Argopy_maps.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1a87f477-ede7-4723-afaf-ddd19e03549a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in /srv/conda/envs/notebook/lib/python3.9/site-packages (1.21.4)\n",
      "Collecting numpy\n",
      "  Using cached numpy-1.22.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (16.8 MB)\n",
      "Installing collected packages: numpy\n",
      "  Attempting uninstall: numpy\n",
      "    Found existing installation: numpy 1.21.4\n",
      "    Uninstalling numpy-1.21.4:\n",
      "      Successfully uninstalled numpy-1.21.4\n",
      "Successfully installed numpy-1.22.3\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install -U numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "06b08b38-308d-477b-82f8-55c5bc454e05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting argopy\n",
      "  Using cached argopy-0.1.10-py3-none-any.whl (119 kB)\n",
      "Requirement already satisfied: scikit-learn<2.0 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from argopy) (1.0.1)\n",
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      "Requirement already satisfied: aiohttp>=3.6.2 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from argopy) (3.8.1)\n",
      "Requirement already satisfied: netCDF4<1.5.9 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from argopy) (1.5.8)\n",
      "Requirement already satisfied: xarray>=0.15.1 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from argopy) (0.20.1)\n",
      "Collecting gsw<=3.4.0\n",
      "  Using cached gsw-3.4.0-cp39-cp39-linux_x86_64.whl\n",
      "Requirement already satisfied: packaging>=20.4 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from argopy) (21.3)\n",
      "Requirement already satisfied: scipy>=1.1.0 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from argopy) (1.7.3)\n",
      "Collecting erddapy>=0.6\n",
      "  Using cached erddapy-1.2.0-py3-none-any.whl (17 kB)\n",
      "Requirement already satisfied: multidict<7.0,>=4.5 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from aiohttp>=3.6.2->argopy) (5.2.0)\n",
      "Requirement already satisfied: aiosignal>=1.1.2 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from aiohttp>=3.6.2->argopy) (1.2.0)\n",
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      "Requirement already satisfied: attrs>=17.3.0 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from aiohttp>=3.6.2->argopy) (21.2.0)\n",
      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from aiohttp>=3.6.2->argopy) (4.0.1)\n",
      "Requirement already satisfied: frozenlist>=1.1.1 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from aiohttp>=3.6.2->argopy) (1.2.0)\n",
      "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from aiohttp>=3.6.2->argopy) (2.0.0)\n",
      "Requirement already satisfied: cloudpickle>=1.1.1 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from dask>=2.9->argopy) (2.0.0)\n",
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      "Requirement already satisfied: numpy in /srv/conda/envs/notebook/lib/python3.9/site-packages (from gsw<=3.4.0->argopy) (1.22.3)\n",
      "Requirement already satisfied: cftime in /srv/conda/envs/notebook/lib/python3.9/site-packages (from netCDF4<1.5.9->argopy) (1.5.1.1)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from packaging>=20.4->argopy) (3.0.6)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from scikit-learn<2.0->argopy) (3.0.0)\n",
      "Requirement already satisfied: joblib>=0.11 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from scikit-learn<2.0->argopy) (1.1.0)\n",
      "Requirement already satisfied: typing-extensions>=3.6.5 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from async-timeout<5.0,>=4.0.0a3->aiohttp>=3.6.2->argopy) (4.0.1)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from pandas>=0.20.3->erddapy>=0.6->argopy) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2017.3 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from pandas>=0.20.3->erddapy>=0.6->argopy) (2021.3)\n",
      "Requirement already satisfied: locket in /srv/conda/envs/notebook/lib/python3.9/site-packages/locket-0.2.1-py3.9.egg (from partd>=0.3.10->dask>=2.9->argopy) (0.2.1)\n",
      "Requirement already satisfied: idna>=2.0 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from yarl<2.0,>=1.0->aiohttp>=3.6.2->argopy) (3.1)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from requests->erddapy>=0.6->argopy) (1.26.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from requests->erddapy>=0.6->argopy) (2021.10.8)\n",
      "Requirement already satisfied: six>=1.5 in /srv/conda/envs/notebook/lib/python3.9/site-packages (from python-dateutil>=2.7.3->pandas>=0.20.3->erddapy>=0.6->argopy) (1.16.0)\n",
      "Installing collected packages: gsw, erddapy, argopy\n",
      "Successfully installed argopy-0.1.10 erddapy-1.2.0 gsw-3.4.0\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install argopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "742908db-c722-4772-a5e1-2b47c47b0485",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "de8e7176-fddd-4cf8-bbc2-f3b1eba8cc39",
   "metadata": {},
   "outputs": [],
   "source": [
    "import argopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b8a0cbc0-bb2e-4140-bf27-8a0b836b664f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from argopy import DataFetcher as ArgoDataFetcher"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aab20be4-a5cf-433c-9e2e-c9d7d44f91c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<argopy.options.set_options at 0x7f16146e7850>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "argopy.set_options(src='erddap')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c42c28c8-86e4-4d10-af51-114d23279303",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:                (N_POINTS: 20966)\n",
      "Coordinates:\n",
      "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 20962 20963 20964 20965\n",
      "    LATITUDE               (N_POINTS) float64 -39.93 -39.93 ... -44.16 -44.16\n",
      "    LONGITUDE              (N_POINTS) float64 10.81 10.81 10.81 ... 92.65 92.65\n",
      "    TIME                   (N_POINTS) datetime64[ns] 2008-02-25T04:03:00 ... ...\n",
      "Data variables: (12/13)\n",
      "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 2 2 2 2 2 2 2 2\n",
      "    CYCLE_NUMBER           (N_POINTS) int64 0 0 0 0 0 0 ... 192 192 192 192 192\n",
      "    DATA_MODE              (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'D' 'D' 'D' 'D'\n",
      "    DIRECTION              (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'\n",
      "    PLATFORM_NUMBER        (N_POINTS) int64 1900857 1900857 ... 1900857 1900857\n",
      "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
      "    ...                     ...\n",
      "    PRES_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
      "    PSAL                   (N_POINTS) float64 34.68 34.68 34.69 ... 34.71 34.72\n",
      "    PSAL_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
      "    TEMP                   (N_POINTS) float64 16.14 16.14 16.03 ... 2.422 2.413\n",
      "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
      "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
      "Attributes:\n",
      "    DATA_ID:              ARGO\n",
      "    DOI:                  http://doi.org/10.17882/42182\n",
      "    Fetched_from:         https://www.ifremer.fr/erddap\n",
      "    Fetched_by:           jovyan\n",
      "    Fetched_date:         2022/03/13\n",
      "    Fetched_constraints:  phy;WMO1900857\n",
      "    Fetched_uri:          ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
      "    history:              Variables filtered according to DATA_MODE; Variable...\n"
     ]
    }
   ],
   "source": [
    "with argopy.set_options(src='erddap'):\n",
    "   ds = ArgoDataFetcher().float(1900857).to_xarray()\n",
    "   print(ds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0ee28488-0087-422f-bb84-d784c018c7c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "#ds.plot.scatter(x='LONGITUDE', y='LATITUDE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a2ca7086-ab8b-43c6-95cd-16d97d6769b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9b5ffd2493594011a94b80a0bdf10871",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HTML(value='<table><tr><td><img src=\"https://img.shields.io/static/v1?style=flat-square&label=src%20argovis%20…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<argopy.utilities.monitor_status at 0x7f2c9ff71f10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "argopy.status()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0746be11-536a-4138-8569-0ab89903ea61",
   "metadata": {},
   "outputs": [],
   "source": [
    "from argopy import IndexFetcher as ArgoIndexFetcher\n",
    "idx = ArgoIndexFetcher().float([6902745, 6902746]).load()\n",
    "fig, ax = idx.plot('trajectory')\n",
    " # Trajectory is the default plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2fcddf4b-8aa4-430f-8044-fb73b8687270",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from argopy import IndexFetcher as ArgoIndexFetcher\n",
    "idx = ArgoIndexFetcher().float([6903574, 6903094,5906624, 5906308, 5906306, 5906305, 5906296, 5906295, 5906294, 5906293, 5906250, \n",
    "          5906249, 5906246, 5906244, 5906227, 5906226, 5906224, 5906223, 5906222, 5906221, 5906220, 5906219, 5906218, 5906211, 5906209, 5906208, 5906207, 5906206, 5906205, 5906204, 2902823, 2902762]).load()\n",
    "fig, ax = idx.plot('trajectory')\n",
    " # Trajectory is the default plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b4d456d4-589a-4f64-b487-7818247107ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#net cdf files are downloaded for nitrate\n",
    "\n",
    "idx1 = ArgoIndexFetcher().float([4903026, 5906026, 5906045, 5906293, 5906296, 5906297, 5906449, 5906468,\n",
    "                                 5906484, 5906486, 5906507, 5906094]).load() \n",
    "fig, ax = idx1.plot('trajectory')\n",
    " # Trajectory is the default plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d961ad26-29eb-4db7-8694-42237bbf4896",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "cd66cc86-cfef-47cb-a3af-bec6228353c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"100%\"\n",
       "            height=\"1000\"\n",
       "            src=\"https://fleetmonitoring.euro-argo.eu\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "            \n",
       "        ></iframe>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.lib.display.IFrame at 0x7f15aa63ceb0>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Comment this out to see the stations, select nitrate from below, year 2020\n",
    "argopy.dashboard()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9ba96c1-9046-48f0-80a9-bb5afc9dd895",
   "metadata": {},
   "outputs": [],
   "source": [
    "stations_O2=[6903574, 6903094, 5906624, 5906308, 5906306, 5906305, 5906296, 5906295, 5906294, 5906293, 5906250, \n",
