dcherian/aquarius_wrangling.ipynb

## aquarius_wrangling.ipynb
{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "# Data wrangling with xarray: Datasets that don't follow CF conventions completely\n\nTake for example, this particular dataset from the Aquarius satellite that primarily measures sea surface salinity (SSS). Available at https://podaac.jpl.nasa.gov/dataset/AQUARIUS_L3_SSS-RainFlagged_SMID_7DAY_V5?ids=Collections:Measurement:Variable:TemporalResolution&values=Aquarius:Salinity/Density:Salinity:Weekly\n\n(To get this I downloaded it using WebDAV and then extracted each file from a bz2 archive by folder).\n\nI'm working with a folder that looks like this:"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:06.502597Z",
          "end_time": "2018-07-25T21:17:06.647003Z"
        },
        "scrolled": true,
        "trusted": true
      },
      "cell_type": "code",
      "source": "!ls /home/deepak/datasets/aquarius/combined/",
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": "Q20140012014007.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140082014014.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140152014021.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140222014028.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140292014035.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140362014042.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140432014049.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140502014056.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140572014063.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140642014070.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140712014077.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140782014084.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140852014091.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140922014098.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20140992014105.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141062014112.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141132014119.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141202014126.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141272014133.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141342014140.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141412014147.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141482014154.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141552014161.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141622014168.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141692014175.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141762014182.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141832014189.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141902014196.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20141972014203.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142042014210.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142112014217.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142182014224.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142252014231.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142322014238.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142392014245.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142462014252.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142532014259.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142602014266.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142672014273.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142742014280.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142812014287.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142882014294.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20142952014301.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143022014308.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143092014315.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143162014322.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143232014329.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143302014336.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143372014343.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143442014350.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143512014357.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143582014364.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\nQ20143652015006.L3m_7D_SCID_V5.0_SSS_1deg.nc\r\n",
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Fixing a single file"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:06.653443Z",
          "end_time": "2018-07-25T21:17:06.704857Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "ds = xr.open_dataset('/home/deepak/datasets/aquarius/combined/Q20140012014007.L3m_7D_SCID_V5.0_SSS_1deg.nc')\nds",
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 6,
          "data": {
            "text/plain": "<xarray.Dataset>\nDimensions:   (phony_dim_0: 180, phony_dim_1: 360, phony_dim_2: 3, phony_dim_3: 256)\nDimensions without coordinates: phony_dim_0, phony_dim_1, phony_dim_2, phony_dim_3\nData variables:\n    l3m_data  (phony_dim_0, phony_dim_1) float32 ...\n    palette   (phony_dim_2, phony_dim_3) uint8 ...\nAttributes:\n    product_name:                      Q20140012014007.L3m_7D_SCID_V5.0_SSS_1deg\n    instrument:                        Aquarius\n    title:                             Aquarius Level-3 Standard Mapped Image\n    project:                           Ocean Biology Processing Group (NASA/G...\n    platform:                          SAC-D Aquarius\n    temporal_range:                    7D\n    processing_version:                V5.0\n    date_created:                      2017-10-21T13:55:07.000Z\n    history:                           smigen par=Q20140012014007.L3m_7D_SCID...\n    l2_flag_names:                     POINTING,NAV,LANDRED,ICERED,REFL_1STOK...