01_search_and_filter.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8f163187-8fa3-4ff4-be57-6d54031ee38b",
   "metadata": {},
   "source": [
    "# Finding datasets of interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e5427e14-40cc-4921-9464-b6f71c707ad1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from erddapy import ERDDAP\n",
    "from tqdm.notebook import tqdm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5aba354e-40bb-4ca3-871f-c7c2778fb316",
   "metadata": {},
   "source": [
    "We can use ERDDAP's built in search function to find datasets that match a keyword\n",
    "\n",
    "### Find drifter datasets from OSMC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bbb0e3f2-779b-46b5-8b33-a765f349ad45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset ID</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>drifter_hourly_qc</td>\n",
       "      <td>Global Drifter Program - 1 Hour Interpolated Q...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>drifter_6hour_qc</td>\n",
       "      <td>Global Drifter Program - 6 Hour Interpolated Q...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Dataset ID                                              Title\n",
       "0  drifter_hourly_qc  Global Drifter Program - 1 Hour Interpolated Q...\n",
       "1   drifter_6hour_qc  Global Drifter Program - 6 Hour Interpolated Q..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e = ERDDAP(\n",
    "    server=\"https://osmc.noaa.gov/erddap\",\n",
    "    protocol=\"tabledap\"\n",
    ")\n",
    "url = e.get_search_url(search_for=\"drifter\", response=\"csv\")\n",
    "\n",
    "df = pd.read_csv(url)\n",
    "df[[\"Dataset ID\", \"Title\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87d8d592-599a-42a8-be0e-b25f59ab634f",
   "metadata": {},
   "source": [
    "### Find ADCP data on the IOOS sensors ERDDAP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6d29b898-d67b-4e7a-9d3b-afaaa02f8427",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset ID</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>noaa_nos_co_ops_t01010</td>\n",
       "      <td>Sunshine Skyway Bridge ADCP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ism-caricoos-pr1_doppler_5e96_75</td>\n",
       "      <td>CARICOOS PR1 (Ponce, PR) Buoy: ADCP Currents data</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ism-caricoos-pr2_doppler_34d7_c6</td>\n",
       "      <td>CARICOOS PR2 (San Juan, PR) Buoy: ADCP Current...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ism-caricoos-pr3_doppler_b3ca_6d</td>\n",
       "      <td>CARICOOS PR3 (Vieques, PR) Buoy: ADCP Currents...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ism-caricoos-vi1_doppler_200f_7a</td>\n",
       "      <td>CARICOOS VI1 (St. John, USVI) Buoy: ADCP Curre...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>mooring-ob27m-onslow-bay-nc</td>\n",
       "      <td>Mooring OB27M, Onslow Bay, NC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ce_312_20160122t2140_delayed</td>\n",
       "      <td>IOOS Glider - ce_312-20160122T2140-delayed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ce_383_20170131t1942_delayed</td>\n",
       "      <td>IOOS Glider - ce_383-20170131T1942-delayed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ism-secoora-edu_usf_marine_comps</td>\n",
       "      <td>Big Carlos Pass Shorebased Tower (NDBC: BGCF1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>edu_usf_marine_comps_1407d550</td>\n",
       "      <td>Big Carlos Pass Shorebased Tower (NDBC: BGCF1)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ru36_20220413t2107</td>\n",
       "      <td>IOOS Glider - ru36-20220413T2107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>glos_236_20130807t1502_delayed</td>\n",
       "      <td>IOOS Glider - glos_236-20130807T1502-delayed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ru29_20200908t1623</td>\n",
       "      <td>IOOS Glider - ru29-20200908T1623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>maracoos_02_20210716t1814</td>\n",
       "      <td>IOOS Glider - maracoos_02-20210716T1814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ru29_20210630t1343</td>\n",
       "      <td>IOOS Glider - ru29-20210630T1343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>ru33_20201014t1746</td>\n",
       "      <td>IOOS Glider - ru33-20201014T1746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ru33_20201203t1521</td>\n",
       "      <td>IOOS Glider - ru33-20201203T1521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>maracoos_02_20210503t1937</td>\n",
       "      <td>IOOS Glider - maracoos_02-20210503T1937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>maracoos_02_20210820t1546</td>\n",
       "      <td>IOOS Glider - maracoos_02-20210820T1546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>maracoos_02_20211020t1322</td>\n",
       "      <td>IOOS Glider - maracoos_02-20211020T1322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ru29_20210908t1943</td>\n",
       "      <td>IOOS Glider - ru29-20210908T1943</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Dataset ID  \\\n",
       "0             noaa_nos_co_ops_t01010   \n",
       "1   ism-caricoos-pr1_doppler_5e96_75   \n",
       "2   ism-caricoos-pr2_doppler_34d7_c6   \n",
       "3   ism-caricoos-pr3_doppler_b3ca_6d   \n",
       "4   ism-caricoos-vi1_doppler_200f_7a   \n",
       "5        mooring-ob27m-onslow-bay-nc   \n",
       "6       ce_312_20160122t2140_delayed   \n",
       "7       ce_383_20170131t1942_delayed   \n",
       "8   ism-secoora-edu_usf_marine_comps   \n",
       "9      edu_usf_marine_comps_1407d550   \n",
       "10                ru36_20220413t2107   \n",
       "11    glos_236_20130807t1502_delayed   \n",
       "12                ru29_20200908t1623   \n",
       "13         maracoos_02_20210716t1814   \n",
       "14                ru29_20210630t1343   \n",
       "15                ru33_20201014t1746   \n",
       "16                ru33_20201203t1521   \n",