    "             5906249, 5906246, 5906244, 5906227, 5906226, 5906224, 5906223, 5906222, 5906221, 5906220, 5906219,\n",
    "             5906218, 5906211, 5906209, 5906208, 5906207, 5906206, 5906205, 5906204, 2902823, 2902762]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4b3ae67-a943-4a89-a776-25ed42c18a2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Comment this out to see a particular station\n",
    "#argopy.dashboard(wmo=6902746)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "934cc849-b831-48b7-8fdd-7d277bb5901b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#stations that were deployed in 2020 and have nitrate data (skipped one station since its data has some issue), year o deployment 2020 (33 in total)\n",
    "#stations_NO3=[6903574, 6903094, 5906624, 5906308, 5906306, 5906305, 5906296, 5906295, 5906294, 5906293, 5906250, \n",
    "#          5906249, 5906246, 5906244, 5906227, 5906226, 5906224, 5906223, 5906222, 5906221, 5906220, 5906219,\n",
    "#          5906218, 5906211, 5906209, 5906208, 5906207, 5906206, 5906205, 5906204, 2902823, 2902762]"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/21)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) &lt;U1 &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    DIRECTION              (N_POINTS) &lt;U1 &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    SIG0                   (N_POINTS) float64 26.75 26.75 26.76 ... 28.08 28.08\n",
       "    CNDC                   (N_POINTS) float64 39.04 39.05 39.06 ... 29.19 29.21\n",
       "    N2                     (N_POINTS) float64 nan 3.951e-05 ... 1.898e-07 nan\n",
       "    PV                     (N_POINTS) float64 nan 5.419e-10 ... 2.606e-12 nan\n",
       "    PTEMP                  (N_POINTS) float64 11.03 11.03 ... -0.8124 -0.8212\n",
       "    SOUND_SPEED            (N_POINTS) float64 1.493e+03 1.493e+03 ... 1.478e+03\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          [&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-470478e4-451d-43bc-8805-671a5f0ad0a3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-470478e4-451d-43bc-8805-671a5f0ad0a3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>N_POINTS</span>: 29267</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-562b775a-8768-4fd3-815e-41221426a4d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-562b775a-8768-4fd3-815e-41221426a4d9' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>N_POINTS</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 29263 29264 29265 29266</div><input id='attrs-c85a13dd-bd35-4913-9ae1-59eaae39c122' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c85a13dd-bd35-4913-9ae1-59eaae39c122' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adf013b4-e7ae-4a5f-b7e7-2df2e6d54e32' class='xr-var-data-in' type='checkbox'><label for='data-adf013b4-e7ae-4a5f-b7e7-2df2e6d54e32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 29264, 29265, 29266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LATITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>67.5 67.5 67.5 ... 67.71 67.71</div><input id='attrs-ba329dad-ce8f-474f-82f0-13ec7ea21212' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba329dad-ce8f-474f-82f0-13ec7ea21212' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3bb3c4b-d50f-4a58-90bc-b413da5cb38f' class='xr-var-data-in' type='checkbox'><label for='data-c3bb3c4b-d50f-4a58-90bc-b413da5cb38f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>actual_range :</span></dt><dd>[65.15173167 67.73593   ]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Latitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([67.50215333, 67.50215333, 67.50215333, ..., 67.71014167,\n",
       "       67.71014167, 67.71014167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LONGITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.531 -0.531 ... -2.693 -2.693</div><input id='attrs-2828d3b6-b4f1-4600-a9fa-c4a9ae681ed4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2828d3b6-b4f1-4600-a9fa-c4a9ae681ed4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b84ce8-764b-49bb-af99-228a567aa67a' class='xr-var-data-in' type='checkbox'><label for='data-d1b84ce8-764b-49bb-af99-228a567aa67a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>actual_range :</span></dt><dd>[-5.31154333 -0.50186833]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Longitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([-0.53096833, -0.53096833, -0.53096833, ..., -2.69315   ,\n",
       "       -2.69315   , -2.69315   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-25T22:18:00 ... 2022-03-...</div><input id='attrs-4f93794a-ffd7-448e-b7a1-5c29a4dd9cda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f93794a-ffd7-448e-b7a1-5c29a4dd9cda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efe99335-f93c-4677-b141-04046841e9f9' class='xr-var-data-in' type='checkbox'><label for='data-efe99335-f93c-4677-b141-04046841e9f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Time</dd><dt><span>actual_range :</span></dt><dd>[1.59839388e+09 1.64682480e+09]</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Julian day (UTC) of the station relative to REFERENCE_DATE_TIME</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-25T22:18:00.000000000&#x27;, &#x27;2020-08-25T22:18:00.000000000&#x27;,\n",
       "       &#x27;2020-08-25T22:18:00.000000000&#x27;, ...,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;, &#x27;2022-03-09T11:20:00.000000000&#x27;,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d2072f4-f0f6-40e3-9f54-38ab0613d86f' class='xr-section-summary-in' type='checkbox'  ><label for='section-5d2072f4-f0f6-40e3-9f54-38ab0613d86f' class='xr-section-summary' >Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CONFIG_MISSION_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3</div><input id='attrs-23baa26c-2fac-4b6e-a19b-3e7675b50140' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23baa26c-2fac-4b6e-a19b-3e7675b50140' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de98412d-ae93-4615-929d-8442c1c690fc' class='xr-var-data-in' type='checkbox'><label for='data-de98412d-ae93-4615-929d-8442c1c690fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 3]</dd><dt><span>colorBarMaximum :</span></dt><dd>100.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>conventions :</span></dt><dd>1...N, 1 : first complete mission</dd><dt><span>ioos_category :</span></dt><dd>Statistics</dd><dt><span>long_name :</span></dt><dd>Unique number denoting the missions performed by the float</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 3, 3, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CYCLE_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 ... 113 113 113 113 113</div><input id='attrs-d8ccc6d6-3906-4644-b5bd-ac7367ef7bc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8ccc6d6-3906-4644-b5bd-ac7367ef7bc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81f71b63-d774-4a73-ad16-e1dffe7d9538' class='xr-var-data-in' type='checkbox'><label for='data-81f71b63-d774-4a73-ad16-e1dffe7d9538' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float cycle number</dd><dt><span>convention :</span></dt><dd>0..N, 0 : launch cycle (if exists), 1 : first complete cycle</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([  1,   1,   1, ..., 113, 113, 113])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DATA_MODE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-648c41be-2ce4-4019-927d-ee0fa5accc53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-648c41be-2ce4-4019-927d-ee0fa5accc53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d5d840b-466e-476b-a306-e42d2ff2986c' class='xr-var-data-in' type='checkbox'><label for='data-0d5d840b-466e-476b-a306-e42d2ff2986c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delayed mode or real time data</dd><dt><span>convention :</span></dt><dd>R : real time; D : delayed mode; A : real time with adjustment</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;R&#x27;, &#x27;R&#x27;, &#x27;R&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DIRECTION</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-ea5406c2-da79-4924-b6e7-0b212bbced61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea5406c2-da79-4924-b6e7-0b212bbced61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-770972b8-6152-4ed1-bb97-3a89276141d1' class='xr-var-data-in' type='checkbox'><label for='data-770972b8-6152-4ed1-bb97-3a89276141d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Direction of the station profiles</dd><dt><span>convention :</span></dt><dd>A: ascending profiles, D: descending profiles</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;D&#x27;, &#x27;D&#x27;, &#x27;D&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PLATFORM_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>6903574 6903574 ... 6903574 6903574</div><input id='attrs-6ac1d590-b39e-4d27-a248-f2cc86f1d064' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ac1d590-b39e-4d27-a248-f2cc86f1d064' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef1b10f4-d1fd-474f-a7d1-78b910f7dfe2' class='xr-var-data-in' type='checkbox'><label for='data-ef1b10f4-d1fd-474f-a7d1-78b910f7dfe2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float unique identifier</dd><dt><span>convention :</span></dt><dd>WMO float identifier : A9IIIII</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([6903574, 6903574, 6903574, ..., 6903574, 6903574, 6903574])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-a632f130-668e-4c16-928e-43724772ed9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a632f130-668e-4c16-928e-43724772ed9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d89f5e6f-5aae-4248-a8a0-98f47f6b6398' class='xr-var-data-in' type='checkbox'><label for='data-d89f5e6f-5aae-4248-a8a0-98f47f6b6398' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of POSITION_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.4 2.4 3.5 ... 1.925e+03 1.97e+03</div><input id='attrs-9a12c492-bd00-43d3-a842-6314037e3bbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9a12c492-bd00-43d3-a842-6314037e3bbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5da07b48-6051-463c-906e-3947f96f50d5' class='xr-var-data-in' type='checkbox'><label for='data-5da07b48-6051-463c-906e-3947f96f50d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>decibar</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>resolution :</span></dt><dd>0.1</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1.4000e+00, 2.4000e+00, 3.5000e+00, ..., 1.8756e+03, 1.9247e+03,\n",
