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    "# Advanced Xarray\n",
    "\n",
    "\n",
    "*This material is adapted from the [Earth and Environmental Data Science](https://earth-env-data-science.github.io/intro.html), from Ryan Abernathey (Columbia University)*.\n",
    "\n",
    "\n",
    "In this notebook, we cover some more advanced aspects of `Xarray`.\n",
    "\n",
    "## Groupby\n",
    "\n",
    "`Xarray` copies Pandas' very useful groupby functionality, enabling the \"split / apply / combine\" workflow on xarray DataArrays and Datasets. In the first part of the notebook, we will learn to use groupby by analyzing sea-surface temperature data."
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    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "#%config InlineBackend.figure_format = 'retina'\n",
    "plt.ion()  # To trigger the interactive inline mode\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (6,5)"
   ]
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   "source": [
    "First we load a dataset. We will use the [NOAA Extended Reconstructed Sea Surface Temperature (ERSST) v5](https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v5) product, a widely used and trusted gridded compilation of of historical data going back to 1854.\n",
    "\n",
    "Since the data is provided via an [OPeNDAP](https://en.wikipedia.org/wiki/OPeNDAP) server, we can load it directly without downloading anything:"
   ]
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   "cell_type": "code",
   "execution_count": 41,
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan\n",
       "Attributes: (12/38)\n",
       "    climatology:                     Climatology is based on 1971-2000 SST, X...\n",
       "    description:                     In situ data: ICOADS2.5 before 2007 and ...\n",
       "    keywords_vocabulary:             NASA Global Change Master Directory (GCM...\n",
       "    keywords:                        Earth Science &gt; Oceans &gt; Ocean Temperatu...\n",
       "    instrument:                      Conventional thermometers\n",
       "    source_comment:                  SSTs were observed by conventional therm...\n",
       "    ...                              ...\n",
       "    license:                         No constraints on data access or use\n",
       "    comment:                         SSTs were observed by conventional therm...\n",
       "    summary:                         ERSST.v5 is developed based on v4 after ...\n",
       "    dataset_title:                   NOAA Extended Reconstructed SST V5\n",
       "    data_modified:                   2021-03-07\n",
       "    DODS_EXTRA.Unlimited_Dimension:  time</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0099063b-2cb0-474b-8c37-f90619a845da' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0099063b-2cb0-474b-8c37-f90619a845da' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 708</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2cd95683-d322-4969-ae27-58354e1e528a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2cd95683-d322-4969-ae27-58354e1e528a' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-7bc9f3b7-c47a-4b3c-a9ee-6c3b7dcaa490' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bc9f3b7-c47a-4b3c-a9ee-6c3b7dcaa490' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ea66583-9841-4e40-baa7-d9d7c3117aff' class='xr-var-data-in' type='checkbox'><label for='data-6ea66583-9841-4e40-baa7-d9d7c3117aff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-135ec482-4183-4fe5-b1dc-5b87c3c3e452' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-135ec482-4183-4fe5-b1dc-5b87c3c3e452' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-725959fa-7b05-47a2-9082-519e57d20abb' class='xr-var-data-in' type='checkbox'><label for='data-725959fa-7b05-47a2-9082-519e57d20abb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-c1165c7a-f34d-43aa-83b5-996d4c254add' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1165c7a-f34d-43aa-83b5-996d4c254add' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9c137ed-0d25-4275-8451-1c8f3147ccb5' class='xr-var-data-in' type='checkbox'><label for='data-c9c137ed-0d25-4275-8451-1c8f3147ccb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-518c7f45-16ab-498d-be70-312a59bfa9ea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-518c7f45-16ab-498d-be70-312a59bfa9ea' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.8 -1.8 -1.8 -1.8 ... nan nan nan</div><input id='attrs-042ce466-2dea-481b-9503-6684e5a6acb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-042ce466-2dea-481b-9503-6684e5a6acb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91d513aa-a80b-4afe-85fc-86346aa6bca8' class='xr-var-data-in' type='checkbox'><label for='data-91d513aa-a80b-4afe-85fc-86346aa6bca8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8     42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8 45. ]</dd><dt><span>_ChunkSizes :</span></dt><dd>[  1  89 180]</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-59c8a6db-c436-4993-9421-8ac1370271eb' class='xr-section-summary-in' type='checkbox'  ><label for='section-59c8a6db-c436-4993-9421-8ac1370271eb' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>climatology :</span></dt><dd>Climatology is based on 1971-2000 SST, Xue, Y., T. M. Smith, and R. W. Reynolds, 2003: Interdecadal changes of 30-yr SST normals during 1871.2000. Journal of Climate, 16, 1601-1612.</dd><dt><span>description :</span></dt><dd>In situ data: ICOADS2.5 before 2007 and NCEP in situ data from 2008 to present. Ice data: HadISST ice before 2010 and NCEP ice after 2010.</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>keywords :</span></dt><dd>Earth Science &gt; Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature &gt;</dd><dt><span>instrument :</span></dt><dd>Conventional thermometers</dd><dt><span>source_comment :</span></dt><dd>SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets) or Engine Room Intaker</dd><dt><span>geospatial_lon_min :</span></dt><dd>-1.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>359.0</dd><dt><span>geospatial_laty_max :</span></dt><dd>89.0</dd><dt><span>geospatial_laty_min :</span></dt><dd>-89.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>89.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-89.