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    "# Getting Started\n",
    "## Opening files\n",
    "The first step is to load in some tracks. HuracanPy can load track data from various sources as an [xarray.Dataset](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html) with a minimal number of assumed variables (track_id, lon, lat, time) e.g."
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    "import huracanpy\n",
    "\n",
    "tracks = huracanpy.load(huracanpy.example_csv_file)\n",
    "print(tracks)"
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    "Each \"record\" corresponds to a TC point (time, lon, lat).\n",
    "\n",
    "Note that the data is one dimensional but represents multiple tracks.\n",
    "This is done rather than having track_id as an additional dimension to avoid having to add blank data to each track when they are not the same length.\n",
    "The `groupby` function, built in to xarray, allows us to easily loop over tracks in this format."
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    "# Iterating over all tracks\n",
    "# Each track will be a subset of the xarray Dataset with a unique track_id\n",
    "# The track_id is not necessarily an integer, it follows whatever you have loaded\n",
    "# e.g. could be a string for IBTrACS\n",
    "for track_id, track in tracks.groupby(\"track_id\"):\n",
    "    # Do something with the track\n",
    "    print(track_id, len(track.time))"
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    "With the data loaded, we can apply the functions from HuracanPy. The example below is\n",
    "using the `hrcn` accessor from HuracanPy. See the [accessor](accessor.ipynb) page for\n",
    "more details."
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    "# Quickly view the tracks\n",
    "tracks.hrcn.plot_tracks(intensity_var_name=\"wind10\")\n",
    "\n",
    "# Add a new variable to the tracks and plot this instead\n",
    "tracks = tracks.hrcn.add_is_land()\n",
    "tracks.hrcn.plot_tracks(intensity_var_name=\"is_land\")"
   ]
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   "source": [
    "For more in-depth examples see [example workflows](demo.ipynb) or the [examples gallery](../examples/index.rst).\n",
    "Or check the [API](../api/index.rst) to see everything included with HuracanPy."
   ]
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