{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "URL: https://docs.bokeh.org/en/2.4.1/docs/gallery/iris_splom.html\n",
    "\n",
    "Most examples work across multiple plotting backends, this example is also available for:\n",
    "\n",
    "* [Bokeh - iris_splom_example](../bokeh/iris_splom_example.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import holoviews as hv\n",
    "from holoviews import opts\n",
    "\n",
    "hv.extension('matplotlib')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Declaring data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bokeh.sampledata.iris import flowers\n",
    "from holoviews.operation import gridmatrix\n",
    "\n",
    "ds = hv.Dataset(flowers)\n",
    "\n",
    "grouped_by_species = ds.groupby('species', container_type=hv.NdOverlay)\n",
    "grid = gridmatrix(grouped_by_species, diagonal_type=hv.Scatter)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "grid.opts(opts.Scatter(bgcolor='#efe8e2', alpha=0.4, s=16))"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
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 "nbformat": 4,
 "nbformat_minor": 4
}