       "       1.9698e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-1fe85dd2-2495-431b-987c-9a76534184c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1fe85dd2-2495-431b-987c-9a76534184c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d7506d4-0570-43fc-aa23-859d0727b03f' class='xr-var-data-in' type='checkbox'><label for='data-3d7506d4-0570-43fc-aa23-859d0727b03f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PRES_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.97 34.98 34.98 ... 34.91 34.91</div><input id='attrs-3e34f898-9bb9-4aa2-8d17-51c68fa74bfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e34f898-9bb9-4aa2-8d17-51c68fa74bfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e06b2bca-9b10-43e6-ab45-2611d7e18cc4' class='xr-var-data-in' type='checkbox'><label for='data-e06b2bca-9b10-43e6-ab45-2611d7e18cc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>PRACTICAL SALINITY</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>units :</span></dt><dd>psu</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>43.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([34.971 , 34.976 , 34.982 , ..., 34.9144, 34.9144, 34.9144],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-7a81f9f3-78d6-4c16-a293-1aceb96d8ec4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a81f9f3-78d6-4c16-a293-1aceb96d8ec4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6104f31f-160d-4f31-8451-203996ee0f96' class='xr-var-data-in' type='checkbox'><label for='data-6104f31f-160d-4f31-8451-203996ee0f96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PSAL_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.03 11.03 11.03 ... -0.723 -0.729</div><input id='attrs-9fbadb78-fee5-4778-9df9-1b0d7187e1a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fbadb78-fee5-4778-9df9-1b0d7187e1a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9971000-926d-4d6e-aa0e-f9e2d645c9a7' class='xr-var-data-in' type='checkbox'><label for='data-e9971000-926d-4d6e-aa0e-f9e2d645c9a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>SEA TEMPERATURE IN SITU ITS-90 SCALE</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd><dt><span>valid_min :</span></dt><dd>-2.0</dd><dt><span>valid_max :</span></dt><dd>40.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([11.034, 11.034, 11.034, ..., -0.717, -0.723, -0.729], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-082262e8-9eed-4ae3-8925-540b53629a25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-082262e8-9eed-4ae3-8925-540b53629a25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d52f7f7-3432-4ca1-a894-b31e5148ee80' class='xr-var-data-in' type='checkbox'><label for='data-6d52f7f7-3432-4ca1-a894-b31e5148ee80' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TEMP_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-251b444d-e598-46d6-8260-7bd4579460fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-251b444d-e598-46d6-8260-7bd4579460fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc4945d9-e93d-4852-be05-5a0ba2730b15' class='xr-var-data-in' type='checkbox'><label for='data-fc4945d9-e93d-4852-be05-5a0ba2730b15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TIME_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SA</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.14 35.14 35.15 ... 35.08 35.08</div><input id='attrs-f9a0a644-66f9-4321-96a7-2db338cfaadb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9a0a644-66f9-4321-96a7-2db338cfaadb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79478df0-d886-4409-8842-498981905850' class='xr-var-data-in' type='checkbox'><label for='data-79478df0-d886-4409-8842-498981905850' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Absolute Salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_absolute_salinity</dd><dt><span>unit :</span></dt><dd>g/kg</dd></dl></div><div class='xr-var-data'><pre>array([35.13700858, 35.14203695, 35.14806604, ..., 35.08279916,\n",
       "       35.0828279 , 35.0828543 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CT</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.02 11.02 ... -0.8111 -0.8198</div><input id='attrs-8cf4cbd5-7c78-4a0e-a6dc-ce73575bdc37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cf4cbd5-7c78-4a0e-a6dc-ce73575bdc37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cc65949-1e1d-4df3-b9ff-08c84d7d3b1b' class='xr-var-data-in' type='checkbox'><label for='data-4cc65949-1e1d-4df3-b9ff-08c84d7d3b1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Conservative Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_conservative_temperature</dd><dt><span>unit :</span></dt><dd>degC</dd></dl></div><div class='xr-var-data'><pre>array([11.02380479, 11.02358264, 11.02332838, ..., -0.80206644,\n",
       "       -0.81105845, -0.81983018])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SIG0</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>26.75 26.75 26.76 ... 28.08 28.08</div><input id='attrs-fa7b7034-fb7f-4fc4-8be5-ca2d9743d40a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa7b7034-fb7f-4fc4-8be5-ca2d9743d40a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8383a851-c9e1-4e5a-95d0-18a4646d6580' class='xr-var-data-in' type='checkbox'><label for='data-8383a851-c9e1-4e5a-95d0-18a4646d6580' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Potential density anomaly with reference pressure of 0 dbar</dd><dt><span>standard_name :</span></dt><dd>sea_water_sigma_theta</dd><dt><span>unit :</span></dt><dd>kg/m^3</dd></dl></div><div class='xr-var-data'><pre>array([26.75020987, 26.75412841, 26.75882462, ..., 28.08014622,\n",
       "       28.0805583 , 28.0809579 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CNDC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>39.04 39.05 39.06 ... 29.19 29.21</div><input id='attrs-7c64e483-8ca7-4cde-91b0-d51d62c12baa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c64e483-8ca7-4cde-91b0-d51d62c12baa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebca9835-f3a2-4ac2-9209-762fc37aacea' class='xr-var-data-in' type='checkbox'><label for='data-ebca9835-f3a2-4ac2-9209-762fc37aacea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Electrical Conductivity</dd><dt><span>standard_name :</span></dt><dd>sea_water_electrical_conductivity</dd><dt><span>unit :</span></dt><dd>mS/cm</dd></dl></div><div class='xr-var-data'><pre>array([39.0445458 , 39.05000307, 39.05650187, ..., 29.17971086,\n",
       "       29.19466046, 29.20791327])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>N2</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 3.951e-05 ... 1.898e-07 nan</div><input id='attrs-5a8209ff-5423-437b-93d5-4d4d1348bb8d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a8209ff-5423-437b-93d5-4d4d1348bb8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e59e28bc-d3a3-41ea-be3f-24d4ceebb0e3' class='xr-var-data-in' type='checkbox'><label for='data-e59e28bc-d3a3-41ea-be3f-24d4ceebb0e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Squared buoyancy frequency</dd><dt><span>unit :</span></dt><dd>1/s^2</dd></dl></div><div class='xr-var-data'><pre>array([           nan, 3.95144759e-05, 3.95143052e-05, ...,\n",
       "       2.73043926e-07, 1.89848310e-07,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 5.419e-10 ... 2.606e-12 nan</div><input id='attrs-29da03ca-3ca7-4102-b63b-8ce95ac789f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29da03ca-3ca7-4102-b63b-8ce95ac789f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5a72f63-3c5b-472e-b6ba-7ef797631141' class='xr-var-data-in' type='checkbox'><label for='data-d5a72f63-3c5b-472e-b6ba-7ef797631141' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Planetary Potential Vorticity</dd><dt><span>unit :</span></dt><dd>1/m/s</dd></dl></div><div class='xr-var-data'><pre>array([           nan, 5.41936361e-10, 5.41933886e-10, ...,\n",
       "       3.74875566e-12, 2.60649337e-12,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PTEMP</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.03 11.03 ... -0.8124 -0.8212</div><input id='attrs-5ea6d1c9-56b4-468d-81f4-a116ed603885' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ea6d1c9-56b4-468d-81f4-a116ed603885' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bda93b73-6ab2-4246-afe3-673492083659' class='xr-var-data-in' type='checkbox'><label for='data-bda93b73-6ab2-4246-afe3-673492083659' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Potential Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>unit :</span></dt><dd>degC</dd></dl></div><div class='xr-var-data'><pre>array([11.03382893, 11.03370643, 11.03357165, ..., -0.80341614,\n",
       "       -0.81241912, -0.82120155])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SOUND_SPEED</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.493e+03 1.493e+03 ... 1.478e+03</div><input id='attrs-d1cbd92d-7221-4d9c-a6b7-6f0f9e9938c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1cbd92d-7221-4d9c-a6b7-6f0f9e9938c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e94116f-32e3-4b48-8b2c-a0e9bb315d92' class='xr-var-data-in' type='checkbox'><label for='data-9e94116f-32e3-4b48-8b2c-a0e9bb315d92' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Speed of sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>unit :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([1493.47118943, 1493.49348944, 1493.51861768, ..., 1476.29726702,\n",
       "       1477.09011   , 1477.81679619])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4df8a798-38d1-4041-9a01-1420cdeea8da' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4df8a798-38d1-4041-9a01-1420cdeea8da' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>DATA_ID :</span></dt><dd>ARGO</dd><dt><span>DOI :</span></dt><dd>http://doi.org/10.17882/42182</dd><dt><span>Fetched_from :</span></dt><dd>https://www.ifremer.fr/erddap</dd><dt><span>Fetched_by :</span></dt><dd>jovyan</dd><dt><span>Fetched_date :</span></dt><dd>2022/03/13</dd><dt><span>Fetched_constraints :</span></dt><dd>phy;WMO6903574</dd><dt><span>Fetched_uri :</span></dt><dd>[&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats.nc?data_mode,latitude,longitude,position_qc,time,time_qc,direction,platform_number,cycle_number,config_mission_number,vertical_sampling_scheme,pres,temp,psal,pres_qc,temp_qc,psal_qc,pres_adjusted,temp_adjusted,psal_adjusted,pres_adjusted_qc,temp_adjusted_qc,psal_adjusted_qc,pres_adjusted_error,temp_adjusted_error,psal_adjusted_error&amp;platform_number=~&quot;6903574&quot;&amp;distinct()&amp;orderBy(&quot;time,pres&quot;)&#x27;]</dd><dt><span>history :</span></dt><dd>Variables filtered according to DATA_MODE; Variables selected according to QC</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/21)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'A' 'A' 'A' 'A'\n",
       "    DIRECTION              (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    SIG0                   (N_POINTS) float64 26.75 26.75 26.76 ... 28.08 28.08\n",
       "    CNDC                   (N_POINTS) float64 39.04 39.05 39.06 ... 29.19 29.21\n",
       "    N2                     (N_POINTS) float64 nan 3.951e-05 ... 1.898e-07 nan\n",
       "    PV                     (N_POINTS) float64 nan 5.419e-10 ... 2.606e-12 nan\n",
       "    PTEMP                  (N_POINTS) float64 11.03 11.03 ... -0.8124 -0.8212\n",
       "    SOUND_SPEED            (N_POINTS) float64 1.493e+03 1.493e+03 ... 1.478e+03\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable..."