       "17         maracoos_02_20210503t1937   \n",
       "18         maracoos_02_20210820t1546   \n",
       "19         maracoos_02_20211020t1322   \n",
       "20                ru29_20210908t1943   \n",
       "\n",
       "                                                Title  \n",
       "0                         Sunshine Skyway Bridge ADCP  \n",
       "1   CARICOOS PR1 (Ponce, PR) Buoy: ADCP Currents data  \n",
       "2   CARICOOS PR2 (San Juan, PR) Buoy: ADCP Current...  \n",
       "3   CARICOOS PR3 (Vieques, PR) Buoy: ADCP Currents...  \n",
       "4   CARICOOS VI1 (St. John, USVI) Buoy: ADCP Curre...  \n",
       "5                       Mooring OB27M, Onslow Bay, NC  \n",
       "6          IOOS Glider - ce_312-20160122T2140-delayed  \n",
       "7          IOOS Glider - ce_383-20170131T1942-delayed  \n",
       "8      Big Carlos Pass Shorebased Tower (NDBC: BGCF1)  \n",
       "9      Big Carlos Pass Shorebased Tower (NDBC: BGCF1)  \n",
       "10                   IOOS Glider - ru36-20220413T2107  \n",
       "11       IOOS Glider - glos_236-20130807T1502-delayed  \n",
       "12                   IOOS Glider - ru29-20200908T1623  \n",
       "13            IOOS Glider - maracoos_02-20210716T1814  \n",
       "14                   IOOS Glider - ru29-20210630T1343  \n",
       "15                   IOOS Glider - ru33-20201014T1746  \n",
       "16                   IOOS Glider - ru33-20201203T1521  \n",
       "17            IOOS Glider - maracoos_02-20210503T1937  \n",
       "18            IOOS Glider - maracoos_02-20210820T1546  \n",
       "19            IOOS Glider - maracoos_02-20211020T1322  \n",
       "20                   IOOS Glider - ru29-20210908T1943  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e = ERDDAP(\n",
    "    server=\"https://erddap.sensors.ioos.us/erddap\",\n",
    "    protocol=\"tabledap\"\n",
    ")\n",
    "url = e.get_search_url(search_for=\"adcp\", response=\"csv\")\n",
    "\n",
    "df = pd.read_csv(url)\n",
    "df[[\"Dataset ID\", \"Title\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41cd76ce-99f0-40d4-bf98-65f59b3876ca",
   "metadata": {},
   "source": [
    "### Find argo floats with chlorophyll and CDOM data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0bfe2a54-82c2-41f4-857f-c84102243005",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataset ID</th>\n",
       "      <th>Title</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ArgoFloats-synthetic-BGC</td>\n",
       "      <td>Argo float synthetic vertical profiles : BGC data</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OceanGlidersGDACTrajectories</td>\n",
       "      <td>OceanGliders GDAC trajectories</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Dataset ID  \\\n",
       "0      ArgoFloats-synthetic-BGC   \n",
       "1  OceanGlidersGDACTrajectories   \n",
       "\n",
       "                                               Title  \n",
       "0  Argo float synthetic vertical profiles : BGC data  \n",
       "1                     OceanGliders GDAC trajectories  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e = ERDDAP(\n",
    "    server=\"https://erddap.ifremer.fr/erddap\",\n",
    ")\n",
    "url = e.get_search_url(search_for=\"chlorophyll CDOM\", response=\"csv\")\n",
    "\n",
    "df = pd.read_csv(url)\n",
    "df[[\"Dataset ID\", \"Title\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef83ff86-43fe-4273-acc5-6deeeea5345c",
   "metadata": {},
   "source": [
    "### Search with allDatasets\n",
    "\n",
    "For a more sophisticated search, we can use the `allDatasets` dataset from ERDDAP to examine the primary metadata of all datasets. \n",
    "\n",
    "### Get metadata for IOOS glider datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c7ff9bd0-06a2-48ca-8fae-4a57e06e1826",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1682 datasets\n"
     ]
    }
   ],
   "source": [
    "e = ERDDAP(\n",
    "    server=\"https://gliders.ioos.us/erddap\",\n",
    "    protocol=\"tabledap\",\n",
    ")\n",
    "\n",
    "# Fetch dataset list\n",
    "e.dataset_id = \"allDatasets\"\n",
    "df_datasets = e.to_pandas()\n",
    "\n",
    "# drop the allDatasets row and make the datasetID the index for easier reading\n",
    "df_datasets.set_index(\"datasetID\", inplace=True)\n",
    "df_datasets.drop(\"allDatasets\", inplace=True)\n",
    "df_datasets[\"minTime\"] = pd.to_datetime(df_datasets['minTime (UTC)'].str[:-1])\n",
    "df_datasets[\"maxTime\"] = pd.to_datetime(df_datasets['maxTime (UTC)'].str[:-1])\n",
    "\n",
    "# Keep a susbset of useful columns\n",
    "df_datasets = df_datasets[[\n",
    " 'institution',\n",
    " 'minLongitude (degrees_east)',\n",
    " 'maxLongitude (degrees_east)',\n",
    " 'minLatitude (degrees_north)',\n",
    " 'maxLatitude (degrees_north)',\n",
    " 'minAltitude (m)',\n",
    " 'maxAltitude (m)',\n",
    " 'minTime',\n",
    " 'maxTime',\n",
    "]]\n",
    "\n",
    "print(f\"Found {len(df_datasets)} datasets\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "916cd2b1-11f7-4736-bbe5-2090708c0896",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>institution</th>\n",
       "      <th>minLongitude (degrees_east)</th>\n",
       "      <th>maxLongitude (degrees_east)</th>\n",
       "      <th>minLatitude (degrees_north)</th>\n",
       "      <th>maxLatitude (degrees_north)</th>\n",
       "      <th>minAltitude (m)</th>\n",
       "      <th>maxAltitude (m)</th>\n",
       "      <th>minTime</th>\n",
       "      <th>maxTime</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasetID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>amelia-20180501T0000</th>\n",
       "      <td>Virginia Institute of Marine Science - William...</td>\n",
       "      <td>-75.079579</td>\n",
       "      <td>-74.445788</td>\n",
       "      <td>37.404436</td>\n",
       "      <td>37.539598</td>\n",
       "      <td>-1.040000e+00</td>\n",
       "      <td>-351.1800</td>\n",
       "      <td>2018-05-01 14:58:48</td>\n",
