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"Figure\",\"id\":\"p1855\",\"attributes\":{\"x_range\":{\"type\":\"object\",\"name\":\"FactorRange\",\"id\":\"p1854\",\"attributes\":{\"factors\":[[\"female\",\"insomniac\"],[\"female\",\"normal\"],[\"male\",\"insomniac\"],[\"male\",\"normal\"]]}},\"y_range\":{\"type\":\"object\",\"name\":\"DataRange1d\",\"id\":\"p1857\"},\"x_scale\":{\"type\":\"object\",\"name\":\"CategoricalScale\",\"id\":\"p1864\"},\"y_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1865\"},\"title\":{\"type\":\"object\",\"name\":\"Title\",\"id\":\"p1862\"},\"renderers\":[{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1895\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1883\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1884\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1885\"},\"data\":{\"type\":\"map\",\"entries\":[[\"middle\",[72.5,85.0,83.75,82.5]],[\"bottom\",[67.5,75.0,76.875,77.5]],[\"top\",[83.75,88.75,88.75,89.375]],[\"top_whisker\",[95.0,100.0,97.5,95.0]],[\"bottom_whisker\",[45.0,55.0,67.5,67.5]],[\"cat\",[[\"female\",\"insomniac\"],[\"female\",\"normal\"],[\"male\",\"insomniac\"],[\"male\",\"normal\"]]],[\"__label\",[\"female, insomniac\",\"female, normal\",\"male, insomniac\",\"male, normal\"]]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1896\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1897\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1892\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"cat\"},\"y0\":{\"type\":\"field\",\"field\":\"top\"},\"x1\":{\"type\":\"field\",\"field\":\"cat\"},\"y1\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_width\":{\"type\":\"value\",\"value\":2}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1893\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"cat\"},\"y0\":{\"type\":\"field\",\"field\":\"top\"},\"x1\":{\"type\":\"field\",\"field\":\"cat\"},\"y1\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"line_width\":{\"type\":\"value\",\"value\":2}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1894\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"cat\"},\"y0\":{\"type\":\"field\",\"field\":\"top\"},\"x1\":{\"type\":\"field\",\"field\":\"cat\"},\"y1\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"line_width\":{\"type\":\"value\",\"value\":2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1904\",\"attributes\":{\"data_source\":{\"id\":\"p1883\"},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1905\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1906\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1901\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"cat\"},\"y0\":{\"type\":\"field\",\"field\":\"bottom\"},\"x1\":{\"type\":\"field\",\"field\":\"cat\"},\"y1\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_width\":{\"type\":\"value\",\"value\":2}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1902\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"cat\"},\"y0\":{\"type\":\"field\",\"field\":\"bottom\"},\"x1\":{\"type\":\"field\",\"field\":\"cat\"},\"y1\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"line_width\":{\"type\":\"value\",\"value\":2}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Segment\",\"id\":\"p1903\",\"attributes\":{\"x0\":{\"type\":\"field\",\"field\":\"cat\"},\"y0\":{\"type\":\"field\",\"field\":\"bottom\"},\"x1\":{\"type\":\"field\",\"field\":\"cat\"},\"y1\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"line_width\":{\"type\":\"value\",\"value\":2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1913\",\"attributes\":{\"data_source\":{\"id\":\"p1883\"},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1914\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1915\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1910\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.1},\"bottom\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"top\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_width\":{\"type\":\"value\",\"value\":2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1911\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.1},\"bottom\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"top\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"line_width\":{\"type\":\"value\",\"value\":2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1912\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.1},\"bottom\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"top\":{\"type\":\"field\",\"field\":\"top_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"line_width\":{\"type\":\"value\",\"value\":2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1922\",\"attributes\":{\"data_source\":{\"id\":\"p1883\"},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1923\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1924\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1919\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.1},\"bottom\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"top\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_width\":{\"type\":\"value\",\"value\":2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1920\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.1},\"bottom\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"top\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"line_width\":{\"type\":\"value\",\"value\":2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1921\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.1},\"bottom\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"top\":{\"type\":\"field\",\"field\":\"bottom_whisker\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"line_width\":{\"type\":\"value\",\"value\":2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1931\",\"attributes\":{\"data_source\":{\"id\":\"p1883\"},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1932\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1933\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