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = ArgoDataFetcher().float(6903574).to_xarray()\n",
    "# none of the following variables give nitrate\n",
    "#ds.argo.teos10(['SA', 'CT', 'PV', 'N2'])\n",
    "ds.argo.teos10([\"SA\", \"CT\", \"SIG0\", \"N2\", \"PV\", \"PTEMP\", \"SOUND_SPEED\", \"CNDC\"])"
   ]
  },
  {
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   "execution_count": 60,
   "id": "b2447f89-c160-4c50-9c5f-ea825f8b629e",
   "metadata": {},
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       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/16)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) &lt;U1 &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    DIRECTION              (N_POINTS) &lt;U1 &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    TEMP                   (N_POINTS) float32 11.03 11.03 ... -0.723 -0.729\n",
       "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    SA                     (N_POINTS) float64 35.14 35.14 35.15 ... 35.08 35.08\n",
       "    CT                     (N_POINTS) float64 11.02 11.02 ... -0.8111 -0.8198\n",
       "    PV                     (N_POINTS) float64 nan 5.419e-10 ... 2.606e-12 nan\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          [&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c4483783-0f4d-4f11-92e6-953e0aba0fd4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c4483783-0f4d-4f11-92e6-953e0aba0fd4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>N_POINTS</span>: 29267</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ee092492-9f07-44dc-a2e1-f084b8f6e4d0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ee092492-9f07-44dc-a2e1-f084b8f6e4d0' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>N_POINTS</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 29263 29264 29265 29266</div><input id='attrs-e6478720-e3ef-456a-b5e8-1acd9d5a70e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e6478720-e3ef-456a-b5e8-1acd9d5a70e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-750a747f-53fb-4a42-83a8-0a0f5543c8d6' class='xr-var-data-in' type='checkbox'><label for='data-750a747f-53fb-4a42-83a8-0a0f5543c8d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 29264, 29265, 29266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LATITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>67.5 67.5 67.5 ... 67.71 67.71</div><input id='attrs-3a5e7c30-bdb3-41cc-8a7f-bd295117648f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a5e7c30-bdb3-41cc-8a7f-bd295117648f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e42dc98-6a66-419e-bdc5-6a1edbe7819e' class='xr-var-data-in' type='checkbox'><label for='data-5e42dc98-6a66-419e-bdc5-6a1edbe7819e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>actual_range :</span></dt><dd>[65.15173167 67.73593   ]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Latitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([67.50215333, 67.50215333, 67.50215333, ..., 67.71014167,\n",
       "       67.71014167, 67.71014167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LONGITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.531 -0.531 ... -2.693 -2.693</div><input id='attrs-3ffa510d-b2ba-43b6-9c97-f1c2b341f6d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ffa510d-b2ba-43b6-9c97-f1c2b341f6d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41367a0a-6b6d-4d5e-8600-fd1ec4921a18' class='xr-var-data-in' type='checkbox'><label for='data-41367a0a-6b6d-4d5e-8600-fd1ec4921a18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>actual_range :</span></dt><dd>[-5.31154333 -0.50186833]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Longitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([-0.53096833, -0.53096833, -0.53096833, ..., -2.69315   ,\n",
       "       -2.69315   , -2.69315   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-25T22:18:00 ... 2022-03-...</div><input id='attrs-705a3200-6e5c-4098-8b83-8ed5aa3dc62a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-705a3200-6e5c-4098-8b83-8ed5aa3dc62a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f53dc69-2b57-4853-9d6d-fbf3c467589d' class='xr-var-data-in' type='checkbox'><label for='data-0f53dc69-2b57-4853-9d6d-fbf3c467589d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Time</dd><dt><span>actual_range :</span></dt><dd>[1.59839388e+09 1.64682480e+09]</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Julian day (UTC) of the station relative to REFERENCE_DATE_TIME</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-25T22:18:00.000000000&#x27;, &#x27;2020-08-25T22:18:00.000000000&#x27;,\n",
       "       &#x27;2020-08-25T22:18:00.000000000&#x27;, ...,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;, &#x27;2022-03-09T11:20:00.000000000&#x27;,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0a2a65ad-bc01-4804-bd30-b0ba481a842f' class='xr-section-summary-in' type='checkbox'  ><label for='section-0a2a65ad-bc01-4804-bd30-b0ba481a842f' class='xr-section-summary' >Data variables: <span>(16)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CONFIG_MISSION_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3</div><input id='attrs-e94c0717-25cc-4814-b3a2-1135e28fdf55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e94c0717-25cc-4814-b3a2-1135e28fdf55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cfb1fb0-7c6c-4383-84d7-db5bf3960793' class='xr-var-data-in' type='checkbox'><label for='data-7cfb1fb0-7c6c-4383-84d7-db5bf3960793' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 3]</dd><dt><span>colorBarMaximum :</span></dt><dd>100.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>conventions :</span></dt><dd>1...N, 1 : first complete mission</dd><dt><span>ioos_category :</span></dt><dd>Statistics</dd><dt><span>long_name :</span></dt><dd>Unique number denoting the missions performed by the float</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 3, 3, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CYCLE_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 ... 113 113 113 113 113</div><input id='attrs-84661444-52ec-46da-90b7-6c58111b26a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84661444-52ec-46da-90b7-6c58111b26a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01057c5e-e025-41e9-a025-96fe26b391b6' class='xr-var-data-in' type='checkbox'><label for='data-01057c5e-e025-41e9-a025-96fe26b391b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float cycle number</dd><dt><span>convention :</span></dt><dd>0..N, 0 : launch cycle (if exists), 1 : first complete cycle</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([  1,   1,   1, ..., 113, 113, 113])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DATA_MODE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-3737e703-20df-41ff-85e8-a29d10e0fc8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3737e703-20df-41ff-85e8-a29d10e0fc8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5c908c8-1dcd-43ca-98e7-6c9352cf5873' class='xr-var-data-in' type='checkbox'><label for='data-c5c908c8-1dcd-43ca-98e7-6c9352cf5873' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delayed mode or real time data</dd><dt><span>convention :</span></dt><dd>R : real time; D : delayed mode; A : real time with adjustment</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;R&#x27;, &#x27;R&#x27;, &#x27;R&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DIRECTION</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-83219d7f-bc8b-40c9-86e1-2298ccd1bcb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83219d7f-bc8b-40c9-86e1-2298ccd1bcb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7db010e4-2fe9-4cd4-a617-a2a648d5fa38' class='xr-var-data-in' type='checkbox'><label for='data-7db010e4-2fe9-4cd4-a617-a2a648d5fa38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Direction of the station profiles</dd><dt><span>convention :</span></dt><dd>A: ascending profiles, D: descending profiles</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;D&#x27;, &#x27;D&#x27;, &#x27;D&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PLATFORM_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>6903574 6903574 ... 6903574 6903574</div><input id='attrs-375d174e-7525-4fbd-8dfe-348cf15ef556' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-375d174e-7525-4fbd-8dfe-348cf15ef556' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f80f5471-3658-41a6-97b5-aed9a84c801f' class='xr-var-data-in' type='checkbox'><label for='data-f80f5471-3658-41a6-97b5-aed9a84c801f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float unique identifier</dd><dt><span>convention :</span></dt><dd>WMO float identifier : A9IIIII</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([6903574, 6903574, 6903574, ..., 6903574, 6903574, 6903574])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-e55ed3b9-cb6d-4a1c-9a63-a20069c441bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e55ed3b9-cb6d-4a1c-9a63-a20069c441bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2c8ae97-8c15-4396-b700-2a67473f88b6' class='xr-var-data-in' type='checkbox'><label for='data-f2c8ae97-8c15-4396-b700-2a67473f88b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of POSITION_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.4 2.4 3.5 ... 1.925e+03 1.97e+03</div><input id='attrs-695e9913-3f2f-40a5-9cc7-51e25360ef60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-695e9913-3f2f-40a5-9cc7-51e25360ef60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d43fc00-50eb-44ff-aa5e-adc42de4551c' class='xr-var-data-in' type='checkbox'><label for='data-6d43fc00-50eb-44ff-aa5e-adc42de4551c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>decibar</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>resolution :</span></dt><dd>0.1</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1.4000e+00, 2.4000e+00, 3.5000e+00, ..., 1.8756e+03, 1.9247e+03,\n",
