access_glider_from_GDAC.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Glider data from the Glider Data Assembly center\n",
    "\n",
    "Glider data from the US Integrated Ocean Observing System\n",
    "\n",
    "A map of current glider deployments is available here:\n",
    "https://gliders.ioos.us/map/\n",
    "\n",
    "and data is available via THREDDS server: https://gliders.ioos.us/thredds/catalog/deployments/catalog.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/beaird/anaconda3/lib/python3.7/site-packages/xarray/core/merge.py:17: FutureWarning: The Panel class is removed from pandas. Accessing it from the top-level namespace will also be removed in the next version\n",
      "  PANDAS_TYPES = (pd.Series, pd.DataFrame, pd.Panel)\n"
     ]
    }
   ],
   "source": [
    "import xarray as xr\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                                  (obs: 247, profile: 1344, trajectory: 1)\n",
       "Coordinates:\n",
       "  * trajectory                               (trajectory) object 'bios_minnie-20191021T1613'\n",
       "    time                                     (trajectory, profile) float64 ...\n",
       "    latitude                                 (trajectory, profile) float64 ...\n",
       "    longitude                                (trajectory, profile) float64 ...\n",
       "    time_uv                                  (trajectory, profile) float64 ...\n",
       "    lat_uv                                   (trajectory, profile) float64 ...\n",
       "    lon_uv                                   (trajectory, profile) float64 ...\n",
       "    depth                                    (trajectory, profile, obs) float32 ...\n",
       "Dimensions without coordinates: obs, profile\n",
       "Data variables:\n",
       "    wmo_id                                   (trajectory) object ...\n",
       "    profile_id                               (trajectory, profile) float64 ...\n",
       "    u                                        (trajectory, profile) float64 ...\n",
       "    v                                        (trajectory, profile) float64 ...\n",
       "    precise_time                             (trajectory, profile, obs) float64 ...\n",
       "    pressure                                 (trajectory, profile, obs) float32 ...\n",
       "    temperature                              (trajectory, profile, obs) float32 ...\n",
       "    conductivity                             (trajectory, profile, obs) float32 ...\n",
       "    salinity                                 (trajectory, profile, obs) float32 ...\n",
       "    density                                  (trajectory, profile, obs) float32 ...\n",
       "    precise_lat                              (trajectory, profile, obs) float64 ...\n",
       "    precise_lon                              (trajectory, profile, obs) float64 ...\n",
       "    platform_meta                            (trajectory, profile, obs) float32 ...\n",
       "    instrument_ctd                           (trajectory, profile, obs) float32 ...\n",
       "    precise_lon_qc                           (trajectory, profile, obs) float32 ...\n",
       "    salinity_qc                              (trajectory, profile, obs) float32 ...\n",
       "    density_qc                               (trajectory, profile, obs) float32 ...\n",
       "    temperature_qc                           (trajectory, profile, obs) float32 ...\n",
       "    lat_uv_qc                                (trajectory, profile, obs) float32 ...\n",
       "    precise_time_qc                          (trajectory, profile, obs) float32 ...\n",
       "    longitude_qc                             (trajectory, profile, obs) float32 ...\n",
       "    pressure_qc                              (trajectory, profile, obs) float32 ...\n",
       "    time_uv_qc                               (trajectory, profile, obs) float32 ...\n",
       "    latitude_qc                              (trajectory, profile, obs) float32 ...\n",
       "    u_qc                                     (trajectory, profile, obs) float32 ...\n",
       "    v_qc                                     (trajectory, profile, obs) float32 ...\n",
       "    depth_qc                                 (trajectory, profile, obs) float32 ...\n",