1928\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.4},\"bottom\":{\"type\":\"field\",\"field\":\"bottom\"},\"top\":{\"type\":\"field\",\"field\":\"top\"},\"line_color\":{\"type\":\"value\",\"value\":null},\"fill_color\":{\"type\":\"value\",\"value\":\"#7C0000\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1929\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.4},\"bottom\":{\"type\":\"field\",\"field\":\"bottom\"},\"top\":{\"type\":\"field\",\"field\":\"top\"},\"line_color\":{\"type\":\"value\",\"value\":null},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1930\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.4},\"bottom\":{\"type\":\"field\",\"field\":\"bottom\"},\"top\":{\"type\":\"field\",\"field\":\"top\"},\"line_color\":{\"type\":\"value\",\"value\":null},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1940\",\"attributes\":{\"data_source\":{\"id\":\"p1883\"},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1941\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1942\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1937\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.4},\"bottom\":{\"type\":\"field\",\"field\":\"middle\"},\"top\":{\"type\":\"field\",\"field\":\"middle\"},\"line_color\":{\"type\":\"value\",\"value\":\"white\"},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1938\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.4},\"bottom\":{\"type\":\"field\",\"field\":\"middle\"},\"top\":{\"type\":\"field\",\"field\":\"middle\"},\"line_color\":{\"type\":\"value\",\"value\":\"white\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"VBar\",\"id\":\"p1939\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"width\":{\"type\":\"value\",\"value\":0.4},\"bottom\":{\"type\":\"field\",\"field\":\"middle\"},\"top\":{\"type\":\"field\",\"field\":\"middle\"},\"line_color\":{\"type\":\"value\",\"value\":\"white\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"value\",\"value\":\"#1f77b4\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2}}}}},{\"type\":\"object\",\"name\":\"GlyphRenderer\",\"id\":\"p1949\",\"attributes\":{\"data_source\":{\"type\":\"object\",\"name\":\"ColumnDataSource\",\"id\":\"p1886\",\"attributes\":{\"selected\":{\"type\":\"object\",\"name\":\"Selection\",\"id\":\"p1887\",\"attributes\":{\"indices\":[],\"line_indices\":[]}},\"selection_policy\":{\"type\":\"object\",\"name\":\"UnionRenderers\",\"id\":\"p1888\"},\"data\":{\"type\":\"map\",\"entries\":[[\"gender\",[\"male\",\"male\"]],[\"percent correct\",[57.5,40.0]],[\"sleeper\",[\"normal\",\"normal\"]],[\"cat\",[[\"male\",\"normal\"],[\"male\",\"normal\"]]],[\"__label\",[\"male, normal\",\"male, normal\"]]]}}},\"view\":{\"type\":\"object\",\"name\":\"CDSView\",\"id\":\"p1950\",\"attributes\":{\"filter\":{\"type\":\"object\",\"name\":\"AllIndices\",\"id\":\"p1951\"}}},\"glyph\":{\"type\":\"object\",\"name\":\"Scatter\",\"id\":\"p1946\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"y\":{\"type\":\"field\",\"field\":\"percent correct\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"fill_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"marker\":{\"type\":\"value\",\"value\":\"diamond\"}}},\"nonselection_glyph\":{\"type\":\"object\",\"name\":\"Scatter\",\"id\":\"p1947\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"y\":{\"type\":\"field\",\"field\":\"percent correct\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.1},\"fill_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.1},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.1},\"marker\":{\"type\":\"value\",\"value\":\"diamond\"}}},\"muted_glyph\":{\"type\":\"object\",\"name\":\"Scatter\",\"id\":\"p1948\",\"attributes\":{\"x\":{\"type\":\"field\",\"field\":\"cat\"},\"y\":{\"type\":\"field\",\"field\":\"percent correct\"},\"line_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"line_alpha\":{\"type\":\"value\",\"value\":0.2},\"fill_color\":{\"type\":\"value\",\"value\":\"#7C0000\"},\"fill_alpha\":{\"type\":\"value\",\"value\":0.2},\"hatch_alpha\":{\"type\":\"value\",\"value\":0.2},\"marker\":{\"type\":\"value\",\"value\":\"diamond\"}}}}}],\"toolbar\":{\"type\":\"object\",\"name\":\"Toolbar\",\"id\":\"p1863\",\"attributes\":{\"tools\":[{\"type\":\"object\",\"name\":\"PanTool\",\"id\":\"p1876\"},{\"type\":\"object\",\"name\":\"WheelZoomTool\",\"id\":\"p1877\"},{\"type\":\"object\",\"name\":\"BoxZoomTool\",\"id\":\"p1878\",\"attributes\":{\"overlay\":{\"type\":\"object\",\"name\":\"BoxAnnotation\",\"id\":\"p1879\",\"attributes\":{\"syncable\":false,\"level\":\"overlay\",\"visible\":false,\"left_units\":\"canvas\",\"right_units\":\"canvas\",\"bottom_units\":\"canvas\",\"top_units\":\"canvas\",\"line_color\":\"black\",\"line_alpha\":1.0,\"line_width\":2,\"line_dash\":[4,4],\"fill_color\":\"lightgrey\",\"fill_alpha\":0.5}}}},{\"type\":\"object\",\"name\":\"SaveTool\",\"id\":\"p1880\"},{\"type\":\"object\",\"name\":\"ResetTool\",\"id\":\"p1881\"},{\"type\":\"object\",\"name\":\"HelpTool\",\"id\":\"p1882\"}]}},\"toolbar_location\":\"above\",\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"p1871\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"p1872\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"p1873\"},\"axis_label\":\"percent correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1874\"}}}],\"below\":[{\"type\":\"object\",\"name\":\"CategoricalAxis\",\"id\":\"p1866\",\"attributes\":{\"ticker\":{\"type\":\"object\",\"name\":\"CategoricalTicker\",\"id\":\"p1867\"},\"formatter\":{\"type\":\"object\",\"name\":\"CategoricalTickFormatter\",\"id\":\"p1868\"},\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p1869\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1870\",\"attributes\":{\"axis\":{\"id\":\"p1866\"},\"grid_line_color\":null}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p1875\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p1871\"}}}],\"frame_width\":375,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"fd636ccf-01e2-4132-9feb-4b7c21c72124\",\"roots\":{\"p1855\":\"ca6ec01b-5150-422e-ad5d-c9f36e4e5c0a\"},\"root_ids\":[\"p1855\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1855"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.box(\n",