\n    time_coverage_start:               2014-01-01T02:20:44.939Z\n    time_coverage_end:                 2014-01-08T01:05:43.652Z\n    start_orbit_number:                13765\n    end_orbit_number:                  13867\n    map_projection:                    Equidistant Cylindrical\n    latitude_units:                    degrees_north\n    longitude_units:                   degrees_east\n    northernmost_latitude:             90.0\n    southernmost_latitude:             -90.0\n    westernmost_longitude:             -180.0\n    easternmost_longitude:             180.0\n    geospatial_lat_max:                90.0\n    geospatial_lat_min:                -90.0\n    geospatial_lon_max:                180.0\n    geospatial_lon_min:                -180.0\n    grid_mapping_name:                 latitude_longitude\n    latitude_step:                     1.0\n    longitude_step:                    1.0\n    sw_point_latitude:                 -89.5\n    sw_point_longitude:                -179.5\n    geospatial_lon_resolution:         1.0\n    geospatial_lat_resolution:         1.0\n    geospatial_lat_units:              deg\n    geospatial_lon_units:              deg\n    spatialResolution:                 1.00 deg\n    data_bins:                         28393\n    number_of_lines:                   180\n    number_of_columns:                 360\n    measure:                           Mean\n    data_minimum:                      4.82436\n    data_maximum:                      38.82527\n    suggested_image_scaling_minimum:   0.0\n    suggested_image_scaling_maximum:   70.0\n    suggested_image_scaling_type:      ATAN\n    suggested_image_scaling_applied:   No\n    _lastModified:                     2017-10-21T13:55:07.000Z\n    Conventions:                       CF-1.6\n    institution:                       NASA Goddard Space Flight Center, Ocea...\n    standard_name_vocabulary:          NetCDF Climate and Forecast (CF) Metad...\n    Metadata_Conventions:              Unidata Dataset Discovery v1.0\n    naming_authority:                  gov.nasa.gsfc.sci.oceandata\n    id:                                Q20140012014007.L3b_7D_SCID_V5.0.main/...\n    license:                           http://science.nasa.gov/earth-science/...\n    creator_name:                      NASA/GSFC/OBPG\n    publisher_name:                    NASA/GSFC/OBPG\n    creator_email:                     data@oceancolor.gsfc.nasa.gov\n    publisher_email:                   data@oceancolor.gsfc.nasa.gov\n    creator_url:                       http://oceandata.sci.gsfc.nasa.gov\n    publisher_url:                     http://oceandata.sci.gsfc.nasa.gov\n    processing_level:                  L3 Mapped\n    cdm_data_type:                     grid\n    identifier_product_doi_authority:  http://dx.doi.org\n    identifier_product_doi:            http://dx.doi.org\n    keywords:                          SURFACE SALINITY, SALINITY, AQUARIUS, ...\n    keywords_vocabulary:               NASA Global Change Master Directory (G...\n    software_name:                     smigen\n    software_version:                  5.20\n    source:                            Q20140012014007.L3b_7D_SCID_V5.0.main"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "What does a plot look like?"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:06.706765Z",
          "end_time": "2018-07-25T21:17:07.219783Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "ds.l3m_data.plot()",
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 7,
          "data": {
            "text/plain": "<matplotlib.collections.QuadMesh at 0x7f55ac4af208>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 2 Axes>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": ":/\n\nThe dimensions are phony, the variable name is not useful; and the plot is upside down. Sigh.\n\nLets try `open_mfdataset`"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:07.221906Z",
          "end_time": "2018-07-25T21:17:07.424975Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "aq = xr.open_mfdataset('/home/deepak/datasets/aquarius/combined/*.nc', autoclose=True)",
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "cannot infer dimension to concatenate: supply the ``concat_dim`` argument explicitly",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-8-2ae73787f6d4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0maq\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mxr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopen_mfdataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/home/deepak/datasets/aquarius/combined/*.nc'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mautoclose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m~/work/python/xarray/xarray/backends/api.py\u001b[0m in \u001b[0;36mopen_mfdataset\u001b[0;34m(paths, chunks, concat_dim, compat, preprocess, engine, lock, data_vars, coords, autoclose, parallel, **kwargs)\u001b[0m\n\u001b[1;32m    636\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mconcat_dim\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0m_CONCAT_DIM_DEFAULT\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    637\u001b[0m             combined = auto_combine(datasets, compat=compat,\n\u001b[0;32m--> 638\u001b[0;31m                                     data_vars=data_vars, coords=coords)\n\u001b[0m\u001b[1;32m    639\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    640\u001b[0m             combined = auto_combine(datasets, concat_dim=concat_dim,\n",
            "\u001b[0;32m~/work/python/xarray/xarray/core/combine.py\u001b[0m in \u001b[0;36mauto_combine\u001b[0;34m(datasets, concat_dim, compat, data_vars, coords)\u001b[0m\n\u001b[1;32m    434\u001b[0m         concatenated = [_auto_concat(ds, dim=dim,\n\u001b[1;32m    435\u001b[0m                                      data_vars=data_vars, coords=coords)\n\u001b[0;32m--> 436\u001b[0;31m                         for ds in grouped]\n\u001b[0m\u001b[1;32m    437\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    438\u001b[0m         \u001b[0mconcatenated\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdatasets\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/core/combine.