       "       1.9698e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-95e2833d-9153-4116-9ce2-23a45db42db6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95e2833d-9153-4116-9ce2-23a45db42db6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b20b9592-291e-4613-8684-959fe30e7fa7' class='xr-var-data-in' type='checkbox'><label for='data-b20b9592-291e-4613-8684-959fe30e7fa7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PRES_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.97 34.98 34.98 ... 34.91 34.91</div><input id='attrs-213abdd8-fa79-4632-949f-fa720a01ffca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-213abdd8-fa79-4632-949f-fa720a01ffca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1009d76-822e-476a-adf4-5d245a9a9c74' class='xr-var-data-in' type='checkbox'><label for='data-c1009d76-822e-476a-adf4-5d245a9a9c74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>PRACTICAL SALINITY</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>units :</span></dt><dd>psu</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>43.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([34.971 , 34.976 , 34.982 , ..., 34.9144, 34.9144, 34.9144],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-4a0c4672-daf9-460f-925f-0c1be5e311e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a0c4672-daf9-460f-925f-0c1be5e311e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17e35008-bb55-40eb-9e39-062668a4c944' class='xr-var-data-in' type='checkbox'><label for='data-17e35008-bb55-40eb-9e39-062668a4c944' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PSAL_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.03 11.03 11.03 ... -0.723 -0.729</div><input id='attrs-325caafd-debb-41b9-b5fe-a5e6a98f7e7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-325caafd-debb-41b9-b5fe-a5e6a98f7e7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1f1ceaa-461c-4588-aff9-6f0780934dc0' class='xr-var-data-in' type='checkbox'><label for='data-a1f1ceaa-461c-4588-aff9-6f0780934dc0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>SEA TEMPERATURE IN SITU ITS-90 SCALE</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd><dt><span>valid_min :</span></dt><dd>-2.0</dd><dt><span>valid_max :</span></dt><dd>40.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([11.034, 11.034, 11.034, ..., -0.717, -0.723, -0.729], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-99a43436-6ec4-45f6-812a-a2abca4ce804' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99a43436-6ec4-45f6-812a-a2abca4ce804' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f90b1f3-38cd-4d80-a847-c8384118e83e' class='xr-var-data-in' type='checkbox'><label for='data-8f90b1f3-38cd-4d80-a847-c8384118e83e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TEMP_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-41986867-1620-4caf-8394-fa6e1735d328' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41986867-1620-4caf-8394-fa6e1735d328' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-739f353e-75a2-43a7-86ae-c0ec777c0cf1' class='xr-var-data-in' type='checkbox'><label for='data-739f353e-75a2-43a7-86ae-c0ec777c0cf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TIME_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SA</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>35.14 35.14 35.15 ... 35.08 35.08</div><input id='attrs-ccbdf8a1-7eb1-431e-a5c4-c1cc3f78d6e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccbdf8a1-7eb1-431e-a5c4-c1cc3f78d6e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2439420e-c397-41a7-821c-fc371ab46a10' class='xr-var-data-in' type='checkbox'><label for='data-2439420e-c397-41a7-821c-fc371ab46a10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Absolute Salinity</dd><dt><span>standard_name :</span></dt><dd>sea_water_absolute_salinity</dd><dt><span>unit :</span></dt><dd>g/kg</dd></dl></div><div class='xr-var-data'><pre>array([35.13700858, 35.14203695, 35.14806604, ..., 35.08279916,\n",
       "       35.0828279 , 35.0828543 ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CT</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>11.02 11.02 ... -0.8111 -0.8198</div><input id='attrs-95d13378-6215-4442-a450-217500fff16e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-95d13378-6215-4442-a450-217500fff16e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e696cacd-0682-4c16-a185-559c4d2e5931' class='xr-var-data-in' type='checkbox'><label for='data-e696cacd-0682-4c16-a185-559c4d2e5931' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Conservative Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_conservative_temperature</dd><dt><span>unit :</span></dt><dd>degC</dd></dl></div><div class='xr-var-data'><pre>array([11.02380479, 11.02358264, 11.02332838, ..., -0.80206644,\n",
       "       -0.81105845, -0.81983018])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PV</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 5.419e-10 ... 2.606e-12 nan</div><input id='attrs-c29cc83d-e0bd-49ae-be7c-ca8d438f8efa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c29cc83d-e0bd-49ae-be7c-ca8d438f8efa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c804d127-99dd-4336-9519-04444f6b8e64' class='xr-var-data-in' type='checkbox'><label for='data-c804d127-99dd-4336-9519-04444f6b8e64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Planetary Potential Vorticity</dd><dt><span>unit :</span></dt><dd>1/m/s</dd></dl></div><div class='xr-var-data'><pre>array([           nan, 5.41936361e-10, 5.41933886e-10, ...,\n",
       "       3.74875566e-12, 2.60649337e-12,            nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35da485b-36f9-40d0-a564-805e9eaea33c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-35da485b-36f9-40d0-a564-805e9eaea33c' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>DATA_ID :</span></dt><dd>ARGO</dd><dt><span>DOI :</span></dt><dd>http://doi.org/10.17882/42182</dd><dt><span>Fetched_from :</span></dt><dd>https://www.ifremer.fr/erddap</dd><dt><span>Fetched_by :</span></dt><dd>jovyan</dd><dt><span>Fetched_date :</span></dt><dd>2022/03/13</dd><dt><span>Fetched_constraints :</span></dt><dd>phy;WMO6903574</dd><dt><span>Fetched_uri :</span></dt><dd>[&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats.nc?data_mode,latitude,longitude,position_qc,time,time_qc,direction,platform_number,cycle_number,config_mission_number,vertical_sampling_scheme,pres,temp,psal,pres_qc,temp_qc,psal_qc,pres_adjusted,temp_adjusted,psal_adjusted,pres_adjusted_qc,temp_adjusted_qc,psal_adjusted_qc,pres_adjusted_error,temp_adjusted_error,psal_adjusted_error&amp;platform_number=~&quot;6903574&quot;&amp;distinct()&amp;orderBy(&quot;time,pres&quot;)&#x27;]</dd><dt><span>history :</span></dt><dd>Variables filtered according to DATA_MODE; Variables selected according to QC</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/16)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'A' 'A' 'A' 'A'\n",
       "    DIRECTION              (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    TEMP                   (N_POINTS) float32 11.03 11.03 ... -0.723 -0.729\n",
       "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    SA                     (N_POINTS) float64 35.14 35.14 35.15 ... 35.08 35.08\n",
       "    CT                     (N_POINTS) float64 11.02 11.02 ... -0.8111 -0.8198\n",
       "    PV                     (N_POINTS) float64 nan 5.419e-10 ... 2.606e-12 nan\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable..."