       "      <td>2018-05-14 12:29:12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amelia-20200825T1929</th>\n",
       "      <td>Virginia Institute of Marine Science - William...</td>\n",
       "      <td>-75.360315</td>\n",
       "      <td>-74.443807</td>\n",
       "      <td>36.334915</td>\n",
       "      <td>37.353705</td>\n",
       "      <td>2.511368e-02</td>\n",
       "      <td>-323.9919</td>\n",
       "      <td>2020-08-25 19:59:18</td>\n",
       "      <td>2020-09-25 14:32:48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amelia-20201015T1436</th>\n",
       "      <td>Virginia Institute of Marine Science - William...</td>\n",
       "      <td>-74.947858</td>\n",
       "      <td>-74.405013</td>\n",
       "      <td>37.042386</td>\n",
       "      <td>37.662572</td>\n",
       "      <td>-2.014898e-02</td>\n",
       "      <td>-344.7628</td>\n",
       "      <td>2020-10-15 14:44:15</td>\n",
       "      <td>2020-10-22 06:36:43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amlr01-20181216T0641-delayed</th>\n",
       "      <td>NOAA SWFSC Antarctic Ecosystem Research Division</td>\n",
       "      <td>-61.756371</td>\n",
       "      <td>-56.996472</td>\n",
       "      <td>-63.465319</td>\n",
       "      <td>-62.203002</td>\n",
       "      <td>-1.315100e-14</td>\n",
       "      <td>-1003.8600</td>\n",
       "      <td>2018-12-16 16:05:20</td>\n",
       "      <td>2019-03-08 09:37:33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>amlr01-20191206T0452-delayed</th>\n",
       "      <td>NOAA SWFSC Antarctic Ecosystem Research Division</td>\n",
       "      <td>-61.667188</td>\n",
       "      <td>-57.433161</td>\n",
       "      <td>-63.555934</td>\n",
       "      <td>-62.186826</td>\n",
       "      <td>-3.265242e-15</td>\n",
       "      <td>-962.1450</td>\n",
       "      <td>2019-12-06 14:45:17</td>\n",
       "      <td>2020-03-12 14:37:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UW646-20210816T0000</th>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>-125.395030</td>\n",
       "      <td>-124.601065</td>\n",
       "      <td>43.850373</td>\n",
       "      <td>44.653477</td>\n",
       "      <td>4.059241e-01</td>\n",
       "      <td>-996.5469</td>\n",
       "      <td>2021-08-16 18:57:36</td>\n",
       "      <td>2021-08-24 23:59:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UW646-20211112T0000</th>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>-128.973918</td>\n",
       "      <td>-124.363708</td>\n",
       "      <td>40.820313</td>\n",
       "      <td>41.177692</td>\n",
       "      <td>5.003096e-01</td>\n",
       "      <td>-1005.2760</td>\n",
       "      <td>2021-11-12 18:53:18</td>\n",
       "      <td>2022-06-16 14:33:31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UW646-20220907T0000</th>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>-129.101990</td>\n",
       "      <td>-124.354081</td>\n",
       "      <td>40.805190</td>\n",
       "      <td>41.240848</td>\n",
       "      <td>6.568508e-01</td>\n",
       "      <td>-994.1479</td>\n",
       "      <td>2022-07-29 04:21:11</td>\n",
       "      <td>2023-01-26 13:31:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UW685-20230125T0000</th>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>-129.214460</td>\n",
       "      <td>-124.350906</td>\n",
       "      <td>40.834967</td>\n",
       "      <td>41.195338</td>\n",
       "      <td>3.087025e-01</td>\n",
       "      <td>-993.3872</td>\n",
       "      <td>2023-01-26 20:10:27</td>\n",
       "      <td>2023-08-14 18:26:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>whoi_406-20160902T1700</th>\n",
       "      <td>Woods Hole Oceanographic Institution</td>\n",
       "      <td>-71.549828</td>\n",
       "      <td>-70.675373</td>\n",
       "      <td>40.257794</td>\n",
       "      <td>41.120018</td>\n",
       "      <td>-2.490000e+00</td>\n",
       "      <td>-98.0500</td>\n",
       "      <td>2016-09-02 17:05:38</td>\n",
       "      <td>2016-09-20 13:32:33</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1682 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                    institution  \\\n",
       "datasetID                                                                         \n",
       "amelia-20180501T0000          Virginia Institute of Marine Science - William...   \n",
       "amelia-20200825T1929          Virginia Institute of Marine Science - William...   \n",
       "amelia-20201015T1436          Virginia Institute of Marine Science - William...   \n",
       "amlr01-20181216T0641-delayed   NOAA SWFSC Antarctic Ecosystem Research Division   \n",
       "amlr01-20191206T0452-delayed   NOAA SWFSC Antarctic Ecosystem Research Division   \n",
       "...                                                                         ...   \n",
       "UW646-20210816T0000                                     Oregon State University   \n",
       "UW646-20211112T0000                                     Oregon State University   \n",
       "UW646-20220907T0000                                     Oregon State University   \n",
       "UW685-20230125T0000                                     Oregon State University   \n",
       "whoi_406-20160902T1700                     Woods Hole Oceanographic Institution   \n",
       "\n",
       "                              minLongitude (degrees_east)  \\\n",
       "datasetID                                                   \n",
       "amelia-20180501T0000                           -75.079579   \n",
       "amelia-20200825T1929                           -75.360315   \n",
       "amelia-20201015T1436                           -74.947858   \n",
       "amlr01-20181216T0641-delayed                   -61.756371   \n",
       "amlr01-20191206T0452-delayed                   -61.667188   \n",
       "...                                                   ...   \n",
       "UW646-20210816T0000                           -125.395030   \n",
       "UW646-20211112T0000                           -128.973918   \n",