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>project :</span></dt><dd>NOAA Extended Reconstructed Sea Surface Temperature (ERSST)</dd><dt><span>original_publisher_url :</span></dt><dd>http://www.ncdc.noaa.gov</dd><dt><span>References :</span></dt><dd>https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v5 at NCEI and http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.ersst.v5.html</dd><dt><span>source :</span></dt><dd>In situ data: ICOADS R3.0 before 2015, NCEP in situ GTS from 2016 to present, and Argo SST from 1999 to present. Ice data: HadISST2 ice before 2015, and NCEP ice after 2015</dd><dt><span>title :</span></dt><dd>NOAA ERSSTv5 (in situ only)</dd><dt><span>history :</span></dt><dd>created 07/2017 by PSD data using NCEI&#x27;s ERSST V5 NetCDF values</dd><dt><span>institution :</span></dt><dd>This version written at NOAA/ESRL PSD: obtained from NOAA/NESDIS/National Centers for Environmental Information and time aggregated. Original Full Source: NOAA/NESDIS/NCEI/CCOG</dd><dt><span>citation :</span></dt><dd>Huang et al, 2017: Extended Reconstructed Sea Surface Temperatures Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons. Journal of Climate, https://doi.org/10.1175/JCLI-D-16-0836.1</dd><dt><span>platform :</span></dt><dd>Ship and Buoy SSTs from ICOADS R3.0 and NCEP GTS</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table (v40, 25 January 2017)</dd><dt><span>processing_level :</span></dt><dd>NOAA Level 4</dd><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>metadata_link :</span></dt><dd>:metadata_link = https://doi.org/10.7289/V5T72FNM (original format)</dd><dt><span>creator_name :</span></dt><dd>Boyin Huang (original)</dd><dt><span>date_created :</span></dt><dd>2017-06-30T12:18:00Z (original)</dd><dt><span>product_version :</span></dt><dd>Version 5</dd><dt><span>creator_url_original :</span></dt><dd>https://www.ncei.noaa.gov</dd><dt><span>license :</span></dt><dd>No constraints on data access or use</dd><dt><span>comment :</span></dt><dd>SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets), Engine Room Intakers, or floats and drifters</dd><dt><span>summary :</span></dt><dd>ERSST.v5 is developed based on v4 after revisions of 8 parameters using updated data sets and advanced knowledge of ERSST analysis</dd><dt><span>dataset_title :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>data_modified :</span></dt><dd>2021-03-07</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan\n",
       "Attributes: (12/38)\n",
       "    climatology:                     Climatology is based on 1971-2000 SST, X...\n",
       "    description:                     In situ data: ICOADS2.5 before 2007 and ...\n",
       "    keywords_vocabulary:             NASA Global Change Master Directory (GCM...\n",
       "    keywords:                        Earth Science > Oceans > Ocean Temperatu...\n",
       "    instrument:                      Conventional thermometers\n",
       "    source_comment:                  SSTs were observed by conventional therm...\n",
       "    ...                              ...\n",
       "    license:                         No constraints on data access or use\n",
       "    comment:                         SSTs were observed by conventional therm...\n",
       "    summary:                         ERSST.v5 is developed based on v4 after ...\n",
       "    dataset_title:                   NOAA Extended Reconstructed SST V5\n",
       "    data_modified:                   2021-03-07\n",
       "    DODS_EXTRA.Unlimited_Dimension:  time"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = 'http://www.esrl.noaa.gov/psd/thredds/dodsC/Datasets/noaa.ersst.v5/sst.mnmean.nc'\n",
    "ds = xr.open_dataset(url, drop_variables=['time_bnds'])\n",
    "ds = ds.sel(time=slice('1960', '2018')).load()\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's do some basic visualizations of the data, just to make sure it looks reasonable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fba506a8d60>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 332,
       "width": 398
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.sst[0].plot(vmin=-2, vmax=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that xarray correctly parsed the time index, resulting in a Pandas datetime index on the time dimension."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;time&#x27; (time: 708)&gt;\n",
       "array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "Attributes:\n",
       "    long_name:        Time\n",
       "    delta_t:          0000-01-00 00:00:00\n",
       "    avg_period:       0000-01-00 00:00:00\n",
       "    prev_avg_period:  0000-00-07 00:00:00\n",
       "    standard_name:    time\n",
       "    axis:             T\n",
       "    actual_range:     [19723. 80750.]\n",
       "    _ChunkSizes:      1</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'time'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 708</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-7c135edd-5f7d-4aed-b553-a5177afcec3d' class='xr-array-in' type='checkbox' checked><label for='section-7c135edd-5f7d-4aed-b553-a5177afcec3d' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1960-01-01 1960-02-01 1960-03-01 ... 2018-10-01 2018-11-01 2018-12-01</span></div><div class='xr-array-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-0906bedd-7a5e-46c5-85c8-c9db68185772' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0906bedd-7a5e-46c5-85c8-c9db68185772' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-c123d216-0886-42ce-a997-a4ce05d6ee3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c123d216-0886-42ce-a997-a4ce05d6ee3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c97a341a-93ab-4a48-8dd9-c5240c42f75d' class='xr-var-data-in' type='checkbox'><label for='data-c97a341a-93ab-4a48-8dd9-c5240c42f75d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5d2d2c6d-be53-4a51-90d7-fffe4bca7b63' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5d2d2c6d-be53-4a51-90d7-fffe4bca7b63' class='xr-section-summary' >Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'time' (time: 708)>\n",
       "array(['1960-01-01T00:00:00.000000000', '1960-02-01T00:00:00.000000000',\n",
       "       '1960-03-01T00:00:00.000000000', ..., '2018-10-01T00:00:00.000000000',\n",
       "       '2018-11-01T00:00:00.000000000', '2018-12-01T00:00:00.000000000'],\n",
       "      dtype='datetime64[ns]')\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "Attributes:\n",
       "    long_name:        Time\n",
       "    delta_t:          0000-01-00 00:00:00\n",
       "    avg_period:       0000-01-00 00:00:00\n",
       "    prev_avg_period:  0000-00-07 00:00:00\n",
       "    standard_name:    time\n",
       "    axis:             T\n",
       "    actual_range:     [19723. 80750.]\n",
       "    _ChunkSizes:      1"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fba72c02e80>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 343,
       "width": 404
      },
