{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# National Solar Radiation Database (NSRDB)\n",
    "\n",
    "> The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations. The data are publicly available at no cost to the user and maintained by NREL. "
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Let's set our NREL API key."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "import os\n",
    "from nrel_dev_api import set_nrel_api_key\n",
    "from nrel_dev_api.solar import NSRDB_DataQuery, get_nsrdb_download_links, download_nsrdb_data\n",
    "\n",
    "\n",
    "# get and set NREL developer API key\n",
    "NREL_API_KEY = os.environ[\"NREL_API_KEY\"]\n",
    "set_nrel_api_key(NREL_API_KEY)"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Data Query\n",
    "\n",
    ">Find NSRDB datasets for a location"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Get information for a single location point using latitude and longitude."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "nsrdb_data_query = NSRDB_DataQuery(lat=21.204, lon=72.839)\n",
    "\n",
    "# check the outputs\n",
    "nsrdb_data_query.outputs"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Using a well-known text (WKT) representation of the geometry for which to extract data"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "nsrdb_data_query = NSRDB_DataQuery(wkt=\"POINT(91.287 23.832)\")\n",
    "\n",
    "# check the outputs\n",
    "nsrdb_data_query.outputs"
   ],
   "outputs": [],
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Data Downloader\n",
    "\n",
    "> Download solar irradiance and meteorological data for a location."
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Let's get all the available links for the year 2016."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "links = get_nsrdb_download_links(year=2016, lat=47.6, lon=-122.3)\n",
    "links"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "Once we have the available links, we can download the data of interest.\n",
    "\n",
    "Here, we will download from the first link."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "df = download_nsrdb_data(links[0], email=os.environ[\"EMAIL\"])"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "df.columns"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "df[[\"Temperature\", \"GHI\", \"Pressure\", \"Wind Speed\", \"Precipitable Water\"]]"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "> The index in the `DataFrame` returned automatically accounts for the leap years."
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "feb = df.loc[\"2016-02\"][[\"Year\", \"Month\", \"Day\", \"Minute\"]]\n",
    "feb.tail()"
   ],
   "outputs": [],
   "metadata": {}
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:nrel-dev-api]",
   "language": "python",
   "name": "conda-env-nrel-dev-api-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}