       "UW646-20220907T0000                           -129.101990   \n",
       "UW685-20230125T0000                           -129.214460   \n",
       "whoi_406-20160902T1700                         -71.549828   \n",
       "\n",
       "                              maxLongitude (degrees_east)  \\\n",
       "datasetID                                                   \n",
       "amelia-20180501T0000                           -74.445788   \n",
       "amelia-20200825T1929                           -74.443807   \n",
       "amelia-20201015T1436                           -74.405013   \n",
       "amlr01-20181216T0641-delayed                   -56.996472   \n",
       "amlr01-20191206T0452-delayed                   -57.433161   \n",
       "...                                                   ...   \n",
       "UW646-20210816T0000                           -124.601065   \n",
       "UW646-20211112T0000                           -124.363708   \n",
       "UW646-20220907T0000                           -124.354081   \n",
       "UW685-20230125T0000                           -124.350906   \n",
       "whoi_406-20160902T1700                         -70.675373   \n",
       "\n",
       "                              minLatitude (degrees_north)  \\\n",
       "datasetID                                                   \n",
       "amelia-20180501T0000                            37.404436   \n",
       "amelia-20200825T1929                            36.334915   \n",
       "amelia-20201015T1436                            37.042386   \n",
       "amlr01-20181216T0641-delayed                   -63.465319   \n",
       "amlr01-20191206T0452-delayed                   -63.555934   \n",
       "...                                                   ...   \n",
       "UW646-20210816T0000                             43.850373   \n",
       "UW646-20211112T0000                             40.820313   \n",
       "UW646-20220907T0000                             40.805190   \n",
       "UW685-20230125T0000                             40.834967   \n",
       "whoi_406-20160902T1700                          40.257794   \n",
       "\n",
       "                              maxLatitude (degrees_north)  minAltitude (m)  \\\n",
       "datasetID                                                                    \n",
       "amelia-20180501T0000                            37.539598    -1.040000e+00   \n",
       "amelia-20200825T1929                            37.353705     2.511368e-02   \n",
       "amelia-20201015T1436                            37.662572    -2.014898e-02   \n",
       "amlr01-20181216T0641-delayed                   -62.203002    -1.315100e-14   \n",
       "amlr01-20191206T0452-delayed                   -62.186826    -3.265242e-15   \n",
       "...                                                   ...              ...   \n",
       "UW646-20210816T0000                             44.653477     4.059241e-01   \n",
       "UW646-20211112T0000                             41.177692     5.003096e-01   \n",
       "UW646-20220907T0000                             41.240848     6.568508e-01   \n",
       "UW685-20230125T0000                             41.195338     3.087025e-01   \n",
       "whoi_406-20160902T1700                          41.120018    -2.490000e+00   \n",
       "\n",
       "                              maxAltitude (m)             minTime  \\\n",
       "datasetID                                                           \n",
       "amelia-20180501T0000                -351.1800 2018-05-01 14:58:48   \n",
       "amelia-20200825T1929                -323.9919 2020-08-25 19:59:18   \n",
       "amelia-20201015T1436                -344.7628 2020-10-15 14:44:15   \n",
       "amlr01-20181216T0641-delayed       -1003.8600 2018-12-16 16:05:20   \n",
       "amlr01-20191206T0452-delayed        -962.1450 2019-12-06 14:45:17   \n",
       "...                                       ...                 ...   \n",
       "UW646-20210816T0000                 -996.5469 2021-08-16 18:57:36   \n",
       "UW646-20211112T0000                -1005.2760 2021-11-12 18:53:18   \n",
       "UW646-20220907T0000                 -994.1479 2022-07-29 04:21:11   \n",
       "UW685-20230125T0000                 -993.3872 2023-01-26 20:10:27   \n",
       "whoi_406-20160902T1700               -98.0500 2016-09-02 17:05:38   \n",
       "\n",
       "                                         maxTime  \n",
       "datasetID                                         \n",
       "amelia-20180501T0000         2018-05-14 12:29:12  \n",
       "amelia-20200825T1929         2020-09-25 14:32:48  \n",
       "amelia-20201015T1436         2020-10-22 06:36:43  \n",
       "amlr01-20181216T0641-delayed 2019-03-08 09:37:33  \n",
       "amlr01-20191206T0452-delayed 2020-03-12 14:37:18  \n",
       "...                                          ...  \n",
       "UW646-20210816T0000          2021-08-24 23:59:59  \n",
       "UW646-20211112T0000          2022-06-16 14:33:31  \n",
       "UW646-20220907T0000          2023-01-26 13:31:17  \n",
       "UW685-20230125T0000          2023-08-14 18:26:07  \n",
       "whoi_406-20160902T1700       2016-09-20 13:32:33  \n",
       "\n",
       "[1682 rows x 9 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f93da4a-0003-45cc-97f7-5c3ec3660cb9",
   "metadata": {},
   "source": [
    "### Which gliders have uploaded data in the last 6 hours?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "559b0afb-e00d-4682-96dc-6eee78975111",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>institution</th>\n",
       "      <th>minLongitude (degrees_east)</th>\n",
       "      <th>maxLongitude (degrees_east)</th>\n",
       "      <th>minLatitude (degrees_north)</th>\n",
       "      <th>maxLatitude (degrees_north)</th>\n",
       "      <th>minAltitude (m)</th>\n",
       "      <th>maxAltitude (m)</th>\n",
       "      <th>minTime</th>\n",
       "      <th>maxTime</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasetID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ce_311-20230616T1819</th>\n",