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds.sst.sel(lon=300, lat=50).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see from the plot, the timeseries at any one point is totally dominated by the seasonal cycle. We would like to remove this seasonal cycle (called the \"climatology\") in order to better see the long-term variaitions in temperature. We will accomplish this using **groupby**.\n",
    "\n",
    "The syntax of `Xarray`'s `groupby` is almost identical to `Pandas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": [
     "scroll-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method groupby in module xarray.core.common:\n",
      "\n",
      "groupby(group, squeeze: bool = True, restore_coord_dims: bool = None) method of xarray.core.dataset.Dataset instance\n",
      "    Returns a GroupBy object for performing grouped operations.\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    group : str, DataArray or IndexVariable\n",
      "        Array whose unique values should be used to group this array. If a\n",
      "        string, must be the name of a variable contained in this dataset.\n",
      "    squeeze : bool, optional\n",
      "        If \"group\" is a dimension of any arrays in this dataset, `squeeze`\n",
      "        controls whether the subarrays have a dimension of length 1 along\n",
      "        that dimension or if the dimension is squeezed out.\n",
      "    restore_coord_dims : bool, optional\n",
      "        If True, also restore the dimension order of multi-dimensional\n",
      "        coordinates.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    grouped\n",
      "        A `GroupBy` object patterned after `pandas.GroupBy` that can be\n",
      "        iterated over in the form of `(unique_value, grouped_array)` pairs.\n",
      "    \n",
      "    Examples\n",
      "    --------\n",
      "    Calculate daily anomalies for daily data:\n",
      "    \n",
      "    >>> da = xr.DataArray(\n",
      "    ...     np.linspace(0, 1826, num=1827),\n",
      "    ...     coords=[pd.date_range(\"1/1/2000\", \"31/12/2004\", freq=\"D\")],\n",
      "    ...     dims=\"time\",\n",
      "    ... )\n",
      "    >>> da\n",
      "    <xarray.DataArray (time: 1827)>\n",
      "    array([0.000e+00, 1.000e+00, 2.000e+00, ..., 1.824e+03, 1.825e+03,\n",
      "           1.826e+03])\n",
      "    Coordinates:\n",
      "      * time     (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2004-12-31\n",
      "    >>> da.groupby(\"time.dayofyear\") - da.groupby(\"time.dayofyear\").mean(\"time\")\n",
      "    <xarray.DataArray (time: 1827)>\n",
      "    array([-730.8, -730.8, -730.8, ...,  730.2,  730.2,  730.5])\n",
      "    Coordinates:\n",
      "      * time       (time) datetime64[ns] 2000-01-01 2000-01-02 ... 2004-12-31\n",
      "        dayofyear  (time) int64 1 2 3 4 5 6 7 8 ... 359 360 361 362 363 364 365 366\n",
      "    \n",
      "    See Also\n",
      "    --------\n",
      "    core.groupby.DataArrayGroupBy\n",
      "    core.groupby.DatasetGroupBy\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(ds.groupby)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Split Step\n",
    "\n",
    "The most important argument is `group`: this defines the unique values we will use to \"split\" the data for grouped analysis. We can pass either a `DataArray` or a name of a variable in the dataset. Lets first use a `DataArray`. Just like with `Pandas`, we can use the time index to extract specific components of dates and times. `Xarray` uses a special syntax for this `.dt`, called the `DatetimeAccessor`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xarray.core.accessor_dt.DatetimeAccessor at 0x7fba72be7c40>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.time.dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": [
     "scroll-output"
    ]
   },
   "outputs": [
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       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;month&#x27; (time: 708)&gt;\n",
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "...\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'month'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 708</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-0e0cfc9a-d5a9-4cfe-87f1-a5e549a9d1ca' class='xr-array-in' type='checkbox' checked><label for='section-0e0cfc9a-d5a9-4cfe-87f1-a5e549a9d1ca' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 ... 11 12 1 2 3 4 5 6 7 8 9 10 11 12</span></div><div class='xr-array-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "...\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></div></li><li class='xr-section-item'><input id='section-db6e7792-3012-41fd-97b7-5bf6af59adc0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-db6e7792-3012-41fd-97b7-5bf6af59adc0' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-65149401-1795-4446-8e34-50d157909d71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65149401-1795-4446-8e34-50d157909d71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3392cbce-c5c0-4db4-b334-1cf9f6b31fd8' class='xr-var-data-in' type='checkbox'><label for='data-3392cbce-c5c0-4db4-b334-1cf9f6b31fd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-84a20355-f13f-4961-8fc7-ef9f3303e64b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-84a20355-f13f-4961-8fc7-ef9f3303e64b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'month' (time: 708)>\n",
       "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "...\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.time.dt.month"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ds.time.dt.year"
   ]
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  {
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   "source": [
    "We can use these arrays in a groupby operation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetGroupBy, grouped over 'month' \n",
       "12 groups with labels 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gb = ds.groupby(ds.time.dt.month)\n",
    "gb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Xarray also offers a more concise syntax when the variable you're grouping on is already present in the dataset. This is identical to the previous line:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetGroupBy, grouped over 'month' \n",
       "12 groups with labels 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gb = ds.groupby('time.month')\n",
    "gb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that the data are split, we can manually iterate over the group. The iterator returns the key (group name) and the value (the actual dataset corresponding to that group) for each group."