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    434\u001b[0m         concatenated = [_auto_concat(ds, dim=dim,\n\u001b[1;32m    435\u001b[0m                                      data_vars=data_vars, coords=coords)\n\u001b[0;32m--> 436\u001b[0;31m                         for ds in grouped]\n\u001b[0m\u001b[1;32m    437\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    438\u001b[0m         \u001b[0mconcatenated\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdatasets\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/core/combine.py\u001b[0m in \u001b[0;36m_auto_concat\u001b[0;34m(datasets, dim, data_vars, coords)\u001b[0m\n\u001b[1;32m    359\u001b[0m                                  'concatenate: %s' % concat_dims)\n\u001b[1;32m    360\u001b[0m             \u001b[0;32melif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconcat_dims\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 361\u001b[0;31m                 raise ValueError('cannot infer dimension to concatenate: '\n\u001b[0m\u001b[1;32m    362\u001b[0m                                  \u001b[0;34m'supply the ``concat_dim`` argument '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    363\u001b[0m                                  'explicitly')\n",
            "\u001b[0;31mValueError\u001b[0m: cannot infer dimension to concatenate: supply the ``concat_dim`` argument explicitly"
          ]
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "If we look closely at the Dataset `repr` we see that the time co-ordinate is in the dataset attributes and the appropriate dimension doesn't exist. This will take some work."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:09.559105Z",
          "end_time": "2018-07-25T21:17:09.592156Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "dsnew = ds.copy()",
      "execution_count": 9,
      "outputs": []
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Adding proper lat, lon co-ordinates\n\nLet's first create `latitude` and `longitude` co-ordinates and sort by `latitude`"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:09.594229Z",
          "end_time": "2018-07-25T21:17:09.621637Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "dsnew['latitude'] = xr.DataArray(np.linspace(90, -90, 180),\n                                 dims=['phony_dim_0'])\ndsnew['longitude'] = xr.DataArray(np.linspace(-180, 180, 360),\n                                  dims=['phony_dim_1'])\ndsnew = (dsnew.rename({'l3m_data': 'sss',\n                       'phony_dim_0': 'latitude',\n                       'phony_dim_1': 'longitude'})\n         .set_coords(['latitude', 'longitude']))\n\ndsnew",
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 10,
          "data": {
            "text/plain": "<xarray.Dataset>\nDimensions:    (latitude: 180, longitude: 360, phony_dim_2: 3, phony_dim_3: 256)\nCoordinates:\n  * latitude   (latitude) float64 90.0 88.99 87.99 86.98 85.98 84.97 83.97 ...\n  * longitude  (longitude) float64 -180.0 -179.0 -178.0 -177.0 -176.0 -175.0 ...\nDimensions without coordinates: phony_dim_2, phony_dim_3\nData variables:\n    sss        (latitude, longitude) float32 ...\n    palette    (phony_dim_2, phony_dim_3) uint8 ...\nAttributes:\n    product_name:                      Q20140012014007.L3m_7D_SCID_V5.0_SSS_1deg\n    instrument:                        Aquarius\n    title:                             Aquarius Level-3 Standard Mapped Image\n    project:                           Ocean Biology Processing Group (NASA/G...\n    platform:                          SAC-D Aquarius\n    temporal_range:                    7D\n    processing_version:                V5.0\n    date_created:                      2017-10-21T13:55:07.000Z\n    history:                           smigen par=Q20140012014007.L3m_7D_SCID...\n    l2_flag_names:                     POINTING,NAV,LANDRED,ICERED,REFL_1STOK...\n    time_coverage_start:               2014-01-01T02:20:44.939Z\n    time_coverage_end:                 2014-01-08T01:05:43.652Z\n    start_orbit_number:                13765\n    end_orbit_number:                  13867\n    map_projection:                    Equidistant Cylindrical\n    latitude_units:                    degrees_north\n    longitude_units:                   degrees_east\n    northernmost_latitude:             90.0\n    southernmost_latitude:             -90.0\n    westernmost_longitude:             -180.0\n    easternmost_longitude:             180.0\n    geospatial_lat_max:                90.0\n    geospatial_lat_min:                -90.0\n    geospatial_lon_max:                180.0\n    geospatial_lon_min:                -180.0\n    grid_mapping_name:                 latitude_longitude\n    latitude_step:                     1.0\n    longitude_step:                    1.0\n    sw_point_latitude:                 -89.5\n    sw_point_longitude:                -179.5\n    geospatial_lon_resolution:         1.0\n    geospatial_lat_resolution:         1.0\n    geospatial_lat_units:              deg\n    geospatial_lon_units:              deg\n    spatialResolution:                 1.00 deg\n    data_bins:                         28393\n    number_of_lines:                   180\n    number_of_columns:                 360\n    measure:                           Mean\n    data_minimum:                      4.82436\n    data_maximum:                      38.82527\n    suggested_image_scaling_minimum:   0.0\n    suggested_image_scaling_maximum:   70.0\n    suggested_image_scaling_type:      ATAN\n    suggested_image_scaling_applied:   No\n    _lastModified:                     2017-10-21T13:55:07.000Z\n    Conventions:                       CF-1.6\n    institution:                       NASA Goddard Space Flight Center, Ocea...\n    standard_name_vocabulary:          NetCDF Climate and Forecast (CF) Metad...\n    Metadata_Conventions:              Unidata Dataset Discovery v1.0\n    naming_authority:                  gov.nasa.gsfc.sci.oceandata\n    id:                                Q20140012014007.L3b_7D_SCID_V5.0.main/...\n    license:                           http://science.nasa.gov/earth-science/...