       "    time_qc                                  (trajectory, profile, obs) float32 ...\n",
       "    lon_uv_qc                                (trajectory, profile, obs) float32 ...\n",
       "    precise_lat_qc                           (trajectory, profile, obs) float32 ...\n",
       "    conductivity_qc                          (trajectory, profile, obs) float32 ...\n",
       "    qartod_density_spike_flag                (trajectory, profile, obs) float32 ...\n",
       "    qartod_density_gross_range_flag          (trajectory, profile, obs) float32 ...\n",
       "    qartod_salinity_gross_range_flag         (trajectory, profile, obs) float32 ...\n",
       "    qartod_salinity_spike_flag               (trajectory, profile, obs) float32 ...\n",
       "    qartod_conductivity_primary_flag         (trajectory, profile, obs) float32 ...\n",
       "    qartod_conductivity_flat_line_flag       (trajectory, profile, obs) float32 ...\n",
       "    qartod_density_primary_flag              (trajectory, profile, obs) float32 ...\n",
       "    qartod_density_flat_line_flag            (trajectory, profile, obs) float32 ...\n",
       "    qartod_salinity_rate_of_change_flag      (trajectory, profile, obs) float32 ...\n",
       "    qartod_temperature_spike_flag            (trajectory, profile, obs) float32 ...\n",
       "    qartod_conductivity_gross_range_flag     (trajectory, profile, obs) float32 ...\n",
       "    qartod_pressure_gross_range_flag         (trajectory, profile, obs) float32 ...\n",
       "    qartod_density_rate_of_change_flag       (trajectory, profile, obs) float32 ...\n",
       "    qartod_temperature_flat_line_flag        (trajectory, profile, obs) float32 ...\n",
       "    qartod_pressure_spike_flag               (trajectory, profile, obs) float32 ...\n",
       "    qartod_pressure_primary_flag             (trajectory, profile, obs) float32 ...\n",
       "    qartod_conductivity_rate_of_change_flag  (trajectory, profile, obs) float32 ...\n",
       "    qartod_monotonic_pressure_flag           (trajectory, profile, obs) float32 ...\n",
       "    qartod_pressure_rate_of_change_flag      (trajectory, profile, obs) float32 ...\n",
       "    qartod_salinity_primary_flag             (trajectory, profile, obs) float32 ...\n",
       "    qartod_salinity_flat_line_flag           (trajectory, profile, obs) float32 ...\n",
       "    qartod_temperature_gross_range_flag      (trajectory, profile, obs) float32 ...\n",
       "    qartod_conductivity_spike_flag           (trajectory, profile, obs) float32 ...\n",
       "    qartod_temperature_rate_of_change_flag   (trajectory, profile, obs) float32 ...\n",
       "    qartod_pressure_flat_line_flag           (trajectory, profile, obs) float32 ...\n",
       "    qartod_temperature_primary_flag          (trajectory, profile, obs) float32 ...\n",
       "Attributes:\n",
       "    acknowledgment:                This deployment supported by the National ...\n",
       "    cdm_data_type:                 TrajectoryProfile\n",
       "    cdm_profile_variables:         time_uv,lat_uv,lon_uv,u,v,profile_id,time,...\n",
       "    cdm_trajectory_variables:      trajectory,wmo_id\n",
       "    contributor_name:              Ruth Curry\n",
       "    contributor_role:              Program PI\n",
       "    Conventions:                   Unidata Dataset Discovery v1.0, COARDS, CF...\n",
       "    creator_email:                 ruth.curry@bios.edu \n",
       "    creator_name:                  Ruth Curry \n",
       "    creator_url:                    magic.bios.edu\n",
       "    date_created:                  2020-01-24T15:33:48Z\n",
       "    date_issued:                   2020-01-24T15:33:48Z\n",
       "    Easternmost_Easting:           -63.87705965323364\n",
       "    featureType:                   TrajectoryProfile\n",
       "    format_version:                IOOS_Glider_NetCDF_v3.0-noqartod.nc\n",
       "    geospatial_lat_max:            31.866578100508015\n",
       "    geospatial_lat_min:            31.65864874487505\n",
       "    geospatial_lat_units:          degrees_north\n",
       "    geospatial_lon_max:            -63.87705965323364\n",
       "    geospatial_lon_min:            -64.09326739855638\n",
       "    geospatial_lon_units:          degrees_east\n",
       "    geospatial_vertical_max:       88.961\n",
       "    geospatial_vertical_min:       1.0\n",