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  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
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       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, time: 59)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1961-01-01 ... 2018-01-01\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan\n",
       "Attributes: (12/38)\n",
       "    climatology:                     Climatology is based on 1971-2000 SST, X...\n",
       "    description:                     In situ data: ICOADS2.5 before 2007 and ...\n",
       "    keywords_vocabulary:             NASA Global Change Master Directory (GCM...\n",
       "    keywords:                        Earth Science &gt; Oceans &gt; Ocean Temperatu...\n",
       "    instrument:                      Conventional thermometers\n",
       "    source_comment:                  SSTs were observed by conventional therm...\n",
       "    ...                              ...\n",
       "    license:                         No constraints on data access or use\n",
       "    comment:                         SSTs were observed by conventional therm...\n",
       "    summary:                         ERSST.v5 is developed based on v4 after ...\n",
       "    dataset_title:                   NOAA Extended Reconstructed SST V5\n",
       "    data_modified:                   2021-03-07\n",
       "    DODS_EXTRA.Unlimited_Dimension:  time</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0f46cad9-34a7-4d8b-8a9f-9a5536d8ea1a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0f46cad9-34a7-4d8b-8a9f-9a5536d8ea1a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 59</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ee79092a-38a1-4b4e-9084-f385c0d672da' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ee79092a-38a1-4b4e-9084-f385c0d672da' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-19a40d36-1a95-4210-a52d-1c61b92a8862' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19a40d36-1a95-4210-a52d-1c61b92a8862' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-843f6e44-fe17-4949-8a39-39080872ed99' class='xr-var-data-in' type='checkbox'><label for='data-843f6e44-fe17-4949-8a39-39080872ed99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-0d981fd7-0b3b-4843-b3b9-351e357f83cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d981fd7-0b3b-4843-b3b9-351e357f83cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f47a60f-7b47-449b-ac04-6ce6a71220d2' class='xr-var-data-in' type='checkbox'><label for='data-7f47a60f-7b47-449b-ac04-6ce6a71220d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-01-01</div><input id='attrs-6ab77b3b-42b2-4328-93aa-767ce3d12921' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ab77b3b-42b2-4328-93aa-767ce3d12921' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef1c8ae6-f599-48ae-9dc3-476512dacbd8' class='xr-var-data-in' type='checkbox'><label for='data-ef1c8ae6-f599-48ae-9dc3-476512dacbd8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1961-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1962-01-01T00:00:00.000000000&#x27;, &#x27;1963-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1964-01-01T00:00:00.000000000&#x27;, &#x27;1965-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1966-01-01T00:00:00.000000000&#x27;, &#x27;1967-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1968-01-01T00:00:00.000000000&#x27;, &#x27;1969-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1970-01-01T00:00:00.000000000&#x27;, &#x27;1971-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1972-01-01T00:00:00.000000000&#x27;, &#x27;1973-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1974-01-01T00:00:00.000000000&#x27;, &#x27;1975-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1976-01-01T00:00:00.000000000&#x27;, &#x27;1977-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1978-01-01T00:00:00.000000000&#x27;, &#x27;1979-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-01-01T00:00:00.000000000&#x27;, &#x27;1983-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1984-01-01T00:00:00.000000000&#x27;, &#x27;1985-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1986-01-01T00:00:00.000000000&#x27;, &#x27;1987-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1988-01-01T00:00:00.000000000&#x27;, &#x27;1989-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-01-01T00:00:00.000000000&#x27;, &#x27;1991-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1992-01-01T00:00:00.000000000&#x27;, &#x27;1993-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1994-01-01T00:00:00.000000000&#x27;, &#x27;1995-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1996-01-01T00:00:00.000000000&#x27;, &#x27;1997-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1998-01-01T00:00:00.000000000&#x27;, &#x27;1999-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2001-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-01-01T00:00:00.000000000&#x27;, &#x27;2003-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-01T00:00:00.000000000&#x27;, &#x27;2005-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-01-01T00:00:00.000000000&#x27;, &#x27;2007-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-01-01T00:00:00.000000000&#x27;, &#x27;2009-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-01-01T00:00:00.000000000&#x27;, &#x27;2011-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-01-01T00:00:00.000000000&#x27;, &#x27;2013-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-01-01T00:00:00.000000000&#x27;, &#x27;2015-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-01-01T00:00:00.000000000&#x27;, &#x27;2017-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-01-01T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b241840d-4b8d-4de3-98d7-61d5afda0d63' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b241840d-4b8d-4de3-98d7-61d5afda0d63' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.8 -1.8 -1.8 -1.8 ... nan nan nan</div><input id='attrs-b868505c-7062-4483-a0d1-4b1028480c4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b868505c-7062-4483-a0d1-4b1028480c4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1d9fd1e-4e8d-4c2b-9a4e-5931113da387' class='xr-var-data-in' type='checkbox'><label for='data-f1d9fd1e-4e8d-4c2b-9a4e-5931113da387' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8     42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8 45. ]</dd><dt><span>_ChunkSizes :</span></dt><dd>[  1  89 180]</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]],\n",