\n    creator_name:                      NASA/GSFC/OBPG\n    publisher_name:                    NASA/GSFC/OBPG\n    creator_email:                     data@oceancolor.gsfc.nasa.gov\n    publisher_email:                   data@oceancolor.gsfc.nasa.gov\n    creator_url:                       http://oceandata.sci.gsfc.nasa.gov\n    publisher_url:                     http://oceandata.sci.gsfc.nasa.gov\n    processing_level:                  L3 Mapped\n    cdm_data_type:                     grid\n    identifier_product_doi_authority:  http://dx.doi.org\n    identifier_product_doi:            http://dx.doi.org\n    keywords:                          SURFACE SALINITY, SALINITY, AQUARIUS, ...\n    keywords_vocabulary:               NASA Global Change Master Directory (G...\n    software_name:                     smigen\n    software_version:                  5.20\n    source:                            Q20140012014007.L3b_7D_SCID_V5.0.main"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Proper time co-ordinate\n\nThe next step is to add a time co-ordinate with appropriate value inferred from metadata; and expand all variables to have it. Note I am adding 3.5 days since each file contains a 7-day merged field."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:09.623299Z",
          "end_time": "2018-07-25T21:17:09.653571Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "import pandas as pd\n\ndsnew['time'] = (pd.to_datetime(dsnew.attrs['time_coverage_start'])\n                 + np.timedelta64(3, 'D') + np.timedelta64(12, 'h'))\n\ndsnew = (dsnew\n         .expand_dims('time')\n         .set_coords('time'))\n\ndsnew",
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 11,
          "data": {
            "text/plain": "<xarray.Dataset>\nDimensions:    (latitude: 180, longitude: 360, phony_dim_2: 3, phony_dim_3: 256, time: 1)\nCoordinates:\n  * latitude   (latitude) float64 90.0 88.99 87.99 86.98 85.98 84.97 83.97 ...\n  * longitude  (longitude) float64 -180.0 -179.0 -178.0 -177.0 -176.0 -175.0 ...\n  * time       (time) datetime64[ns] 2014-01-04T14:20:44.939000\nDimensions without coordinates: phony_dim_2, phony_dim_3\nData variables:\n    sss        (time, latitude, longitude) float32 nan nan nan nan nan nan ...\n    palette    (time, phony_dim_2, phony_dim_3) uint8 71 0 71 73 0 73 76 0 ...\nAttributes:\n    product_name:                      Q20140012014007.L3m_7D_SCID_V5.0_SSS_1deg\n    instrument:                        Aquarius\n    title:                             Aquarius Level-3 Standard Mapped Image\n    project:                           Ocean Biology Processing Group (NASA/G...\n    platform:                          SAC-D Aquarius\n    temporal_range:                    7D\n    processing_version:                V5.0\n    date_created:                      2017-10-21T13:55:07.000Z\n    history:                           smigen par=Q20140012014007.L3m_7D_SCID...\n    l2_flag_names:                     POINTING,NAV,LANDRED,ICERED,REFL_1STOK...\n    time_coverage_start:               2014-01-01T02:20:44.939Z\n    time_coverage_end:                 2014-01-08T01:05:43.652Z\n    start_orbit_number:                13765\n    end_orbit_number:                  13867\n    map_projection:                    Equidistant Cylindrical\n    latitude_units:                    degrees_north\n    longitude_units:                   degrees_east\n    northernmost_latitude:             90.0\n    southernmost_latitude:             -90.0\n    westernmost_longitude:             -180.0\n    easternmost_longitude:             180.0\n    geospatial_lat_max:                90.0\n    geospatial_lat_min:                -90.0\n    geospatial_lon_max:                180.0\n    geospatial_lon_min:                -180.0\n    grid_mapping_name:                 latitude_longitude\n    latitude_step:                     1.0\n    longitude_step:                    1.0\n    sw_point_latitude:                 -89.5\n    sw_point_longitude:                -179.5\n    geospatial_lon_resolution:         1.0\n    geospatial_lat_resolution:         1.0\n    geospatial_lat_units:              deg\n    geospatial_lon_units:              deg\n    spatialResolution:                 1.00 deg\n    data_bins:                         28393\n    number_of_lines:                   180\n    number_of_columns:                 360\n    measure:                           Mean\n    data_minimum:                      4.82436\n    data_maximum:                      38.82527\n    suggested_image_scaling_minimum:   0.0\n    suggested_image_scaling_maximum:   70.0\n    suggested_image_scaling_type:      ATAN\n    suggested_image_scaling_applied:   No\n    _lastModified:                     2017-10-21T13:55:07.000Z\n    Conventions:                       CF-1.6\n    institution:                       NASA Goddard Space Flight Center, Ocea...\n    standard_name_vocabulary:          NetCDF Climate and Forecast (CF) Metad...\n    Metadata_Conventions:              Unidata Dataset Discovery v1.0\n    naming_authority:                  gov.nasa.gsfc.sci.oceandata\n    id:                                Q20140012014007.L3b_7D_SCID_V5.0.main/...\n    license:                           http://science.nasa.gov/earth-science/...\n    creator_name:                      NASA/GSFC/OBPG\n    publisher_name:                    NASA/GSFC/OBPG\n    creator_email:                     data@oceancolor.gsfc.nasa.gov\n    publisher_email:                   data@oceancolor.gsfc.nasa.gov\n    creator_url:                       http://oceandata.sci.gsfc.nasa.gov\n    publisher_url:                     http://oceandata.sci.gsfc.nasa.gov\n    processing_level:                  L3 Mapped\n    cdm_data_type:                     grid\n    identifier_product_doi_authority:  http://dx.doi.org\n    identifier_product_doi:            http://dx.doi.org\n    keywords:                          SURFACE SALINITY, SALINITY, AQUARIUS, ...\n    keywords_vocabulary:               NASA Global Change Master Directory (G...\n    software_name:                     smigen\n    software_version:                  5.20\n    source:                            Q20140012014007.L3b_7D_SCID_V5.0.main"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-07-25T20:53:57.085927Z",
          "start_time": "2018-07-25T20:53:57.052019Z"
        }
      },
      "cell_type": "markdown",
      "source": "### Sort by latitude\n\nLet's try plotting now."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:09.655157Z",