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds1 = ArgoDataFetcher().float(6903574).to_xarray()\n",
    "# none of the ollowing variables give nitrate\n",
    "ds1.argo.teos10(['SA', 'CT', 'PV', ])\n",
    "#ds.argo.teos10([\"NO3\"])\n",
    "#nitrate might be named 'NO3-N'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "95f060d1-5f65-49fb-858e-bb1824941f85",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "9a759650-8e27-449a-98de-f07a2fe1414d",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = argo_loader.region([-75, -45, 20, 30, 0, 10, '2011-01-01', '2011-06']).to_xarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "cc237a32-158f-47a1-b90c-9fd97c63698d",
   "metadata": {},
   "outputs": [],
   "source": [
    "argo_loader = ArgoDataFetcher()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "0cccdbae-ac51-40d4-bd9a-3bfc938d35a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds2 = argo_loader.float(6903574).to_xarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "f92541c8-c0a0-437b-ad5a-fd0dbef6d444",
   "metadata": {},
   "outputs": [
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       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/13)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) &lt;U1 &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    DIRECTION              (N_POINTS) &lt;U1 &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    PRES_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    PSAL                   (N_POINTS) float32 34.97 34.98 34.98 ... 34.91 34.91\n",
       "    PSAL_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TEMP                   (N_POINTS) float32 11.03 11.03 ... -0.723 -0.729\n",
       "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          [&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-117247bf-660e-43ba-93a4-83c1b28aecbc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-117247bf-660e-43ba-93a4-83c1b28aecbc' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>N_POINTS</span>: 29267</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a24f96f9-0b3f-4786-ab64-3436af3ae33e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a24f96f9-0b3f-4786-ab64-3436af3ae33e' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>N_POINTS</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 29263 29264 29265 29266</div><input id='attrs-2a1c862f-1bc8-4102-ad21-83c211a022e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a1c862f-1bc8-4102-ad21-83c211a022e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba966995-7477-48d1-98a4-caa63ee5086e' class='xr-var-data-in' type='checkbox'><label for='data-ba966995-7477-48d1-98a4-caa63ee5086e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 29264, 29265, 29266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LATITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>67.5 67.5 67.5 ... 67.71 67.71</div><input id='attrs-bbaef697-353c-4004-8159-5e573ced17d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbaef697-353c-4004-8159-5e573ced17d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50f258b8-4d8f-42db-9ede-6b3a7cf4f16a' class='xr-var-data-in' type='checkbox'><label for='data-50f258b8-4d8f-42db-9ede-6b3a7cf4f16a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>actual_range :</span></dt><dd>[65.15173167 67.73593   ]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Latitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([67.50215333, 67.50215333, 67.50215333, ..., 67.71014167,\n",
       "       67.71014167, 67.71014167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LONGITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.531 -0.531 ... -2.693 -2.693</div><input id='attrs-2fab6f33-dfba-43f9-bc05-3a6d05bea3fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fab6f33-dfba-43f9-bc05-3a6d05bea3fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c67d8505-1c35-4386-8552-8ed4185b1e50' class='xr-var-data-in' type='checkbox'><label for='data-c67d8505-1c35-4386-8552-8ed4185b1e50' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>actual_range :</span></dt><dd>[-5.31154333 -0.50186833]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Longitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([-0.53096833, -0.53096833, -0.53096833, ..., -2.69315   ,\n",
       "       -2.69315   , -2.69315   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-25T22:18:00 ... 2022-03-...</div><input id='attrs-ddc56ecc-d9c5-4475-a8a0-f67014f3db1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddc56ecc-d9c5-4475-a8a0-f67014f3db1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d16ff617-4833-4eaf-8f48-011b0638c0cc' class='xr-var-data-in' type='checkbox'><label for='data-d16ff617-4833-4eaf-8f48-011b0638c0cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Time</dd><dt><span>actual_range :</span></dt><dd>[1.59839388e+09 1.64682480e+09]</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Julian day (UTC) of the station relative to REFERENCE_DATE_TIME</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-25T22:18:00.000000000&#x27;, &#x27;2020-08-25T22:18:00.000000000&#x27;,\n",
       "       &#x27;2020-08-25T22:18:00.000000000&#x27;, ...,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;, &#x27;2022-03-09T11:20:00.000000000&#x27;,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-13361e1b-3455-41db-a835-c888d72923f4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13361e1b-3455-41db-a835-c888d72923f4' class='xr-section-summary' >Data variables: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CONFIG_MISSION_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3</div><input id='attrs-c16df8e2-71fe-4260-8acc-68265467388c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c16df8e2-71fe-4260-8acc-68265467388c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c65da204-546a-46c1-a041-8b7bc76e0a42' class='xr-var-data-in' type='checkbox'><label for='data-c65da204-546a-46c1-a041-8b7bc76e0a42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 3]</dd><dt><span>colorBarMaximum :</span></dt><dd>100.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>conventions :</span></dt><dd>1...N, 1 : first complete mission</dd><dt><span>ioos_category :</span></dt><dd>Statistics</dd><dt><span>long_name :</span></dt><dd>Unique number denoting the missions performed by the float</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 3, 3, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CYCLE_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 ... 113 113 113 113 113</div><input id='attrs-52bdfd6f-f622-49a1-9325-b3717f7eeb52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52bdfd6f-f622-49a1-9325-b3717f7eeb52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b521f50-92f1-4e7e-8640-c9a0d41934bc' class='xr-var-data-in' type='checkbox'><label for='data-7b521f50-92f1-4e7e-8640-c9a0d41934bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float cycle number</dd><dt><span>convention :</span></dt><dd>0..N, 0 : launch cycle (if exists), 1 : first complete cycle</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([  1,   1,   1, ..., 113, 113, 113])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DATA_MODE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-687569b9-32fa-4263-aa8d-1d3a86a8216f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-687569b9-32fa-4263-aa8d-1d3a86a8216f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b1a149b-6a93-4e70-b84f-bff8b69a2336' class='xr-var-data-in' type='checkbox'><label for='data-2b1a149b-6a93-4e70-b84f-bff8b69a2336' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delayed mode or real time data</dd><dt><span>convention :</span></dt><dd>R : real time; D : delayed mode; A : real time with adjustment</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;R&#x27;, &#x27;R&#x27;, &#x27;R&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DIRECTION</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-547f94a7-d5b9-4e18-acc9-c582fb512ce2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-547f94a7-d5b9-4e18-acc9-c582fb512ce2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00459a13-f115-4dcd-b7b4-22e4a18890b0' class='xr-var-data-in' type='checkbox'><label for='data-00459a13-f115-4dcd-b7b4-22e4a18890b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Direction of the station profiles</dd><dt><span>convention :</span></dt><dd>A: ascending profiles, D: descending profiles</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;D&#x27;, &#x27;D&#x27;, &#x27;D&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PLATFORM_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>6903574 6903574 ... 6903574 6903574</div><input id='attrs-6b105a1b-9682-4de7-b43e-cd651ce6fd50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6b105a1b-9682-4de7-b43e-cd651ce6fd50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbc9ea99-4cc1-43b9-b6cb-a825be8f7570' class='xr-var-data-in' type='checkbox'><label for='data-bbc9ea99-4cc1-43b9-b6cb-a825be8f7570' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float unique identifier</dd><dt><span>convention :</span></dt><dd>WMO float identifier : A9IIIII</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([6903574, 6903574, 6903574, ..., 6903574, 6903574, 6903574])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-9ecd86e9-5b39-444b-be2a-d589bb48a0be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ecd86e9-5b39-444b-be2a-d589bb48a0be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d19a525-ccd4-4d2e-bec4-0421b59c92e9' class='xr-var-data-in' type='checkbox'><label for='data-2d19a525-ccd4-4d2e-bec4-0421b59c92e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of POSITION_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.4 2.4 3.5 ... 1.925e+03 1.97e+03</div><input id='attrs-32ecb7c0-dceb-4879-bfa0-d5537563e343' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32ecb7c0-dceb-4879-bfa0-d5537563e343' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e56830e-c629-40d8-98a9-df0221c30e79' class='xr-var-data-in' type='checkbox'><label for='data-9e56830e-c629-40d8-98a9-df0221c30e79' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>decibar</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>resolution :</span></dt><dd>0.1</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1.4000e+00, 2.4000e+00, 3.5000e+00, ..., 1.8756e+03, 1.9247e+03,\n",
       "       1.9698e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-9f6f4f0e-8df5-492e-843b-184aeb3a94e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f6f4f0e-8df5-492e-843b-184aeb3a94e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5db0f442-ca56-4375-8393-a02e10e89141' class='xr-var-data-in' type='checkbox'><label for='data-5db0f442-ca56-4375-8393-a02e10e89141' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PRES_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.97 34.98 34.98 ... 34.91 34.91</div><input id='attrs-07f1d1e6-1507-4ea7-aa08-e52b72da0098' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07f1d1e6-1507-4ea7-aa08-e52b72da0098' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1efd76a8-4013-4543-9717-574b527c5d82' class='xr-var-data-in' type='checkbox'><label for='data-1efd76a8-4013-4543-9717-574b527c5d82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>PRACTICAL SALINITY</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>units :</span></dt><dd>psu</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>43.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([34.971 , 34.976 , 34.982 , ..., 34.9144, 34.9144, 34.9144],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-5e896392-bd9b-4ad3-b484-bda85c22fff8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e896392-bd9b-4ad3-b484-bda85c22fff8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01af9360-2825-4222-af11-89768dbb9e8c' class='xr-var-data-in' type='checkbox'><label for='data-01af9360-2825-4222-af11-89768dbb9e8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PSAL_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.03 11.03 11.03 ... -0.723 -0.729</div><input id='attrs-80b0b956-6387-4152-b224-243ce9c3bdb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80b0b956-6387-4152-b224-243ce9c3bdb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e23b044a-a5e6-488d-94ca-234341ccd085' class='xr-var-data-in' type='checkbox'><label for='data-e23b044a-a5e6-488d-94ca-234341ccd085' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>SEA TEMPERATURE IN SITU ITS-90 SCALE</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd><dt><span>valid_min :</span></dt><dd>-2.0</dd><dt><span>valid_max :</span></dt><dd>40.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([11.034, 11.034, 11.034, ..., -0.717, -0.723, -0.729], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-7b8316e1-c633-4ed6-8337-e8466ad7545a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b8316e1-c633-4ed6-8337-e8466ad7545a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b00eeb5-7d43-4df9-aa48-410d0220251a' class='xr-var-data-in' type='checkbox'><label for='data-1b00eeb5-7d43-4df9-aa48-410d0220251a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TEMP_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-bd0f1e7a-ce04-42ed-9917-ac6cde5abbf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd0f1e7a-ce04-42ed-9917-ac6cde5abbf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8367fe8-e38b-4e1a-83b4-deee247221a7' class='xr-var-data-in' type='checkbox'><label for='data-b8367fe8-e38b-4e1a-83b4-deee247221a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TIME_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-006d0218-2183-4525-aa1d-c50d86dbe829' class='xr-section-summary-in' type='checkbox'  checked><label for='section-006d0218-2183-4525-aa1d-c50d86dbe829' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>DATA_ID :</span></dt><dd>ARGO</dd><dt><span>DOI :</span></dt><dd>http://doi.org/10.17882/42182</dd><dt><span>Fetched_from :</span></dt><dd>https://www.ifremer.fr/erddap</dd><dt><span>Fetched_by :</span></dt><dd>jovyan</dd><dt><span>Fetched_date :</span></dt><dd>2022/03/13</dd><dt><span>Fetched_constraints :</span></dt><dd>phy;WMO6903574</dd><dt><span>Fetched_uri :</span></dt><dd>[&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats.nc?data_mode,latitude,longitude,position_qc,time,time_qc,direction,platform_number,cycle_number,config_mission_number,vertical_sampling_scheme,pres,temp,psal,pres_qc,temp_qc,psal_qc,pres_adjusted,temp_adjusted,psal_adjusted,pres_adjusted_qc,temp_adjusted_qc,psal_adjusted_qc,pres_adjusted_error,temp_adjusted_error,psal_adjusted_error&amp;platform_number=~&quot;6903574&quot;&amp;distinct()&amp;orderBy(&quot;time,pres&quot;)&#x27;]</dd><dt><span>history :</span></dt><dd>Variables filtered according to DATA_MODE; Variables selected according to QC</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/13)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'A' 'A' 'A' 'A'\n",
       "    DIRECTION              (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    PRES_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    PSAL                   (N_POINTS) float32 34.97 34.98 34.98 ... 34.91 34.91\n",
       "    PSAL_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TEMP                   (N_POINTS) float32 11.03 11.03 ... -0.723 -0.729\n",
       "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
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       "    Fetched_uri:          ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable..."