       "\n",
       "       [[-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        [-1.8, -1.8, -1.8, ..., -1.8, -1.8, -1.8],\n",
       "        ...,\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "        [ nan,  nan,  nan, ...,  nan,  nan,  nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ef7bc26c-497b-4a44-ba13-a2094d833663' class='xr-section-summary-in' type='checkbox'  ><label for='section-ef7bc26c-497b-4a44-ba13-a2094d833663' class='xr-section-summary' >Attributes: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>climatology :</span></dt><dd>Climatology is based on 1971-2000 SST, Xue, Y., T. M. Smith, and R. W. Reynolds, 2003: Interdecadal changes of 30-yr SST normals during 1871.2000. Journal of Climate, 16, 1601-1612.</dd><dt><span>description :</span></dt><dd>In situ data: ICOADS2.5 before 2007 and NCEP in situ data from 2008 to present. Ice data: HadISST ice before 2010 and NCEP ice after 2010.</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>keywords :</span></dt><dd>Earth Science &gt; Oceans &gt; Ocean Temperature &gt; Sea Surface Temperature &gt;</dd><dt><span>instrument :</span></dt><dd>Conventional thermometers</dd><dt><span>source_comment :</span></dt><dd>SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets) or Engine Room Intaker</dd><dt><span>geospatial_lon_min :</span></dt><dd>-1.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>359.0</dd><dt><span>geospatial_laty_max :</span></dt><dd>89.0</dd><dt><span>geospatial_laty_min :</span></dt><dd>-89.0</dd><dt><span>geospatial_lat_max :</span></dt><dd>89.0</dd><dt><span>geospatial_lat_min :</span></dt><dd>-89.0</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>project :</span></dt><dd>NOAA Extended Reconstructed Sea Surface Temperature (ERSST)</dd><dt><span>original_publisher_url :</span></dt><dd>http://www.ncdc.noaa.gov</dd><dt><span>References :</span></dt><dd>https://www.ncdc.noaa.gov/data-access/marineocean-data/extended-reconstructed-sea-surface-temperature-ersst-v5 at NCEI and http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.ersst.v5.html</dd><dt><span>source :</span></dt><dd>In situ data: ICOADS R3.0 before 2015, NCEP in situ GTS from 2016 to present, and Argo SST from 1999 to present. Ice data: HadISST2 ice before 2015, and NCEP ice after 2015</dd><dt><span>title :</span></dt><dd>NOAA ERSSTv5 (in situ only)</dd><dt><span>history :</span></dt><dd>created 07/2017 by PSD data using NCEI&#x27;s ERSST V5 NetCDF values</dd><dt><span>institution :</span></dt><dd>This version written at NOAA/ESRL PSD: obtained from NOAA/NESDIS/National Centers for Environmental Information and time aggregated. Original Full Source: NOAA/NESDIS/NCEI/CCOG</dd><dt><span>citation :</span></dt><dd>Huang et al, 2017: Extended Reconstructed Sea Surface Temperatures Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons. Journal of Climate, https://doi.org/10.1175/JCLI-D-16-0836.1</dd><dt><span>platform :</span></dt><dd>Ship and Buoy SSTs from ICOADS R3.0 and NCEP GTS</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table (v40, 25 January 2017)</dd><dt><span>processing_level :</span></dt><dd>NOAA Level 4</dd><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3</dd><dt><span>metadata_link :</span></dt><dd>:metadata_link = https://doi.org/10.7289/V5T72FNM (original format)</dd><dt><span>creator_name :</span></dt><dd>Boyin Huang (original)</dd><dt><span>date_created :</span></dt><dd>2017-06-30T12:18:00Z (original)</dd><dt><span>product_version :</span></dt><dd>Version 5</dd><dt><span>creator_url_original :</span></dt><dd>https://www.ncei.noaa.gov</dd><dt><span>license :</span></dt><dd>No constraints on data access or use</dd><dt><span>comment :</span></dt><dd>SSTs were observed by conventional thermometers in Buckets (insulated or un-insulated canvas and wooded buckets), Engine Room Intakers, or floats and drifters</dd><dt><span>summary :</span></dt><dd>ERSST.v5 is developed based on v4 after revisions of 8 parameters using updated data sets and advanced knowledge of ERSST analysis</dd><dt><span>dataset_title :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>data_modified :</span></dt><dd>2021-03-07</dd><dt><span>DODS_EXTRA.Unlimited_Dimension :</span></dt><dd>time</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, time: 59)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1961-01-01 ... 2018-01-01\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan\n",
       "Attributes: (12/38)\n",
       "    climatology:                     Climatology is based on 1971-2000 SST, X...\n",
       "    description:                     In situ data: ICOADS2.5 before 2007 and ...\n",
       "    keywords_vocabulary:             NASA Global Change Master Directory (GCM...\n",
       "    keywords:                        Earth Science > Oceans > Ocean Temperatu...\n",
       "    instrument:                      Conventional thermometers\n",
       "    source_comment:                  SSTs were observed by conventional therm...\n",
       "    ...                              ...\n",
       "    license:                         No constraints on data access or use\n",
       "    comment:                         SSTs were observed by conventional therm...\n",
       "    summary:                         ERSST.v5 is developed based on v4 after ...\n",
       "    dataset_title:                   NOAA Extended Reconstructed SST V5\n",
       "    data_modified:                   2021-03-07\n",
       "    DODS_EXTRA.Unlimited_Dimension:  time"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for group_name, group_ds in gb:\n",
    "    # stop iterating after the first loop\n",
    "    break \n",
    "print(group_name)\n",
    "group_ds"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "### Apply & Combine\n",
    "\n",
    "Now that we have groups defined, it's time to \"apply\" a calculation to the group. Like in Pandas, these calculations can either be:\n",
    "- _aggregation_: reduces the size of the group\n",
    "- _transformation_: preserves the group's full size\n",
    "\n",
    "At then end of the apply step, xarray will automatically combine the aggregated / transformed groups back into a single object.\n",
    "\n",
    "The most fundamental way to apply is with the `.apply` method."