          "end_time": "2018-07-25T21:17:10.159590Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "dsnew.sss.plot()",
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 12,
          "data": {
            "text/plain": "<matplotlib.collections.QuadMesh at 0x7f55da3ebb38>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 2 Axes>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Much better! Let's zoom in on the Northern Hemisphere."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:10.161798Z",
          "end_time": "2018-07-25T21:17:10.452222Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "dsnew.sss.sel(longitude=slice(70, 90), latitude=slice(0, 24)).plot()",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "cannot do a non-empty take from an empty axes.",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-13-4ea91d47f328>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdsnew\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlongitude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m70\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m90\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlatitude\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mslice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m24\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\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~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m    467\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    468\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\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--> 469\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_da\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[0m\n\u001b[0m\u001b[1;32m    470\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    471\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mfunctools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwraps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(darray, row, col, col_wrap, ax, hue, rtol, subplot_kws, **kwargs)\u001b[0m\n\u001b[1;32m    183\u001b[0m     \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'ax'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 185\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mplotfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdarray\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[0m\n\u001b[0m\u001b[1;32m    186\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    187\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36mnewplotfunc\u001b[0;34m(darray, x, y, figsize, size, aspect, ax, row, col, col_wrap, xincrease, yincrease, add_colorbar, add_labels, vmin, vmax, cmap, center, robust, extend, levels, infer_intervals, colors, subplot_kws, cbar_ax, cbar_kwargs, xscale, yscale, xticks, yticks, xlim, ylim, **kwargs)\u001b[0m\n\u001b[1;32m    749\u001b[0m                              \u001b[0mvmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap_params\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'vmin'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    750\u001b[0m                              \u001b[0mvmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap_params\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'vmax'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 751\u001b[0;31m                              **kwargs)\n\u001b[0m\u001b[1;32m    752\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    753\u001b[0m         \u001b[0;31m# Label the plot with metadata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36mpcolormesh\u001b[0;34m(x, y, z, ax, infer_intervals, **kwargs)\u001b[0m\n\u001b[1;32m    980\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    981\u001b[0m             \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_infer_interval_breaks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck_monotonic\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 982\u001b[0;31m             \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_infer_interval_breaks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck_monotonic\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    983\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    984\u001b[0m             \u001b[0;31m# we have to infer the intervals on both axes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36m_infer_interval_breaks\u001b[0;34m(coord, axis, check_monotonic)\u001b[0m\n\u001b[1;32m    951\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mdeltas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    952\u001b[0m         \u001b[0mdeltas\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 953\u001b[0;31m     \u001b[0mfirst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoord\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeltas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    954\u001b[0m     \u001b[0mlast\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoord\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeltas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    955\u001b[0m     trim_last = tuple(slice(None, -1) if n == axis else slice(None)\n",
            "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36mtake\u001b[0;34m(a, indices, axis, out, mode)\u001b[0m\n\u001b[1;32m    157\u001b[0m            [5, 7]])\n\u001b[1;32m    158\u001b[0m     \"\"\"\n\u001b[0;32m--> 159\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_wrapfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'take'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindices\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    160\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36m_wrapfunc\u001b[0;34m(obj, method, *args, **kwds)\u001b[0m\n\u001b[1;32m     50\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_wrapfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\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[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 52\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m)\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[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     54\u001b[0m     \u001b[0;31m# An AttributeError occurs if the object does not have\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mIndexError\u001b[0m: cannot do a non-empty take from an empty axes."