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "5494fc20-5421-44a6-8fbc-8168d8d00c38",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install netcdf4\n",
    "import xarray\n",
    "#pip install seawater"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "5e143249-3f90-40d0-b6ab-65011bbf8b04",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/13)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) &lt;U1 &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    DIRECTION              (N_POINTS) &lt;U1 &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    PRES_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    PSAL                   (N_POINTS) float32 34.97 34.98 34.98 ... 34.91 34.91\n",
       "    PSAL_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TEMP                   (N_POINTS) float32 11.03 11.03 ... -0.723 -0.729\n",
       "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          [&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c4dac267-a769-4925-985e-6ed5a394fb6b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c4dac267-a769-4925-985e-6ed5a394fb6b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>N_POINTS</span>: 29267</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c8f29460-e081-4f80-b6b7-66fe4e94b17e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c8f29460-e081-4f80-b6b7-66fe4e94b17e' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>N_POINTS</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 ... 29263 29264 29265 29266</div><input id='attrs-09adf52a-0b48-4d16-a553-5978ac5c8aca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-09adf52a-0b48-4d16-a553-5978ac5c8aca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c511a7f-75ab-43be-b60d-36ea71147d11' class='xr-var-data-in' type='checkbox'><label for='data-8c511a7f-75ab-43be-b60d-36ea71147d11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([    0,     1,     2, ..., 29264, 29265, 29266])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LATITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>67.5 67.5 67.5 ... 67.71 67.71</div><input id='attrs-9deed602-6693-4fd5-9a07-9be779b77b39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9deed602-6693-4fd5-9a07-9be779b77b39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb611f4c-2239-4b73-be32-05996e758197' class='xr-var-data-in' type='checkbox'><label for='data-fb611f4c-2239-4b73-be32-05996e758197' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd><dt><span>actual_range :</span></dt><dd>[65.15173167 67.73593   ]</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>colorBarMaximum :</span></dt><dd>90.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-90.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Latitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_max :</span></dt><dd>90.0</dd><dt><span>valid_min :</span></dt><dd>-90.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([67.50215333, 67.50215333, 67.50215333, ..., 67.71014167,\n",
       "       67.71014167, 67.71014167])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LONGITUDE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.531 -0.531 ... -2.693 -2.693</div><input id='attrs-c8c256c2-8d00-49bc-9a49-2fc96b95c282' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c8c256c2-8d00-49bc-9a49-2fc96b95c282' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdc12241-4655-4f61-8136-8d22878e0a8d' class='xr-var-data-in' type='checkbox'><label for='data-cdc12241-4655-4f61-8136-8d22878e0a8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd><dt><span>actual_range :</span></dt><dd>[-5.31154333 -0.50186833]</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>colorBarMaximum :</span></dt><dd>180.0</dd><dt><span>colorBarMinimum :</span></dt><dd>-180.0</dd><dt><span>ioos_category :</span></dt><dd>Location</dd><dt><span>long_name :</span></dt><dd>Longitude of the station, best estimate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_max :</span></dt><dd>180.0</dd><dt><span>valid_min :</span></dt><dd>-180.0</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([-0.53096833, -0.53096833, -0.53096833, ..., -2.69315   ,\n",
       "       -2.69315   , -2.69315   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-25T22:18:00 ... 2022-03-...</div><input id='attrs-f87b6fcf-792f-44ea-acd5-f3441e8663ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f87b6fcf-792f-44ea-acd5-f3441e8663ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7497772e-2d34-4be1-899b-131fe4593bb1' class='xr-var-data-in' type='checkbox'><label for='data-7497772e-2d34-4be1-899b-131fe4593bb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>_CoordinateAxisType :</span></dt><dd>Time</dd><dt><span>actual_range :</span></dt><dd>[1.59839388e+09 1.64682480e+09]</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>ioos_category :</span></dt><dd>Time</dd><dt><span>long_name :</span></dt><dd>Julian day (UTC) of the station relative to REFERENCE_DATE_TIME</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>time_origin :</span></dt><dd>01-JAN-1970 00:00:00</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-25T22:18:00.000000000&#x27;, &#x27;2020-08-25T22:18:00.000000000&#x27;,\n",
       "       &#x27;2020-08-25T22:18:00.000000000&#x27;, ...,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;, &#x27;2022-03-09T11:20:00.000000000&#x27;,\n",
       "       &#x27;2022-03-09T11:20:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1fb8d4ce-4dbb-48ae-ac7e-1b54e0bc5bb4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1fb8d4ce-4dbb-48ae-ac7e-1b54e0bc5bb4' class='xr-section-summary' >Data variables: <span>(13)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CONFIG_MISSION_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3</div><input id='attrs-cca72f95-2a87-4bb8-909d-d2002f43318f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cca72f95-2a87-4bb8-909d-d2002f43318f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba53331a-a2be-467c-9ea5-3aa16243b067' class='xr-var-data-in' type='checkbox'><label for='data-ba53331a-a2be-467c-9ea5-3aa16243b067' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>actual_range :</span></dt><dd>[1 3]</dd><dt><span>colorBarMaximum :</span></dt><dd>100.0</dd><dt><span>colorBarMinimum :</span></dt><dd>0.0</dd><dt><span>conventions :</span></dt><dd>1...N, 1 : first complete mission</dd><dt><span>ioos_category :</span></dt><dd>Statistics</dd><dt><span>long_name :</span></dt><dd>Unique number denoting the missions performed by the float</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 3, 3, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CYCLE_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 ... 113 113 113 113 113</div><input id='attrs-c75de959-0f0a-4767-8852-42c43900cb0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c75de959-0f0a-4767-8852-42c43900cb0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-144a858c-d10e-44d1-920b-786ec120b219' class='xr-var-data-in' type='checkbox'><label for='data-144a858c-d10e-44d1-920b-786ec120b219' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float cycle number</dd><dt><span>convention :</span></dt><dd>0..N, 0 : launch cycle (if exists), 1 : first complete cycle</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([  1,   1,   1, ..., 113, 113, 113])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DATA_MODE</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; &#x27;R&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-5ce520df-3a5a-4503-a7b2-f6161bdd42e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ce520df-3a5a-4503-a7b2-f6161bdd42e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-567d5ba7-782a-4d8a-a4ae-a469c5c1997d' class='xr-var-data-in' type='checkbox'><label for='data-567d5ba7-782a-4d8a-a4ae-a469c5c1997d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Delayed mode or real time data</dd><dt><span>convention :</span></dt><dd>R : real time; D : delayed mode; A : real time with adjustment</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;R&#x27;, &#x27;R&#x27;, &#x27;R&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>DIRECTION</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; &#x27;D&#x27; ... &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27; &#x27;A&#x27;</div><input id='attrs-3c126b12-455c-4600-8c6e-e8378a83eb38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c126b12-455c-4600-8c6e-e8378a83eb38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23c85460-f5b2-485f-a8c4-1f668d87cb1e' class='xr-var-data-in' type='checkbox'><label for='data-23c85460-f5b2-485f-a8c4-1f668d87cb1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Direction of the station profiles</dd><dt><span>convention :</span></dt><dd>A: ascending profiles, D: descending profiles</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;D&#x27;, &#x27;D&#x27;, &#x27;D&#x27;, ..., &#x27;A&#x27;, &#x27;A&#x27;, &#x27;A&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PLATFORM_NUMBER</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>6903574 6903574 ... 