{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "parameters"
    ]
   },
   "outputs": [],
   "source": [
    "flex_title = \"Bokeh plots\"\n",
    "flex_source_code = \"https://github.com/danielfrg/jupyter-flex/blob/master/examples/plots/bokeh.ipynb\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "meta"
    ]
   },
   "outputs": [],
   "source": [
    "import datetime\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from bokeh.sampledata.iris import flowers as df\n",
    "from bokeh.plotting import figure, show, output_notebook\n",
    "output_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.models import ColumnDataSource\n",
    "from bokeh.palettes import Category10\n",
    "from bokeh.transform import factor_cmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "size=600"
    ]
   },
   "source": [
    "## Column"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Species"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
   "outputs": [],
   "source": [
    "source = ColumnDataSource(df)\n",
    "color_map = factor_cmap('species', palette=Category10[3], factors=sorted(df.species.unique()))\n",
    "\n",
    "tooltips = [\n",
    "    (\"Sepal Width\", \"@sepal_width\"),\n",
    "    (\"Sepal Length\", \"@sepal_length\"),\n",
    "    (\"Species\", \"@species\"),\n",
    "]\n",
    "\n",
    "p = figure(tooltips=tooltips, sizing_mode=\"stretch_both\")\n",
    "# p = figure(tooltips=tooltips)\n",
    "\n",
    "p.circle(source=source, x='sepal_length', y='sepal_width', color=color_map, legend_field=\"species\", alpha=0.5, size=10)\n",
    "\n",
    "p.legend.title = 'Species'\n",
    "p.xaxis.axis_label = 'Sepal Length'\n",
    "p.yaxis.axis_label = 'Sepal Width'\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "size=400"
    ]
   },
   "source": [
    "## Column 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Species (Quantile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups = df.groupby(\"species\").sepal_length.quantile(np.arange(0, 1, 0.02))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "groups = groups.reset_index().rename(columns={\"level_1\": \"quantile\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
   "outputs": [],
   "source": [
    "source = ColumnDataSource(groups)\n",
    "color_map = factor_cmap('species', palette=Category10[3], factors=sorted(df.species.unique()))\n",
    "\n",
    "tooltips = [\n",
    "    (\"Sepal Length\", \"@sepal_length\"),\n",
    "    (\"Quantile\", \"@quantile\"),\n",
    "    (\"Species\", \"@species\"),\n",
    "]\n",
    "\n",
    "p = figure(tooltips=tooltips, sizing_mode=\"stretch_both\")\n",
    "# p = figure(tooltips=tooltips)\n",
    "\n",
    "p.circle(source=source, x='quantile', y='sepal_length', color=color_map, legend_field=\"species\", alpha=0.5, size=10)\n",
    "\n",
    "p.legend.title = 'Species'\n",
    "p.xaxis.axis_label = 'Quantile'\n",
    "p.yaxis.axis_label = 'Sepal Length'\n",
    "p.legend.location = \"top_left\"\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Petal Width"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.palettes import Greens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cuts = pd.cut(df.petal_width, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"cuts_str\"] = cuts.astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"cuts_mid\"] = cuts.apply(lambda x: x.mid).astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "source = ColumnDataSource(df)\n",
    "color_map = factor_cmap('cuts_mid', palette=Greens[7][:-2], factors=sorted(df.cuts_mid.unique(), reverse=True))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": [
     "chart"
    ]
   },
   "outputs": [],
   "source": [
    "tooltips = [\n",
    "    (\"Sepal Width\", \"@sepal_width\"),\n",
    "    (\"Sepal Length\", \"@sepal_length\"),\n",
    "    (\"Petal Width interval\", \"@cuts_str\"),\n",
    "    (\"Species\", \"@species\"),\n",
    "]\n",
    "\n",
    "p = figure(tooltips=tooltips, sizing_mode=\"stretch_both\")\n",
    "# p = figure(tooltips=tooltips)\n",
    "\n",
    "p.circle(source=source, x='sepal_length', y='sepal_width', color=color_map, legend_field=\"cuts_str\", alpha=0.8, size=10)\n",
    "\n",
    "p.legend.title = 'Petal Width'\n",
    "p.xaxis.axis_label = 'Sepal Length'\n",
    "p.yaxis.axis_label = 'Sepal Width'\n",
    "\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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