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Huh? What happened?"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:19.954885Z",
          "end_time": "2018-07-25T21:17:20.221758Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "(dsnew.sss\n .sel(latitude=slice(-20, 20), \n      longitude=slice(50, 120))\n .plot(robust=True))",
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "cannot do a non-empty take from an empty axes.",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-14-9d73d3061336>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m  .sel(latitude=slice(-20, 20), \n\u001b[1;32m      3\u001b[0m       longitude=slice(50, 120))\n\u001b[0;32m----> 4\u001b[0;31m  .plot(robust=True))\n\u001b[0m",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m    467\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    468\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\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--> 469\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_da\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[0m\n\u001b[0m\u001b[1;32m    470\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    471\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mfunctools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwraps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36mplot\u001b[0;34m(darray, row, col, col_wrap, ax, hue, rtol, subplot_kws, **kwargs)\u001b[0m\n\u001b[1;32m    183\u001b[0m     \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'ax'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    184\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 185\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mplotfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdarray\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[0m\n\u001b[0m\u001b[1;32m    186\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    187\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36mnewplotfunc\u001b[0;34m(darray, x, y, figsize, size, aspect, ax, row, col, col_wrap, xincrease, yincrease, add_colorbar, add_labels, vmin, vmax, cmap, center, robust, extend, levels, infer_intervals, colors, subplot_kws, cbar_ax, cbar_kwargs, xscale, yscale, xticks, yticks, xlim, ylim, **kwargs)\u001b[0m\n\u001b[1;32m    749\u001b[0m                              \u001b[0mvmin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap_params\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'vmin'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    750\u001b[0m                              \u001b[0mvmax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap_params\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'vmax'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 751\u001b[0;31m                              **kwargs)\n\u001b[0m\u001b[1;32m    752\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    753\u001b[0m         \u001b[0;31m# Label the plot with metadata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36mpcolormesh\u001b[0;34m(x, y, z, ax, infer_intervals, **kwargs)\u001b[0m\n\u001b[1;32m    980\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    981\u001b[0m             \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_infer_interval_breaks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck_monotonic\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 982\u001b[0;31m             \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_infer_interval_breaks\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcheck_monotonic\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    983\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    984\u001b[0m             \u001b[0;31m# we have to infer the intervals on both axes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/work/python/xarray/xarray/plot/plot.py\u001b[0m in \u001b[0;36m_infer_interval_breaks\u001b[0;34m(coord, axis, check_monotonic)\u001b[0m\n\u001b[1;32m    951\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mdeltas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    952\u001b[0m         \u001b[0mdeltas\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 953\u001b[0;31m     \u001b[0mfirst\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoord\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeltas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    954\u001b[0m     \u001b[0mlast\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoord\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtake\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdeltas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    955\u001b[0m     trim_last = tuple(slice(None, -1) if n == axis else slice(None)\n",
            "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36mtake\u001b[0;34m(a, indices, axis, out, mode)\u001b[0m\n\u001b[1;32m    157\u001b[0m            [5, 7]])\n\u001b[1;32m    158\u001b[0m     \"\"\"\n\u001b[0;32m--> 159\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_wrapfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'take'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindices\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    160\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py\u001b[0m in \u001b[0;36m_wrapfunc\u001b[0;34m(obj, method, *args, **kwds)\u001b[0m\n\u001b[1;32m     50\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_wrapfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\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[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 52\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m)\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[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     53\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     54\u001b[0m     \u001b[0;31m# An AttributeError occurs if the object does not have\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mIndexError\u001b[0m: cannot do a non-empty take from an empty axes."