       "      <td>OOI Coastal Endurance</td>\n",
       "      <td>-125.997510</td>\n",
       "      <td>-124.094224</td>\n",
       "      <td>44.368149</td>\n",
       "      <td>44.737978</td>\n",
       "      <td>-0.029757</td>\n",
       "      <td>-197.05240</td>\n",
       "      <td>2023-06-16 18:35:00</td>\n",
       "      <td>2023-09-14 04:50:18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ng278-20230824T0000</th>\n",
       "      <td>Naval Oceanographic Office</td>\n",
       "      <td>-64.834369</td>\n",
       "      <td>-63.946192</td>\n",
       "      <td>17.844341</td>\n",
       "      <td>18.176379</td>\n",
       "      <td>-0.059496</td>\n",
       "      <td>-958.22280</td>\n",
       "      <td>2023-08-25 13:32:05</td>\n",
       "      <td>2023-09-14 04:24:37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ng291-20230726T164200</th>\n",
       "      <td>Naval Oceanographic Office</td>\n",
       "      <td>-78.668013</td>\n",
       "      <td>-74.572498</td>\n",
       "      <td>29.910854</td>\n",
       "      <td>31.691723</td>\n",
       "      <td>0.079560</td>\n",
       "      <td>-952.19430</td>\n",
       "      <td>2023-07-26 17:07:15</td>\n",
       "      <td>2023-09-14 05:43:32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ng309-20230820T0000</th>\n",
       "      <td>Naval Oceanographic Office</td>\n",
       "      <td>-96.107507</td>\n",
       "      <td>-94.032590</td>\n",
       "      <td>25.419211</td>\n",
       "      <td>27.640507</td>\n",
       "      <td>-0.009915</td>\n",
       "      <td>-932.11950</td>\n",
       "      <td>2023-08-20 23:08:14</td>\n",
       "      <td>2023-09-14 05:43:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ng781-20230816T0000</th>\n",
       "      <td>Naval Oceanographic Office</td>\n",
       "      <td>-95.532589</td>\n",
       "      <td>-93.845523</td>\n",
       "      <td>25.781966</td>\n",
       "      <td>27.756356</td>\n",
       "      <td>-0.009912</td>\n",
       "      <td>-957.95280</td>\n",
       "      <td>2023-08-16 22:18:39</td>\n",
       "      <td>2023-09-14 05:28:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ru39-20230817T1520</th>\n",
       "      <td>Rutgers University</td>\n",
       "      <td>-74.220534</td>\n",
       "      <td>-72.924055</td>\n",
       "      <td>38.852975</td>\n",
       "      <td>40.346194</td>\n",
       "      <td>-0.873282</td>\n",
       "      <td>-84.27055</td>\n",
       "      <td>2023-08-17 15:21:59</td>\n",
       "      <td>2023-09-14 07:39:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG630-20230826T2004</th>\n",
       "      <td>National Oceanic and Atmospheric Administratio...</td>\n",
       "      <td>-67.460857</td>\n",
       "      <td>-66.909718</td>\n",
       "      <td>15.278253</td>\n",
       "      <td>17.867412</td>\n",
       "      <td>0.393429</td>\n",
       "      <td>-904.16140</td>\n",
       "      <td>2023-08-26 20:07:48</td>\n",
       "      <td>2023-09-14 08:11:13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG664-20230719T1323</th>\n",
       "      <td>National Oceanic and Atmospheric Administratio...</td>\n",
       "      <td>-69.618307</td>\n",
       "      <td>-68.465051</td>\n",
       "      <td>15.701596</td>\n",
       "      <td>18.338595</td>\n",
       "      <td>0.586106</td>\n",
       "      <td>-904.99460</td>\n",
       "      <td>2023-07-19 13:29:34</td>\n",
       "      <td>2023-09-14 07:26:11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG665-20230907T2003</th>\n",
       "      <td>National Oceanic and Atmospheric Administratio...</td>\n",
       "      <td>-67.472650</td>\n",
       "      <td>-66.786891</td>\n",
       "      <td>18.501444</td>\n",
       "      <td>18.982994</td>\n",
       "      <td>0.185032</td>\n",
       "      <td>-903.42260</td>\n",
       "      <td>2023-09-07 20:06:57</td>\n",
       "      <td>2023-09-14 07:57:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG666-20230711T1331</th>\n",
       "      <td>National Oceanic and Atmospheric Administratio...</td>\n",
       "      <td>-67.054038</td>\n",
       "      <td>-66.200716</td>\n",
       "      <td>15.290925</td>\n",
       "      <td>17.864093</td>\n",
       "      <td>0.358870</td>\n",
       "      <td>-904.01050</td>\n",
       "      <td>2023-07-11 13:35:27</td>\n",
       "      <td>2023-09-14 07:34:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG668-20230802T1445</th>\n",
       "      <td>National Oceanic and Atmospheric Administratio...</td>\n",
       "      <td>-76.080444</td>\n",
       "      <td>-74.178095</td>\n",
       "      <td>24.649643</td>\n",
       "      <td>25.430809</td>\n",
       "      <td>0.068813</td>\n",
       "      <td>-904.06610</td>\n",
       "      <td>2023-08-02 14:49:04</td>\n",
       "      <td>2023-09-14 07:33:50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG684-20230711T1347</th>\n",
       "      <td>National Oceanic and Atmospheric Administratio...</td>\n",
       "      <td>-67.052246</td>\n",
       "      <td>-64.909879</td>\n",
       "      <td>15.761065</td>\n",
       "      <td>17.864077</td>\n",
       "      <td>0.360176</td>\n",
       "      <td>-905.71930</td>\n",
       "      <td>2023-07-11 13:52:01</td>\n",
       "      <td>2023-09-14 05:42:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sp039-20230309T2136</th>\n",
       "      <td>Scripps Institution of Oceanography</td>\n",
       "      <td>-122.118928</td>\n",
       "      <td>-121.864850</td>\n",
       "      <td>36.678599</td>\n",
       "      <td>36.798950</td>\n",
       "      <td>-0.754396</td>\n",
       "      <td>-854.50550</td>\n",
       "      <td>2023-03-09 23:15:15</td>\n",
       "      <td>2023-09-14 05:30:15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sylvia-20230911T1409</th>\n",
       "      <td>Virginia Institute of Marine Science</td>\n",
       "      <td>-75.704613</td>\n",