       "    geospatial_vertical_positive:  down\n",
       "    geospatial_vertical_units:     m\n",
       "    history:                       2020-01-24T15:33:48Z Y:Glidersmfilesslocum...\n",
       "    id:                            bios_minnie-20191021T1613_f070_8f49_1646\n",
       "    infoUrl:                       http://data.ioos.us/gliders/erddap/\n",
       "    institution:                   Bermuda Institute of Ocean Sciences \n",
       "    ioos_dac_checksum:             9428ac57cb26f2c0b68a1afa4f578ae3\n",
       "    ioos_dac_completed:            False\n",
       "    keywords:                      AUVS > Autonomous Underwater Vehicles, Oce...\n",
       "    keywords_vocabulary:           GCMD Science Keywords\n",
       "    license:                       This data may be redistributed and used wi...\n",
       "    Metadata_Conventions:          Unidata Dataset Discovery v1.0, COARDS, CF...\n",
       "    naming_authority:              bios.edu\n",
       "    Northernmost_Northing:         31.866578100508015\n",
       "    platform_type:                 Slocum Glider\n",
       "    processing_level:              Data provided are provided in near realtim...\n",
       "    project:                       MAGIC: Mid Atlantic Glider Initiative and ...\n",
       "    publisher_email:               ruth.curry@bios.edu \n",
       "    publisher_name:                 Ruth Curry\n",
       "    publisher_url:                  magic.bios.edu\n",
       "    sea_name:                      Northwest Atlantic Ocean\n",
       "    source:                        Observational data from a profiling glider\n",
       "    sourceUrl:                     (local files)\n",
       "    Southernmost_Northing:         31.65864874487505\n",
       "    standard_name_vocabulary:      CF-v25\n",
       "    subsetVariables:               trajectory,wmo_id,time_uv,lat_uv,lon_uv,u,...\n",
       "    summary:                       The Bermuda Institute of Ocean Sciences MA...\n",
       "    time_coverage_end:             2020-01-24T12:56:01Z\n",
       "    time_coverage_start:           2019-10-21T16:26:39Z\n",
       "    title:                         bios_minnie-20191021T1613\n",
       "    Westernmost_Easting:           -64.09326739855638\n",
       "    DODS.strlen:                   7\n",
       "    DODS.dimName:                  wmo_id_strlen"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# url = 'http://gliders.ioos.us/thredds/dodsC/deployments/mbari/UW157-20190916T0000/UW157-20190916T0000.nc3.nc'\n",
    "url = 'http://gliders.ioos.us/thredds/dodsC/deployments/bios/bios_minnie-20191021T1613/bios_minnie-20191021T1613.nc3.nc'\n",
    "\n",
    "gl = xr.open_dataset(url, decode_times=False)\n",
    "\n",
    "gl"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# data dimensions are profile and observation number\n",
    "but its not actually gridded, and adjacent profiles are going in oposite directions (observation 1 is at the surface in profile 1, and observation 1 is at depth in profile two)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:          (obs: 521, profile: 1068)\n",
       "Coordinates:\n",
       "    trajectory       <U19 'UW157-20190916T0000'\n",
       "    time             (profile) datetime64[ns] ...\n",
       "    latitude         (profile) float64 ...\n",
       "    longitude        (profile) float64 ...\n",
       "    time_uv          (profile) datetime64[ns] ...\n",
       "    lat_uv           (profile) float64 ...\n",
       "    lon_uv           (profile) float64 ...\n",
       "    depth            (profile, obs) float32 ...\n",
       "Dimensions without coordinates: obs, profile\n",
       "Data variables:\n",
       "    wmo_id           object ...\n",
       "    profile_id       (profile) float64 ...\n",
       "    u                (profile) float64 ...\n",
       "    v                (profile) float64 ...\n",
       "    precise_time     (profile, obs) datetime64[ns] ...\n",
       "    pressure         (profile, obs) float32 ...\n",
       "    temperature      (profile, obs) float32 ...\n",
       "    conductivity     (profile, obs) float32 ...\n",
       "    salinity         (profile, obs) float32 ...\n",
       "    density          (profile, obs) float32 ...\n",
       "    precise_lat      (profile, obs) float64 ...\n",