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 1 Axes>",
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "ooops, slicing doesn't work because the latitude co-ordinate is decreasing. So this works but is counter-intuitive."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:24.961342Z",
          "end_time": "2018-07-25T21:17:25.329916Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "(dsnew.sss\n .sel(latitude=slice(20, -20),  # note slice arguments in decreasing order\n      longitude=slice(50, 120))\n .plot(robust=True))",
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 15,
          "data": {
            "text/plain": "<matplotlib.collections.QuadMesh at 0x7f55da022b70>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 2 Axes>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Fixed by `Dataset.sortby`"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:56.847749Z",
          "end_time": "2018-07-25T21:17:57.212388Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "dsnew = dsnew.sortby('latitude')\n\n(dsnew.sss\n .sel(latitude=slice(-20, 20),  # note slice arguments in increasing order\n      longitude=slice(50, 120))\n .plot(robust=True))",
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 21,
          "data": {
            "text/plain": "<matplotlib.collections.QuadMesh at 0x7f55ac0d6fd0>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 2 Axes>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "### Adding metadata\n\nLet's add a little metadata to get nicely labelled plots."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:25.799996Z",
          "end_time": "2018-07-25T21:17:26.316329Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "dsnew.latitude.attrs['units'] = 'degrees_north'\ndsnew.longitude.attrs['units'] = 'degrees_east'\ndsnew.sss.attrs['long_name'] = 'Sea surface salinity'\n\ndsnew.sss.plot()",
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 17,
          "data": {
            "text/plain": "<matplotlib.collections.QuadMesh at 0x7f55da1027b8>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 2 Axes>",
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2018-07-25T21:01:03.671908Z",
          "start_time": "2018-07-25T21:01:03.629770Z"
        }
      },
      "cell_type": "markdown",
      "source": "## Fixing and combining using mfdataset\n\nLet's wrap all the above in a preprocessing function `preprocess` and pass that to `open_mfdataset`"
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:26.318399Z",
          "end_time": "2018-07-25T21:17:26.652193Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "def preprocess(ds):\n\n        dsnew = ds.copy()\n        dsnew['latitude'] = xr.DataArray(np.linspace(90, -90, 180),\n                                         dims=['phony_dim_0'])\n        dsnew['longitude'] = xr.DataArray(np.linspace(-180, 180, 360),\n                                          dims=['phony_dim_1'])\n        dsnew = (dsnew.rename({'l3m_data': 'sss',\n                               'phony_dim_0': 'latitude',\n                               'phony_dim_1': 'longitude'})\n                 .set_coords(['latitude', 'longitude'])\n                 .drop('palette'))\n\n        dsnew['time'] = (pd.to_datetime(dsnew.attrs['time_coverage_start'])\n                         + np.timedelta64(3, 'D') + np.timedelta64(12, 'h'))\n        dsnew = dsnew.expand_dims('time').set_coords('time')\n\n        return dsnew\n\naq = xr.open_mfdataset('/home/deepak/datasets/aquarius/combined/*.nc',\n                       autoclose=True,\n                       preprocess=preprocess)\n\n# do the following here to be a little efficient.\naq['latitude'].attrs['units'] = 'degrees_east'\naq['longitude'].attrs['units'] = 'degrees_north'\naq.sss.attrs['long_name'] = 'Sea surface salinity'\n\naq = aq.sortby('latitude')\n\naq",
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 18,
          "data": {