6903574 6903574</div><input id='attrs-8a6f11b1-efbf-440d-af61-9d5f6e2582f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a6f11b1-efbf-440d-af61-9d5f6e2582f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fda6cf00-7239-4d6f-83fa-37c950e21b94' class='xr-var-data-in' type='checkbox'><label for='data-fda6cf00-7239-4d6f-83fa-37c950e21b94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Float unique identifier</dd><dt><span>convention :</span></dt><dd>WMO float identifier : A9IIIII</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([6903574, 6903574, 6903574, ..., 6903574, 6903574, 6903574])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>POSITION_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-4863bb52-5824-4ca6-8b8f-821ebc17cd6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4863bb52-5824-4ca6-8b8f-821ebc17cd6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c49bef7f-197f-4f3c-aa32-7029f59ad54b' class='xr-var-data-in' type='checkbox'><label for='data-c49bef7f-197f-4f3c-aa32-7029f59ad54b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of POSITION_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.4 2.4 3.5 ... 1.925e+03 1.97e+03</div><input id='attrs-5789a8d1-4aea-4b28-8e3a-d85eccbfae5c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5789a8d1-4aea-4b28-8e3a-d85eccbfae5c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d17bfaf6-9b4b-4a08-87d1-13b71b8b7c54' class='xr-var-data-in' type='checkbox'><label for='data-d17bfaf6-9b4b-4a08-87d1-13b71b8b7c54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Sea Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd><dt><span>units :</span></dt><dd>decibar</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>12000.0</dd><dt><span>resolution :</span></dt><dd>0.1</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1.4000e+00, 2.4000e+00, 3.5000e+00, ..., 1.8756e+03, 1.9247e+03,\n",
       "       1.9698e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PRES_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-54c11578-e1f4-4655-a830-691a9b587946' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54c11578-e1f4-4655-a830-691a9b587946' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3f977f5-560c-4869-a254-5c56854ba6a0' class='xr-var-data-in' type='checkbox'><label for='data-a3f977f5-560c-4869-a254-5c56854ba6a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PRES_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>34.97 34.98 34.98 ... 34.91 34.91</div><input id='attrs-9f38e6d7-f117-4ff3-9071-877d898e2b12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f38e6d7-f117-4ff3-9071-877d898e2b12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c4cfc9d-eb73-449a-9d11-e2a1e87aeab2' class='xr-var-data-in' type='checkbox'><label for='data-7c4cfc9d-eb73-449a-9d11-e2a1e87aeab2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>PRACTICAL SALINITY</dd><dt><span>standard_name :</span></dt><dd>sea_water_salinity</dd><dt><span>units :</span></dt><dd>psu</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>43.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([34.971 , 34.976 , 34.982 , ..., 34.9144, 34.9144, 34.9144],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PSAL_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-3ba66e85-eb84-4c7a-aae8-f3f52beb0ca6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ba66e85-eb84-4c7a-aae8-f3f52beb0ca6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60889948-525d-4676-bf75-4cf6e14fa652' class='xr-var-data-in' type='checkbox'><label for='data-60889948-525d-4676-bf75-4cf6e14fa652' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of PSAL_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>11.03 11.03 11.03 ... -0.723 -0.729</div><input id='attrs-240000fe-9497-4066-a7ab-f71816f15662' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-240000fe-9497-4066-a7ab-f71816f15662' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c7c170f-2e25-48cb-9411-5150d8360350' class='xr-var-data-in' type='checkbox'><label for='data-3c7c170f-2e25-48cb-9411-5150d8360350' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>SEA TEMPERATURE IN SITU ITS-90 SCALE</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd><dt><span>units :</span></dt><dd>degree_Celsius</dd><dt><span>valid_min :</span></dt><dd>-2.0</dd><dt><span>valid_max :</span></dt><dd>40.0</dd><dt><span>resolution :</span></dt><dd>0.001</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([11.034, 11.034, 11.034, ..., -0.717, -0.723, -0.729], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TEMP_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-47f26af5-0a99-4440-8e4a-1fa9c7df2ce0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47f26af5-0a99-4440-8e4a-1fa9c7df2ce0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ceaeba83-4a81-48ec-bf2c-e1bf9980415c' class='xr-var-data-in' type='checkbox'><label for='data-ceaeba83-4a81-48ec-bf2c-e1bf9980415c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TEMP_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TIME_QC</span></div><div class='xr-var-dims'>(N_POINTS)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-c10a21a2-f159-4b03-b6eb-8dd1e61a7e73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c10a21a2-f159-4b03-b6eb-8dd1e61a7e73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-22358024-426d-4353-8fe8-5a37506c6b11' class='xr-var-data-in' type='checkbox'><label for='data-22358024-426d-4353-8fe8-5a37506c6b11' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Global quality flag of TIME_QC profile</dd><dt><span>convention :</span></dt><dd>Argo reference table 2a</dd><dt><span>casted :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, ..., 1, 1, 1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5db757c7-ec9d-4208-9022-9ce7b8985f8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5db757c7-ec9d-4208-9022-9ce7b8985f8f' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>DATA_ID :</span></dt><dd>ARGO</dd><dt><span>DOI :</span></dt><dd>http://doi.org/10.17882/42182</dd><dt><span>Fetched_from :</span></dt><dd>https://www.ifremer.fr/erddap</dd><dt><span>Fetched_by :</span></dt><dd>jovyan</dd><dt><span>Fetched_date :</span></dt><dd>2022/03/13</dd><dt><span>Fetched_constraints :</span></dt><dd>phy;WMO6903574</dd><dt><span>Fetched_uri :</span></dt><dd>[&#x27;https://www.ifremer.fr/erddap/tabledap/ArgoFloats.nc?data_mode,latitude,longitude,position_qc,time,time_qc,direction,platform_number,cycle_number,config_mission_number,vertical_sampling_scheme,pres,temp,psal,pres_qc,temp_qc,psal_qc,pres_adjusted,temp_adjusted,psal_adjusted,pres_adjusted_qc,temp_adjusted_qc,psal_adjusted_qc,pres_adjusted_error,temp_adjusted_error,psal_adjusted_error&amp;platform_number=~&quot;6903574&quot;&amp;distinct()&amp;orderBy(&quot;time,pres&quot;)&#x27;]</dd><dt><span>history :</span></dt><dd>Variables filtered according to DATA_MODE; Variables selected according to QC</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                (N_POINTS: 29267)\n",
       "Coordinates:\n",
       "  * N_POINTS               (N_POINTS) int64 0 1 2 3 ... 29263 29264 29265 29266\n",
       "    LATITUDE               (N_POINTS) float64 67.5 67.5 67.5 ... 67.71 67.71\n",
       "    LONGITUDE              (N_POINTS) float64 -0.531 -0.531 ... -2.693 -2.693\n",
       "    TIME                   (N_POINTS) datetime64[ns] 2020-08-25T22:18:00 ... ...\n",
       "Data variables: (12/13)\n",
       "    CONFIG_MISSION_NUMBER  (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3\n",
       "    CYCLE_NUMBER           (N_POINTS) int64 1 1 1 1 1 1 ... 113 113 113 113 113\n",
       "    DATA_MODE              (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'A' 'A' 'A' 'A'\n",
       "    DIRECTION              (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'\n",
       "    PLATFORM_NUMBER        (N_POINTS) int64 6903574 6903574 ... 6903574 6903574\n",
       "    POSITION_QC            (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    ...                     ...\n",
       "    PRES_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    PSAL                   (N_POINTS) float32 34.97 34.98 34.98 ... 34.91 34.91\n",
       "    PSAL_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TEMP                   (N_POINTS) float32 11.03 11.03 ... -0.723 -0.729\n",
       "    TEMP_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "    TIME_QC                (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1\n",
       "Attributes:\n",
       "    DATA_ID:              ARGO\n",
       "    DOI:                  http://doi.org/10.17882/42182\n",
       "    Fetched_from:         https://www.ifremer.fr/erddap\n",
       "    Fetched_by:           jovyan\n",
       "    Fetched_date:         2022/03/13\n",
       "    Fetched_constraints:  phy;WMO6903574\n",
       "    Fetched_uri:          ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...\n",
       "    history:              Variables filtered according to DATA_MODE; Variable..."
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a4422bb-dd3b-4cec-bfb5-304cad8d71bb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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