       "      <td>-75.366186</td>\n",
       "      <td>36.887819</td>\n",
       "      <td>36.967972</td>\n",
       "      <td>-0.000000</td>\n",
       "      <td>-29.25013</td>\n",
       "      <td>2023-09-11 14:14:02</td>\n",
       "      <td>2023-09-14 06:24:08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ud_476-20230822T2018</th>\n",
       "      <td>University of Delaware</td>\n",
       "      <td>-76.825290</td>\n",
       "      <td>-73.384616</td>\n",
       "      <td>34.254542</td>\n",
       "      <td>38.873762</td>\n",
       "      <td>-0.009924</td>\n",
       "      <td>-100.96090</td>\n",
       "      <td>2023-08-22 21:09:17</td>\n",
       "      <td>2023-09-14 04:49:44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unit_1091-20230905T0000</th>\n",
       "      <td>Skidaway Institute of Oceanography</td>\n",
       "      <td>-80.603126</td>\n",
       "      <td>-79.879858</td>\n",
       "      <td>31.152883</td>\n",
       "      <td>31.564733</td>\n",
       "      <td>-0.000497</td>\n",
       "      <td>-43.52830</td>\n",
       "      <td>2023-09-05 21:08:55</td>\n",
       "      <td>2023-09-14 07:51:13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                               institution  \\\n",
       "datasetID                                                                    \n",
       "ce_311-20230616T1819                                 OOI Coastal Endurance   \n",
       "ng278-20230824T0000                             Naval Oceanographic Office   \n",
       "ng291-20230726T164200                           Naval Oceanographic Office   \n",
       "ng309-20230820T0000                             Naval Oceanographic Office   \n",
       "ng781-20230816T0000                             Naval Oceanographic Office   \n",
       "ru39-20230817T1520                                      Rutgers University   \n",
       "SG630-20230826T2004      National Oceanic and Atmospheric Administratio...   \n",
       "SG664-20230719T1323      National Oceanic and Atmospheric Administratio...   \n",
       "SG665-20230907T2003      National Oceanic and Atmospheric Administratio...   \n",
       "SG666-20230711T1331      National Oceanic and Atmospheric Administratio...   \n",
       "SG668-20230802T1445      National Oceanic and Atmospheric Administratio...   \n",
       "SG684-20230711T1347      National Oceanic and Atmospheric Administratio...   \n",
       "sp039-20230309T2136                    Scripps Institution of Oceanography   \n",
       "sylvia-20230911T1409                  Virginia Institute of Marine Science   \n",
       "ud_476-20230822T2018                                University of Delaware   \n",
       "unit_1091-20230905T0000                 Skidaway Institute of Oceanography   \n",
       "\n",
       "                         minLongitude (degrees_east)  \\\n",
       "datasetID                                              \n",
       "ce_311-20230616T1819                     -125.997510   \n",
       "ng278-20230824T0000                       -64.834369   \n",
       "ng291-20230726T164200                     -78.668013   \n",
       "ng309-20230820T0000                       -96.107507   \n",
       "ng781-20230816T0000                       -95.532589   \n",
       "ru39-20230817T1520                        -74.220534   \n",
       "SG630-20230826T2004                       -67.460857   \n",
       "SG664-20230719T1323                       -69.618307   \n",
       "SG665-20230907T2003                       -67.472650   \n",
       "SG666-20230711T1331                       -67.054038   \n",
       "SG668-20230802T1445                       -76.080444   \n",
       "SG684-20230711T1347                       -67.052246   \n",
       "sp039-20230309T2136                      -122.118928   \n",
       "sylvia-20230911T1409                      -75.704613   \n",
       "ud_476-20230822T2018                      -76.825290   \n",
       "unit_1091-20230905T0000                   -80.603126   \n",
       "\n",
       "                         maxLongitude (degrees_east)  \\\n",
       "datasetID                                              \n",
       "ce_311-20230616T1819                     -124.094224   \n",
       "ng278-20230824T0000                       -63.946192   \n",
       "ng291-20230726T164200                     -74.572498   \n",
       "ng309-20230820T0000                       -94.032590   \n",
       "ng781-20230816T0000                       -93.845523   \n",
       "ru39-20230817T1520                        -72.924055   \n",
       "SG630-20230826T2004                       -66.909718   \n",
       "SG664-20230719T1323                       -68.465051   \n",
       "SG665-20230907T2003                       -66.786891   \n",
       "SG666-20230711T1331                       -66.200716   \n",
       "SG668-20230802T1445                       -74.178095   \n",
       "SG684-20230711T1347                       -64.909879   \n",
       "sp039-20230309T2136                      -121.864850   \n",
       "sylvia-20230911T1409                      -75.366186   \n",
       "ud_476-20230822T2018                      -73.384616   \n",
       "unit_1091-20230905T0000                   -79.879858   \n",
       "\n",
       "                         minLatitude (degrees_north)  \\\n",
       "datasetID                                              \n",
       "ce_311-20230616T1819                       44.368149   \n",
       "ng278-20230824T0000                        17.844341   \n",
       "ng291-20230726T164200                      29.910854   \n",
       "ng309-20230820T0000                        25.419211   \n",
       "ng781-20230816T0000                        25.781966   \n",
       "ru39-20230817T1520                         38.852975   \n",
       "SG630-20230826T2004                        15.278253   \n",
       "SG664-20230719T1323                        15.701596   \n",
       "SG665-20230907T2003                        18.501444   \n",