       "    precise_lon      (profile, obs) float64 ...\n",
       "    platform_meta    (profile, obs) float32 ...\n",
       "    instrument_ctd   (profile, obs) float32 ...\n",
       "    precise_lon_qc   (profile, obs) float32 ...\n",
       "    salinity_qc      (profile, obs) float32 ...\n",
       "    density_qc       (profile, obs) float32 ...\n",
       "    temperature_qc   (profile, obs) float32 ...\n",
       "    lat_uv_qc        (profile, obs) float32 ...\n",
       "    precise_time_qc  (profile, obs) float32 ...\n",
       "    longitude_qc     (profile, obs) float32 ...\n",
       "    pressure_qc      (profile, obs) float32 ...\n",
       "    time_uv_qc       (profile, obs) float32 ...\n",
       "    latitude_qc      (profile, obs) float32 ...\n",
       "    u_qc             (profile, obs) float32 ...\n",
       "    v_qc             (profile, obs) float32 ...\n",
       "    depth_qc         (profile, obs) float32 ...\n",
       "    time_qc          (profile, obs) float32 ...\n",
       "    lon_uv_qc        (profile, obs) float32 ...\n",
       "    precise_lat_qc   (profile, obs) float32 ...\n",
       "    conductivity_qc  (profile, obs) float32 ...\n",
       "    fluorescence     (profile, obs) float64 ...\n",
       "    fluorescence_qc  (profile, obs) float32 ...\n",
       "    oxygen           (profile, obs) float64 ...\n",
       "    oxygen_qc        (profile, obs) float32 ...\n",
       "Attributes:\n",
       "    acknowledgment:                Integrated Ocean Observing System (IOOS)NA...\n",
       "    cdm_data_type:                 TrajectoryProfile\n",
       "    cdm_profile_variables:         time_uv,lat_uv,lon_uv,u,v,profile_id,time,...\n",
       "    cdm_trajectory_variables:      trajectory,wmo_id\n",
       "    comment:                       Data has not been reviewed and is provided...\n",
       "    contributor_name:              Jack Barth, R. Kipp Shearman\n",
       "    contributor_role:              Principal investigator, Principal investig...\n",
       "    Conventions:                   Unidata Dataset Discovery v1.0, COARDS, CF...\n",
       "    creator_email:                 barth@coas.oregonstate.edu\n",
       "    creator_name:                  Jack Barth\n",
       "    creator_url:                   gliderfs2.coas.oregonstate.edu/gliderweb\n",
       "    date_created:                  2020-01-24T17:01:23Z\n",
       "    date_issued:                   2020-01-24T17:01:23Z\n",
       "    date_modified:                 2020-01-24T17:01:23Z\n",
       "    Easternmost_Easting:           -124.34995644076315\n",
       "    featureType:                   TrajectoryProfile\n",
       "    format_version:                IOOS_Glider_NetCDF_v2.0.nc\n",
       "    geospatial_lat_max:            41.106238251717976\n",
       "    geospatial_lat_min:            40.842825000000005\n",
       "    geospatial_lat_units:          degrees_north\n",
       "    geospatial_lon_max:            -124.34995644076315\n",
       "    geospatial_lon_min:            -130.00003137243965\n",
       "    geospatial_lon_units:          degrees_east\n",
       "    geospatial_vertical_max:       1008.427\n",
       "    geospatial_vertical_min:       -0.2888346\n",
       "    geospatial_vertical_positive:  down\n",
       "    geospatial_vertical_units:     m\n",
       "    gts_ingest:                    true\n",
       "    history:                       Processing start:\\nINFO: QC.py(378): Chang...\n",
       "    id:                            UW157-20190916T0000_f070_8f49_1646\n",
       "    infoUrl:                       http://data.ioos.us/gliders/erddap/\n",
       "    institution:                   Oregon State University\n",
       "    ioos_dac_checksum:             d3f9b2f429e81483662b0cc5033c1957\n",
       "    ioos_dac_completed:            False\n",
       "    ioos_regional_association:     CeNCOOS,NANOOS\n",
       "    keywords:                      AUVS > Autonomous Underwater Vehicles, Oce...\n",
       "    keywords_vocabulary:           GCMD Science Keywords\n",
       "    license:                       These data may be redistributed and used w...\n",
       "    Metadata_Conventions:          Unidata Dataset Discovery v1.0, COARDS, CF...\n",
       "    naming_authority:              edu.washington.apl\n",
       "    Northernmost_Northing:         41.106238251717976\n",
