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    "# Getting Started\n",
    "HuracanPy provides a standard way for working with cyclone track data from different sources.\n",
    "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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   "id": "5b1565ee-4e86-4053-ad73-0a7557b3e6cd",
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   "source": [
    "import huracanpy\n",
    "\n",
    "tracks = huracanpy.load(huracanpy.example_csv_file)\n",
    "print(tracks)"
   ]
  },
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   "cell_type": "markdown",
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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 or index tracks in this format."
   ]
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   "id": "960e9a7d-0cf2-4797-a297-c048eb739327",
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   "source": [
    "import huracanpy\n",
    "\n",
    "tracks = huracanpy.load(huracanpy.example_csv_file)\n",
    "\n",
    "track_groups = tracks.groupby(\"track_id\")\n",
    "\n",
    "# Selecting track by 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",
    "track_id1 = track_groups[1]\n",
    "\n",
    "# Iterating over all tracks\n",
    "# Each track will be a subset of the xarray Dataset with a unique track_id\n",
    "for n, track in track_groups:\n",
    "    # Do something with the track\n",
    "    print(track)"
   ]
  }
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