       "SG666-20230711T1331                        15.290925   \n",
       "SG668-20230802T1445                        24.649643   \n",
       "SG684-20230711T1347                        15.761065   \n",
       "sp039-20230309T2136                        36.678599   \n",
       "sylvia-20230911T1409                       36.887819   \n",
       "ud_476-20230822T2018                       34.254542   \n",
       "unit_1091-20230905T0000                    31.152883   \n",
       "\n",
       "                         maxLatitude (degrees_north)  minAltitude (m)  \\\n",
       "datasetID                                                               \n",
       "ce_311-20230616T1819                       44.737978        -0.029757   \n",
       "ng278-20230824T0000                        18.176379        -0.059496   \n",
       "ng291-20230726T164200                      31.691723         0.079560   \n",
       "ng309-20230820T0000                        27.640507        -0.009915   \n",
       "ng781-20230816T0000                        27.756356        -0.009912   \n",
       "ru39-20230817T1520                         40.346194        -0.873282   \n",
       "SG630-20230826T2004                        17.867412         0.393429   \n",
       "SG664-20230719T1323                        18.338595         0.586106   \n",
       "SG665-20230907T2003                        18.982994         0.185032   \n",
       "SG666-20230711T1331                        17.864093         0.358870   \n",
       "SG668-20230802T1445                        25.430809         0.068813   \n",
       "SG684-20230711T1347                        17.864077         0.360176   \n",
       "sp039-20230309T2136                        36.798950        -0.754396   \n",
       "sylvia-20230911T1409                       36.967972        -0.000000   \n",
       "ud_476-20230822T2018                       38.873762        -0.009924   \n",
       "unit_1091-20230905T0000                    31.564733        -0.000497   \n",
       "\n",
       "                         maxAltitude (m)             minTime  \\\n",
       "datasetID                                                      \n",
       "ce_311-20230616T1819          -197.05240 2023-06-16 18:35:00   \n",
       "ng278-20230824T0000           -958.22280 2023-08-25 13:32:05   \n",
       "ng291-20230726T164200         -952.19430 2023-07-26 17:07:15   \n",
       "ng309-20230820T0000           -932.11950 2023-08-20 23:08:14   \n",
       "ng781-20230816T0000           -957.95280 2023-08-16 22:18:39   \n",
       "ru39-20230817T1520             -84.27055 2023-08-17 15:21:59   \n",
       "SG630-20230826T2004           -904.16140 2023-08-26 20:07:48   \n",
       "SG664-20230719T1323           -904.99460 2023-07-19 13:29:34   \n",
       "SG665-20230907T2003           -903.42260 2023-09-07 20:06:57   \n",
       "SG666-20230711T1331           -904.01050 2023-07-11 13:35:27   \n",
       "SG668-20230802T1445           -904.06610 2023-08-02 14:49:04   \n",
       "SG684-20230711T1347           -905.71930 2023-07-11 13:52:01   \n",
       "sp039-20230309T2136           -854.50550 2023-03-09 23:15:15   \n",
       "sylvia-20230911T1409           -29.25013 2023-09-11 14:14:02   \n",
       "ud_476-20230822T2018          -100.96090 2023-08-22 21:09:17   \n",
       "unit_1091-20230905T0000        -43.52830 2023-09-05 21:08:55   \n",
       "\n",
       "                                    maxTime  \n",
       "datasetID                                    \n",
       "ce_311-20230616T1819    2023-09-14 04:50:18  \n",
       "ng278-20230824T0000     2023-09-14 04:24:37  \n",
       "ng291-20230726T164200   2023-09-14 05:43:32  \n",
       "ng309-20230820T0000     2023-09-14 05:43:21  \n",
       "ng781-20230816T0000     2023-09-14 05:28:22  \n",
       "ru39-20230817T1520      2023-09-14 07:39:13  \n",
       "SG630-20230826T2004     2023-09-14 08:11:13  \n",
       "SG664-20230719T1323     2023-09-14 07:26:11  \n",
       "SG665-20230907T2003     2023-09-14 07:57:36  \n",
       "SG666-20230711T1331     2023-09-14 07:34:50  \n",
       "SG668-20230802T1445     2023-09-14 07:33:50  \n",
       "SG684-20230711T1347     2023-09-14 05:42:47  \n",
       "sp039-20230309T2136     2023-09-14 05:30:15  \n",
       "sylvia-20230911T1409    2023-09-14 06:24:08  \n",
       "ud_476-20230822T2018    2023-09-14 04:49:44  \n",
       "unit_1091-20230905T0000 2023-09-14 07:51:13  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_datasets[ np.datetime64('now') - df_datasets.maxTime < datetime.timedelta(hours=6)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "865ce23d-f6f3-47f1-a601-9fbcfc8f5ea4",
   "metadata": {},
   "source": [
    "### Find datasets from deployments that lasted longer than 90 days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "34307d12-d503-4606-a86b-dcbe5e09c421",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "datasetID\n",
       "amlr01-20191206T0452-delayed       96 days 23:52:01\n",
       "amlr02-20191206T1236-delayed       96 days 15:33:31\n",
       "amlr03-20191206T0529-delayed       96 days 22:19:47\n",
       "bios_anna-20180112T0455            91 days 21:55:52\n",
       "bios_anna-20180112T0455-delayed    93 days 16:11:03\n",
       "                                         ...       \n",
       "UW157-20190916T0000               184 days 22:31:43\n",
       "UW157-20200917T0000               143 days 01:43:53\n",
       "UW646-20211112T0000               215 days 19:40:13\n",
       "UW646-20220907T0000               181 days 09:10:06\n",
       "UW685-20230125T0000               199 days 22:15:40\n",
       "Name: endurance, Length: 413, dtype: timedelta64[ns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_datasets[\"endurance\"] = df_datasets['maxTime'] - df_datasets['minTime']\n",
    "min_days = 90\n",
    "df_datasets[df_datasets[\"endurance\"] > datetime.timedelta(days=min_days)].endurance"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a860eb1e-44d1-461d-a60f-7505d7a6ba9c",
   "metadata": {},
   "source": [