   ]
  },
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   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method apply in module xarray.core.groupby:\n",
      "\n",
      "apply(func, args=(), shortcut=None, **kwargs) method of xarray.core.groupby.DatasetGroupBy instance\n",
      "    Backward compatible implementation of ``map``\n",
      "    \n",
      "    See Also\n",
      "    --------\n",
      "    DatasetGroupBy.map\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(gb.apply)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Aggregations\n",
    "\n",
    "`.apply` accepts as its argument a function. We can pass an existing function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
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       "Data variables:\n",
       "    sst      (month) float32 13.66 13.77 13.76 13.68 ... 13.98 13.69 13.51 13.53</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ec8617c3-6fc5-4530-a099-546da30a62f9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ec8617c3-6fc5-4530-a099-546da30a62f9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>month</span>: 12</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c70a2050-e7ca-4302-a542-5c9470435c92' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c70a2050-e7ca-4302-a542-5c9470435c92' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-97556d11-b6dd-4734-b736-d54730d8167a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-97556d11-b6dd-4734-b736-d54730d8167a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3789fa73-b31b-4291-8195-cfdd17860787' class='xr-var-data-in' type='checkbox'><label for='data-3789fa73-b31b-4291-8195-cfdd17860787' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8e462eb1-7ada-4042-821e-b7df23fc54f7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8e462eb1-7ada-4042-821e-b7df23fc54f7' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.66 13.77 13.76 ... 13.51 13.53</div><input id='attrs-3f36c38b-f85d-4aac-81f7-c2482fbc7697' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3f36c38b-f85d-4aac-81f7-c2482fbc7697' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c16e21e0-55ba-48ec-87ce-6b92594493df' class='xr-var-data-in' type='checkbox'><label for='data-c16e21e0-55ba-48ec-87ce-6b92594493df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([13.659641, 13.768647, 13.76488 , 13.684034, 13.642146, 13.713043,\n",
       "       13.921847, 14.093956, 13.982147, 13.691116, 13.506494, 13.529454],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e0df630a-d336-4bd3-8456-fa7b28602098' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e0df630a-d336-4bd3-8456-fa7b28602098' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (month: 12)\n",
       "Coordinates:\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (month) float32 13.66 13.77 13.76 13.68 ... 13.98 13.69 13.51 13.53"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gb.apply(np.mean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because we specified no extra arguments (like `axis`) the function was applied over all space and time dimensions. This is not what we wanted. Instead, we could define a custom function. This function takes a single argument--the group dataset--and returns a new dataset to be combined:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, month: 12)\n",
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       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (month, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4382f4f4-9c48-46fe-b931-e6f31cc2c4e4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4382f4f4-9c48-46fe-b931-e6f31cc2c4e4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>month</span>: 12</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1da55536-ce7b-44dc-8402-16c54c789597' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1da55536-ce7b-44dc-8402-16c54c789597' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-027169e7-c9ba-459e-97ba-35889ff8609f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-027169e7-c9ba-459e-97ba-35889ff8609f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1ec33668-9824-4685-850f-9bdeb7ff0325' class='xr-var-data-in' type='checkbox'><label for='data-1ec33668-9824-4685-850f-9bdeb7ff0325' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-16bccbb0-10c8-46ac-ae7b-7853e0048f74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16bccbb0-10c8-46ac-ae7b-7853e0048f74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5856dc89-2361-4bff-bae6-08995c672a74' class='xr-var-data-in' type='checkbox'><label for='data-5856dc89-2361-4bff-bae6-08995c672a74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-38051667-f000-4f38-8b54-74595377a31b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38051667-f000-4f38-8b54-74595377a31b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-052eb5b9-d1e1-4d3e-902e-25854b0e87f1' class='xr-var-data-in' type='checkbox'><label for='data-052eb5b9-d1e1-4d3e-902e-25854b0e87f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-154b3042-770d-4602-8285-6c5c6523e431' class='xr-section-summary-in' type='checkbox'  checked><label for='section-154b3042-770d-4602-8285-6c5c6523e431' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(month, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.8 -1.8 -1.8 -1.8 ... nan nan nan</div><input id='attrs-1385119f-1356-4dcb-b981-f5a5ffcb5750' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1385119f-1356-4dcb-b981-f5a5ffcb5750' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62d50677-0ff6-49ec-8dcf-6ae412316614' class='xr-var-data-in' type='checkbox'><label for='data-62d50677-0ff6-49ec-8dcf-6ae412316614' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        ...,\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan]],\n",
       "\n",
       "       [[-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "...\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan]],\n",
       "\n",
       "       [[-1.7995025, -1.7995973, -1.7998415, ..., -1.7997988,\n",
       "         -1.7996519, -1.7995045],\n",
       "        [-1.7995876, -1.7997634, -1.8000009, ..., -1.8000009,\n",
       "         -1.7998358, -1.7996247],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        ...,\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b1ae0890-5fe8-4bdd-b659-2f57e66af5c6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b1ae0890-5fe8-4bdd-b659-2f57e66af5c6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, month: 12)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (month, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def time_mean(a):\n",
    "    return a.mean(dim='time')\n",
    "\n",