            "text/plain": "<xarray.Dataset>\nDimensions:    (latitude: 180, longitude: 360, time: 53)\nCoordinates:\n  * latitude   (latitude) float64 -90.0 -88.99 -87.99 -86.98 -85.98 -84.97 ...\n  * longitude  (longitude) float64 -180.0 -179.0 -178.0 -177.0 -176.0 -175.0 ...\n  * time       (time) datetime64[ns] 2014-01-04T14:20:44.939000 ...\nData variables:\n    sss        (time, latitude, longitude) float32 dask.array<shape=(53, 180, 360), chunksize=(1, 180, 360)>\nAttributes:\n    product_name:                      Q20140012014007.L3m_7D_SCID_V5.0_SSS_1deg\n    instrument:                        Aquarius\n    title:                             Aquarius Level-3 Standard Mapped Image\n    project:                           Ocean Biology Processing Group (NASA/G...\n    platform:                          SAC-D Aquarius\n    temporal_range:                    7D\n    processing_version:                V5.0\n    date_created:                      2017-10-21T13:55:07.000Z\n    history:                           smigen par=Q20140012014007.L3m_7D_SCID...\n    l2_flag_names:                     POINTING,NAV,LANDRED,ICERED,REFL_1STOK...\n    time_coverage_start:               2014-01-01T02:20:44.939Z\n    time_coverage_end:                 2014-01-08T01:05:43.652Z\n    start_orbit_number:                13765\n    end_orbit_number:                  13867\n    map_projection:                    Equidistant Cylindrical\n    latitude_units:                    degrees_north\n    longitude_units:                   degrees_east\n    northernmost_latitude:             90.0\n    southernmost_latitude:             -90.0\n    westernmost_longitude:             -180.0\n    easternmost_longitude:             180.0\n    geospatial_lat_max:                90.0\n    geospatial_lat_min:                -90.0\n    geospatial_lon_max:                180.0\n    geospatial_lon_min:                -180.0\n    grid_mapping_name:                 latitude_longitude\n    latitude_step:                     1.0\n    longitude_step:                    1.0\n    sw_point_latitude:                 -89.5\n    sw_point_longitude:                -179.5\n    geospatial_lon_resolution:         1.0\n    geospatial_lat_resolution:         1.0\n    geospatial_lat_units:              deg\n    geospatial_lon_units:              deg\n    spatialResolution:                 1.00 deg\n    data_bins:                         28393\n    number_of_lines:                   180\n    number_of_columns:                 360\n    measure:                           Mean\n    data_minimum:                      4.82436\n    data_maximum:                      38.82527\n    suggested_image_scaling_minimum:   0.0\n    suggested_image_scaling_maximum:   70.0\n    suggested_image_scaling_type:      ATAN\n    suggested_image_scaling_applied:   No\n    _lastModified:                     2017-10-21T13:55:07.000Z\n    Conventions:                       CF-1.6\n    institution:                       NASA Goddard Space Flight Center, Ocea...\n    standard_name_vocabulary:          NetCDF Climate and Forecast (CF) Metad...\n    Metadata_Conventions:              Unidata Dataset Discovery v1.0\n    naming_authority:                  gov.nasa.gsfc.sci.oceandata\n    id:                                Q20140012014007.L3b_7D_SCID_V5.0.main/...\n    license:                           http://science.nasa.gov/earth-science/...\n    creator_name:                      NASA/GSFC/OBPG\n    publisher_name:                    NASA/GSFC/OBPG\n    creator_email:                     data@oceancolor.gsfc.nasa.gov\n    publisher_email:                   data@oceancolor.gsfc.nasa.gov\n    creator_url:                       http://oceandata.sci.gsfc.nasa.gov\n    publisher_url:                     http://oceandata.sci.gsfc.nasa.gov\n    processing_level:                  L3 Mapped\n    cdm_data_type:                     grid\n    identifier_product_doi_authority:  http://dx.doi.org\n    identifier_product_doi:            http://dx.doi.org\n    keywords:                          SURFACE SALINITY, SALINITY, AQUARIUS, ...\n    keywords_vocabulary:               NASA Global Change Master Directory (G...\n    software_name:                     smigen\n    software_version:                  5.20\n    source:                            Q20140012014007.L3b_7D_SCID_V5.0.main"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "Phew, the `repr` above looks sensible and slicing works as expected."
    },
    {
      "metadata": {
        "ExecuteTime": {
          "start_time": "2018-07-25T21:17:26.653537Z",
          "end_time": "2018-07-25T21:17:27.171315Z"
        },
        "trusted": true
      },
      "cell_type": "code",
      "source": "(aq.sss\n .isel(time=10)\n .sel(latitude=slice(-20, 20), \n      longitude=slice(50, 120))\n .plot(robust=True))",
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 19,
          "data": {
            "text/plain": "<matplotlib.collections.QuadMesh at 0x7f55da4c9a90>"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": "<Figure size 780x660 with 2 Axes>",
            "image/png": 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\n"
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