    "    data=df,\n",
    "    q='percent correct',\n",
    "    cats=['gender', 'sleeper'],\n",
    "    q_axis='y',\n",
    "    whisker_caps=True,\n",
    "    outlier_marker='diamond',\n",
    "    box_kwargs=dict(fill_color='#7C0000'),\n",
    "    whisker_kwargs=dict(line_color='#7C0000', line_width=2),\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Customzing strip plots\n",
    "\n",
    "To help alleviate the overlap problem, we can make a strip plot with dash markers and add some transparency."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"d439a2d8-352f-481f-ad66-ed9431e5fb6d\" data-root-id=\"p1953\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
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       "    }, 10, root)\n",
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      "application/vnd.bokehjs_exec.v0+json": ""
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       "id": "p1953"
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   "source": [
    "p = iqplot.strip(\n",
    "    data=df,\n",
    "    q='percent correct',\n",
    "    cats=['gender', 'sleeper'],\n",
    "    marker='dash',\n",
    "    marker_kwargs=dict(alpha=0.5)\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I prefer jittering or swarming to this. Below, I add hover tools that give more information about the respective data points in a jittered strip plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/bois/anaconda3/envs/bebi103_build/lib/python3.11/site-packages/iqplot/cat.py:1771: UserWarning: 1 data points exceed maximum height. Consider using spread='jitter' or increasing the frame height.\n",
      "  warnings.warn(\n"
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    },
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       "  const render_items = [{\"docid\":\"a425d60d-7889-4623-a89b-d604f7485d5a\",\"roots\":{\"p1996\":\"fcb02099-7fa9-4b51-83d5-b28fb8aaa7c6\"},\"root_ids\":[\"p1996\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p1996"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.strip(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=[\"gender\", \"sleeper\"],\n",
    "    spread=\"swarm\", # use spread='jitter' to add random jitter\n",
    "    tooltips=[(\"age\", \"@{age}\"), (\"participant number\", \"@{participant number}\")],\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note the warning that a data point exceeds the maximum spread allowed in a swarm plot such that data points overlap. For this reason, I often prefer jitter plots to swarm plots. In this particular case, because of the discrete values taken by the percent correct, a swarm plot is more effective at showing all data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Customizing histograms\n",
    "\n",
    "We can plot normalized histograms using the `density` kwarg, and we'll make the plot a little wider to support the legend."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p2054\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p2055\",\"attributes\":{\"axis\":{\"id\":\"p2051\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p2060\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p2056\"}}}],\"frame_width\":525,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"acb11ead-d926-4ab4-b461-5cbb1925249a\",\"roots\":{\"p2040\":\"c3216310-705c-4736-8b45-868da5d547f6\"},\"root_ids\":[\"p2040\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p2040"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the histogram\n",
    "p = iqplot.histogram(\n",
    "    data=df,\n",
    "    q='percent correct',\n",
    "    cats=['gender', 'sleeper'],\n",
    "    density=True,\n",
    "    frame_width=525,\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Customizing ECDFs\n",
    "\n",
    "Instead of plotting a separate ECDF for each category, we can put all of the categories together on one ECDF and color the points by the categorical variable by using the `kind='colored'` kwarg. Note that if we do this, we can only have the \"dots\" style ECDF, not the formal staircase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "  <div id=\"c5c711a3-6752-4c0d-a450-42eea00484c7\" data-root-id=\"p2596\" style=\"display: contents;\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
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correct\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"p2610\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p2611\",\"attributes\":{\"axis\":{\"id\":\"p2607\"}}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"p2616\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"p2612\"}}}],\"frame_width\":375,\"frame_height\":275}}]}};\n",
       "  const render_items = [{\"docid\":\"5711dd46-4a8a-45b2-ae70-97e319772f5a\",\"roots\":{\"p2596\":\"c5c711a3-6752-4c0d-a450-42eea00484c7\"},\"root_ids\":[\"p2596\"]}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "p2596"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = iqplot.ecdf(\n",
    "    data=df,\n",
    "    q=\"percent correct\",\n",
    "    cats=[\"gender\", \"sleeper\"],\n",
    "    kind=\"colored\",\n",
    ")\n",
    "\n",
    "bokeh.io.show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In general, for customization, you should check [the documentation](https://iqplot.github.io/) to see what is available."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python implementation: CPython\n",
      "Python version       : 3.11.5\n",
      "IPython version      : 8.15.0\n",
      "\n",
      "pandas    : 2.0.3\n",
      "bokeh     : 3.2.1\n",
      "iqplot    : 0.3.5\n",
      "jupyterlab: 4.0.6\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -v -p pandas,bokeh,iqplot,jupyterlab"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}