    "gb.apply(time_mean)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Like Pandas, xarray's groupby object has many built-in aggregation operations (e.g. `mean`, `min`, `max`, `std`, etc):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, month: 12)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (month, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b2692854-c19a-47c1-86f8-9c353e9d9ac6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b2692854-c19a-47c1-86f8-9c353e9d9ac6' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>month</span>: 12</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a43950ea-dc12-4ecb-9f5d-8093386530ef' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a43950ea-dc12-4ecb-9f5d-8093386530ef' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-7fbf693a-cd54-4842-9537-1a73c849efb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fbf693a-cd54-4842-9537-1a73c849efb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad4e4a85-a59b-4aa7-a326-fe37a4965a82' class='xr-var-data-in' type='checkbox'><label for='data-ad4e4a85-a59b-4aa7-a326-fe37a4965a82' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-69237a88-5450-4b35-ae0a-5f8825894c2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69237a88-5450-4b35-ae0a-5f8825894c2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29f6c762-76ef-49e2-a805-319bc430b4c7' class='xr-var-data-in' type='checkbox'><label for='data-29f6c762-76ef-49e2-a805-319bc430b4c7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-3ef2b471-a4c8-4f8d-bd5d-84e917106c0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3ef2b471-a4c8-4f8d-bd5d-84e917106c0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8396e26d-2f8c-405f-8b34-571def81c9e9' class='xr-var-data-in' type='checkbox'><label for='data-8396e26d-2f8c-405f-8b34-571def81c9e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9ac59941-60e2-46a2-8ef5-b51c4c840c7b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9ac59941-60e2-46a2-8ef5-b51c4c840c7b' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(month, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.8 -1.8 -1.8 -1.8 ... nan nan nan</div><input id='attrs-11e124dc-cca8-43e8-8b6c-79272b1165cf' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11e124dc-cca8-43e8-8b6c-79272b1165cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2bd65bc4-d562-4e38-91ca-3c58d30e4ec4' class='xr-var-data-in' type='checkbox'><label for='data-2bd65bc4-d562-4e38-91ca-3c58d30e4ec4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        ...,\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan]],\n",
       "\n",
       "       [[-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "...\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan]],\n",
       "\n",
       "       [[-1.7995025, -1.7995973, -1.7998415, ..., -1.7997988,\n",
       "         -1.7996519, -1.7995045],\n",
       "        [-1.7995876, -1.7997634, -1.8000009, ..., -1.8000009,\n",
       "         -1.7998358, -1.7996247],\n",
       "        [-1.8000009, -1.8000009, -1.8000009, ..., -1.8000009,\n",
       "         -1.8000009, -1.8000009],\n",
       "        ...,\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan],\n",
       "        [       nan,        nan,        nan, ...,        nan,\n",
       "                nan,        nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63e95180-e696-4f45-b056-72ae9df2b17e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-63e95180-e696-4f45-b056-72ae9df2b17e' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, month: 12)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (month, lat, lon) float32 -1.8 -1.8 -1.8 -1.8 ... nan nan nan nan"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# this does the same thing as the previous cell\n",
    "ds_mm = gb.mean(dim='time')\n",
    "ds_mm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we did what we wanted to do: calculate the climatology at every point in the dataset. Let's look at the data a bit.\n",
    "\n",
    "_Climatlogy at a specific point in the North Atlantic_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fba9083d6a0>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_mm.sst.sel(lon=300, lat=50).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_Zonal Mean Climatolgoy_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fba904a12b0>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 319,
       "width": 403
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_mm.sst.mean(dim='lon').transpose().plot.contourf(levels=12, vmin=-2, vmax=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_Difference between January and July Climatology_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fbac0933130>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 404
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ds_mm.sst.sel(month=1) - ds_mm.sst.sel(month=7)).plot(vmax=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Transformations\n",
    "\n",
    "Now we want to _remove_ this climatology from the dataset, to examine the residual, called the _anomaly_, which is the interesting part from a climate perspective.\n",
    "Removing the seasonal climatology is a perfect example of a transformation: it operates over a group, but doesn't change the size of the dataset. Here is one way to code it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 9.537e-07 9.537e-07 9.537e-07 ... nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-68bad533-3d00-438f-a9c8-a000585b0633' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-68bad533-3d00-438f-a9c8-a000585b0633' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 708</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e8b02b7e-94c7-4c04-a766-13f2d115d075' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e8b02b7e-94c7-4c04-a766-13f2d115d075' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-89003654-a069-4172-b5ec-0f204d3bfd18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89003654-a069-4172-b5ec-0f204d3bfd18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7522bd0-b980-4442-9aca-c93073463402' class='xr-var-data-in' type='checkbox'><label for='data-e7522bd0-b980-4442-9aca-c93073463402' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-49518fdf-7b5d-4fe0-afe8-f44b698dac3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49518fdf-7b5d-4fe0-afe8-f44b698dac3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ead690a3-eabd-4306-8451-d0d718f5fbc6' class='xr-var-data-in' type='checkbox'><label for='data-ead690a3-eabd-4306-8451-d0d718f5fbc6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-ac0c135f-333a-4fa2-85e7-65855048de03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac0c135f-333a-4fa2-85e7-65855048de03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6728c84c-aeb0-41e8-b59d-67376b79ed5f' class='xr-var-data-in' type='checkbox'><label for='data-6728c84c-aeb0-41e8-b59d-67376b79ed5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a4341d98-cea2-4199-bbd4-fd34cb98b2f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a4341d98-cea2-4199-bbd4-fd34cb98b2f3' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.537e-07 9.537e-07 ... nan nan</div><input id='attrs-2a1ccc9e-f4f9-4b3a-843f-69b3a09c9aa6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a1ccc9e-f4f9-4b3a-843f-69b3a09c9aa6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a294773-775e-46cc-ba67-3f61b01fe926' class='xr-var-data-in' type='checkbox'><label for='data-7a294773-775e-46cc-ba67-3f61b01fe926' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        ...,\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "...\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[-4.9746037e-04, -4.0268898e-04, -1.5842915e-04, ...,\n",
       "         -2.0110607e-04, -3.4809113e-04, -4.9543381e-04],\n",
       "        [-4.1234493e-04, -2.3651123e-04,  9.5367432e-07, ...,\n",
       "          9.5367432e-07, -1.6415119e-04, -3.7527084e-04],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        ...,\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-aac8944b-6f98-4465-91c4-3b9731cf2bc1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-aac8944b-6f98-4465-91c4-3b9731cf2bc1' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 9.537e-07 9.537e-07 9.537e-07 ... nan nan"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def remove_time_mean(x):\n",
    "    return x - x.mean(dim='time')\n",
    "\n",
    "ds_anom = ds.groupby('time.month').apply(remove_time_mean)\n",
    "ds_anom"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Xarray makes these sorts of transformations easy by supporting _groupby arithmetic_.\n",