       "    platform_type:                 Seaglider\n",
       "    processing_level:              1.120000\n",
       "    project:                       IOOS Oregon State University seaglider sam...\n",
       "    publisher_email:               cencoos_communications@mbari.org\n",
       "    publisher_name:                Central and Northern California Ocean Obse...\n",
       "    publisher_url:                 www.cencoos.org\n",
       "    references:                    http://data.nodc.noaa.gov/accession/0092291\n",
       "    sea_name:                      North Pacific Ocean\n",
       "    source:                        Seaglider UW157\n",
       "    sourceUrl:                     (local files)\n",
       "    Southernmost_Northing:         40.842825000000005\n",
       "    standard_name_vocabulary:      CF-1.6\n",
       "    subsetVariables:               trajectory,wmo_id,time_uv,lat_uv,lon_uv,u,...\n",
       "    summary:                       Seaglider UW157 Trinidad Head IOOS line, C...\n",
       "    time_coverage_end:             2020-01-24T16:10:49Z\n",
       "    time_coverage_start:           2019-09-16T18:03:12Z\n",
       "    title:                         UW157-20190916T0000\n",
       "    Westernmost_Easting:           -130.00003137243965\n",
       "    DODS.strlen:                   9\n",
       "    DODS.dimName:                  wmo_id_strlen"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gl.squeeze()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 50)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "gl.depth.squeeze().plot()\n",
    "plt.ylim(0,50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "x and y must be the same size",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-20-b1edff1fd581>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpressure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0mc\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mgl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtemperature\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36mscatter\u001b[0;34m(x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, data, **kwargs)\u001b[0m\n\u001b[1;32m   2845\u001b[0m         \u001b[0mverts\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0medgecolors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0medgecolors\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2846\u001b[0m         plotnonfinite=plotnonfinite, **({\"data\": data} if data is not\n\u001b[0;32m-> 2847\u001b[0;31m         None else {}), **kwargs)\n\u001b[0m\u001b[1;32m   2848\u001b[0m     \u001b[0msci\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m__ret\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2849\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0m__ret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36minner\u001b[0;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1599\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0minner\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1600\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mdata\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1601\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msanitize_sequence\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1602\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1603\u001b[0m         \u001b[0mbound\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_sig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbind\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36mscatter\u001b[0;34m(self, x, y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, plotnonfinite, **kwargs)\u001b[0m\n\u001b[1;32m   4442\u001b[0m         \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4443\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4444\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"x and y must be the same size\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   4445\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4446\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0ms\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: x and y must be the same size"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(gl.time.squeeze().values.ravel(), gl.pressure.squeeze().values.ravel(),  c=gl.temperature.squeeze().values.ravel());"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}