{
 "cells": [
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   "source": [
    "## Using data layers to plot points on the surface of planets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook shows how to plot tabular data on the surface of a planet using WorldWide Telescope through [pywwt](https://pywwt.readthedocs.io/). You can find out more about using pywwt in the [documentation](https://pywwt.readthedocs.io).\n",
    "\n",
    "First, we need to connect to the WWT app. If WWT isn't running yet, activate the JupyterLab command palette from the View menu, and select \"WorldWide Telescope\". Then all we need to do is run:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pywwt.jupyter import connect_to_app\n",
    "wwt = await connect_to_app().becomes_ready()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the `wwt` variable will let us talk to the WWT app."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "wwt.set_view('Earth')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally we load a dataset and add a data layer in WWT:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.table import Table\n",
    "EARTHQUAKES = 'https://worldwidetelescope.github.io/pywwt/data/earthquakes_2010.csv'\n",
    "table = Table.read(EARTHQUAKES, delimiter=',', format='ascii.basic', fast_reader=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "layer = wwt.layers.add_data_layer(table=table, frame='Earth', lon_att='longitude', lat_att='latitude', color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Credits\n",
    "\n",
    "This notebook was prepared by Thomas Robitaille."
   ]
  }
 ],
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