    "### Which glider missions extended to a depth of greater than 150 m in seas north of 70 N?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3951754a-b75b-4757-8fa8-3ebd2130d9fd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>institution</th>\n",
       "      <th>minLongitude (degrees_east)</th>\n",
       "      <th>maxLongitude (degrees_east)</th>\n",
       "      <th>minLatitude (degrees_north)</th>\n",
       "      <th>maxLatitude (degrees_north)</th>\n",
       "      <th>minAltitude (m)</th>\n",
       "      <th>maxAltitude (m)</th>\n",
       "      <th>minTime</th>\n",
       "      <th>maxTime</th>\n",
       "      <th>endurance</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>datasetID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cp_389-20161011T2040-delayed</th>\n",
       "      <td>OOI Coastal &amp; Global Scale Nodes (CGSN)</td>\n",
       "      <td>-71.175203</td>\n",
       "      <td>-47.003674</td>\n",
       "      <td>39.331109</td>\n",
       "      <td>84.001959</td>\n",
       "      <td>0.119085</td>\n",
       "      <td>-987.8069</td>\n",
       "      <td>2016-10-11 20:54:26</td>\n",
       "      <td>2017-01-08 18:09:42</td>\n",
       "      <td>88 days 21:15:16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unit_595-20180804T0000-delayed</th>\n",
       "      <td>University of Alaska Fairbanks, College of Fis...</td>\n",
       "      <td>-168.901621</td>\n",
       "      <td>-155.397927</td>\n",
       "      <td>67.835807</td>\n",
       "      <td>71.753266</td>\n",
       "      <td>-0.072915</td>\n",
       "      <td>-188.1303</td>\n",
       "      <td>2018-08-03 22:28:49</td>\n",
       "      <td>2018-09-24 20:56:07</td>\n",
       "      <td>51 days 22:27:18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                      institution  \\\n",
       "datasetID                                                                           \n",
       "cp_389-20161011T2040-delayed              OOI Coastal & Global Scale Nodes (CGSN)   \n",
       "unit_595-20180804T0000-delayed  University of Alaska Fairbanks, College of Fis...   \n",
       "\n",
       "                                minLongitude (degrees_east)  \\\n",
       "datasetID                                                     \n",
       "cp_389-20161011T2040-delayed                     -71.175203   \n",
       "unit_595-20180804T0000-delayed                  -168.901621   \n",
       "\n",
       "                                maxLongitude (degrees_east)  \\\n",
       "datasetID                                                     \n",
       "cp_389-20161011T2040-delayed                     -47.003674   \n",
       "unit_595-20180804T0000-delayed                  -155.397927   \n",
       "\n",
       "                                minLatitude (degrees_north)  \\\n",
       "datasetID                                                     \n",
       "cp_389-20161011T2040-delayed                      39.331109   \n",
       "unit_595-20180804T0000-delayed                    67.835807   \n",
       "\n",
       "                                maxLatitude (degrees_north)  minAltitude (m)  \\\n",
       "datasetID                                                                      \n",
       "cp_389-20161011T2040-delayed                      84.001959         0.119085   \n",
       "unit_595-20180804T0000-delayed                    71.753266        -0.072915   \n",
       "\n",
       "                                maxAltitude (m)             minTime  \\\n",
       "datasetID                                                             \n",
       "cp_389-20161011T2040-delayed          -987.8069 2016-10-11 20:54:26   \n",
       "unit_595-20180804T0000-delayed        -188.1303 2018-08-03 22:28:49   \n",
       "\n",
       "                                           maxTime        endurance  \n",
       "datasetID                                                            \n",
       "cp_389-20161011T2040-delayed   2017-01-08 18:09:42 88 days 21:15:16  \n",
       "unit_595-20180804T0000-delayed 2018-09-24 20:56:07 51 days 22:27:18  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min_altitude = -150 # note the sign!\n",
    "min_northing = 70\n",
    "mask = (df_datasets['maxAltitude (m)'] < min_altitude).values \\\n",
    "* (df_datasets['maxLatitude (degrees_north)'] > min_northing).values\n",
    "df_datasets[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "a0dcf937-7a3e-4c3f-9ea9-ea6d82211f47",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/callum/mambaforge/envs/goosdemo/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast\n",
      "  flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(\n",
      "/home/callum/mambaforge/envs/goosdemo/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast\n",
      "  flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(\n"
     ]
    }
   ],
   "source": [
    "e = ERDDAP(\n",
    "    server=\"https://gliders.ioos.us/erddap\",\n",
    "    protocol=\"tabledap\",\n",
    ")\n",
    "e.constraints = {\"time>=\": \"2018-09-20\"}\n",
    "\n",
    "e.dataset_id = \"unit_595-20180804T0000-delayed\"\n",
    "ds = e.to_xarray()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a0385e04-eefc-4440-a7e4-c8c79fff4c55",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/callum/mambaforge/envs/goosdemo/lib/python3.11/site-packages/xarray/coding/times.py:254: RuntimeWarning: invalid value encountered in cast\n",
      "  flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f676d243bd0>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.u.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "111ba964-7a64-4c99-beda-0d30e471f925",
   "metadata": {},
   "source": [
    "---------------------------\n",
    "### References\n",
    "\n",
    "IOOS ERDDAP https://gliders.ioos.us/erddap\n",
    "\n",
    "More info on using ERDDAP's inbuilt search https://ioos.github.io/erddapy/01b-tabledap-output.html"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}