{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a8373dcf-f097-454d-b97a-2f4e7bf20e62",
   "metadata": {},
   "source": [
    "# Kde"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2ccf9fd5-9d10-4522-961d-7e8d236213b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import hvplot.xarray  # noqa\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7ed6c65-2280-4741-b89b-721110628547",
   "metadata": {},
   "source": [
    "Kernel density estimate (`kde`) provides a mechanism for showing the distribution and spread of the data. In `hvplot` the method is exposed both as `kde` and `density`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e8680d48-02b1-4480-96e3-d0fd7807a804",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.tutorial.open_dataset('air_temperature').load()\n",
    "air = ds.air\n",
    "air1d = air.sel(lat=[25, 50, 75])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f33d3355-deaa-4bdf-befa-af20d2e46d7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "air1d.hvplot.kde('air', by='lat', alpha=0.5)"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}