    "This concept is easiest explained with an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "    month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 ... 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 9.537e-07 9.537e-07 9.537e-07 ... nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cca7d03a-4ea9-4b9c-a84d-f8c41c140519' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cca7d03a-4ea9-4b9c-a84d-f8c41c140519' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 708</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-08a69cc3-b383-4c74-b6b6-b23f368ed466' class='xr-section-summary-in' type='checkbox'  checked><label for='section-08a69cc3-b383-4c74-b6b6-b23f368ed466' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-c4b1684b-398d-49f0-9f58-9176a8260514' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4b1684b-398d-49f0-9f58-9176a8260514' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d947269-12a2-4caa-a8e8-0af8b9824d1b' class='xr-var-data-in' type='checkbox'><label for='data-8d947269-12a2-4caa-a8e8-0af8b9824d1b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-459cf4aa-6b69-445f-8265-b2214df82429' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-459cf4aa-6b69-445f-8265-b2214df82429' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42610e00-97dc-4a2b-9ad7-7688f679d372' class='xr-var-data-in' type='checkbox'><label for='data-42610e00-97dc-4a2b-9ad7-7688f679d372' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-a517bc4d-0239-4525-be94-13b9d7b544d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a517bc4d-0239-4525-be94-13b9d7b544d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23a16f63-238f-4a97-80d5-79a84f1e02a4' class='xr-var-data-in' type='checkbox'><label for='data-23a16f63-238f-4a97-80d5-79a84f1e02a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 6 7 8 9 10 11 12</div><input id='attrs-77da2955-3fac-44f0-a96e-54f0296720e6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77da2955-3fac-44f0-a96e-54f0296720e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3b122d6-6457-4e2c-8435-3f3715b47e42' class='xr-var-data-in' type='checkbox'><label for='data-c3b122d6-6457-4e2c-8435-3f3715b47e42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "...\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9167e8fe-d6ed-4b03-9747-3710eb018871' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9167e8fe-d6ed-4b03-9747-3710eb018871' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.537e-07 9.537e-07 ... nan nan</div><input id='attrs-0730db18-791c-4814-bee9-a1cb8468c52b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0730db18-791c-4814-bee9-a1cb8468c52b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80377108-016a-4c5a-8789-88302f9226e1' class='xr-var-data-in' type='checkbox'><label for='data-80377108-016a-4c5a-8789-88302f9226e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        ...,\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "...\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[-4.9746037e-04, -4.0268898e-04, -1.5842915e-04, ...,\n",
       "         -2.0110607e-04, -3.4809113e-04, -4.9543381e-04],\n",
       "        [-4.1234493e-04, -2.3651123e-04,  9.5367432e-07, ...,\n",
       "          9.5367432e-07, -1.6415119e-04, -3.7527084e-04],\n",
       "        [ 9.5367432e-07,  9.5367432e-07,  9.5367432e-07, ...,\n",
       "          9.5367432e-07,  9.5367432e-07,  9.5367432e-07],\n",
       "        ...,\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [           nan,            nan,            nan, ...,\n",
       "                    nan,            nan,            nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d8a1f921-79c1-4ca7-8eee-c7ecdab0bc88' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d8a1f921-79c1-4ca7-8eee-c7ecdab0bc88' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "    month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 ... 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 9.537e-07 9.537e-07 9.537e-07 ... nan nan"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gb = ds.groupby('time.month')\n",
    "ds_anom = gb - gb.mean(dim='time')\n",
    "ds_anom"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can view the climate signal without the overwhelming influence of the seasonal cycle.\n",
    "\n",
    "_Timeseries at a single point in the North Atlantic_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fba50573640>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 343,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_anom.sst.sel(lon=300, lat=50).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "_Difference between Jan. 1 2018 and Jan. 1 1960_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fba9057eeb0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1mZl1RK/nbvXixcvaLQw+C2GoZUredxLppvle0jecC0k3Ru8uOe80hn42wCxKnu9A6pP9DdJN0lJSd5XTSf2+A7igbv+Z1D1nIafvQLpRm0+6iV3tuQqkb2nPA55kcO7+T5G+BFnjuQT5mC1JN6rP5eufTZpbfzolz1nIx2yUY3YHqRvJYtLN5bWkG+8NmviMhoxl3mcCaVDsIzluA8C5+TobXY9IFaYbSQ8YW0a6Wb8153mbuv3HkfrSz83vMY/0oLbJuSzMrtv/hPq4r20e8jG75s/9sZyPBblMXgocWNhvL+CfSQ8tW5Bj/xCpJeYNa/l781bSg/Dm5Tw/l8vDV4E96vbdhtQy9VTOwx+A/1VW1kgVyS+QZm16Jl/fk6QH2h1Wko8hy3lhvwH8nAUvXrz0YFHESGefMzNrnqR/JD0Y7aSIuLTX+emmPIbjUUoGyfaDPI7lAeCyiHj3cPtb90kaAIiIab3NiZlVjccsmFlbNegHvg1pXMRy4JquZ6p/HC8pJC0Zftf2k7RlfphaMW19BrvzXNX1TFlDkvbI5SVIXaTMzLrOYxbMrN2uzLPj3EHq3z+N1L97fdIc842m5xzLXgDOKfw81APQOulU0sPCZpGerbElaRzHa0jdZP5vj/Jl5eaxerl5oUf5MLMKczckM2srSR8m9WHfkdQXfhFpUOhFEfHvvcxb1Uk6CDgDeBMwlVRpeQD4EWksSdlD4fqapDfR5BSqETGjk3kxMxuLXFkwM7NRS9IJDE49O6SI0PB7mZlZkSsLZmZmZmZWygOczczMzMyslCsLZmZmZmZWypUFMzMzMzMr5cqCmZmZmZmVcmXBzMzMzMxKubJgZmZmZmalXFkwMzMzM7NSriyYmZmZmVkpVxbMzMzMzKyUKwtmZmZmZlbKlQUzMzMzMyvlyoKZmZmZmZVyZcHMzMzMzEr9f0AlBVd+fI9RAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 332,
       "width": 389
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ds_anom.sel(time='2018-01-01') - ds_anom.sel(time='1960-01-01')).sst.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grouby-Related: Resample, Rolling, Coarsen\n",
    "\n",
    "Resample in xarray is nearly identical to Pandas. It is effectively a group-by operation, and uses the same basic syntax. It can be applied only to time-index dimensions. Here we compute the five-year mean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
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       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, time: 13)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1960-12-31 1965-12-31 ... 2020-12-31\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 -0.0005707 -0.0005493 ... nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d0cd586a-46a7-471c-93a5-b643552de408' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d0cd586a-46a7-471c-93a5-b643552de408' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 13</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-81e91177-3619-4f17-9a4e-f3f2705ce886' class='xr-section-summary-in' type='checkbox'  checked><label for='section-81e91177-3619-4f17-9a4e-f3f2705ce886' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-12-31 ... 2020-12-31</div><input id='attrs-d4647c96-a19f-4a49-9ac7-d1216ecbce76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4647c96-a19f-4a49-9ac7-d1216ecbce76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-761f19a6-7a30-44ea-bff0-a80237cebb89' class='xr-var-data-in' type='checkbox'><label for='data-761f19a6-7a30-44ea-bff0-a80237cebb89' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-12-31T00:00:00.000000000&#x27;, &#x27;1965-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;1970-12-31T00:00:00.000000000&#x27;, &#x27;1975-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-12-31T00:00:00.000000000&#x27;, &#x27;1985-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;1990-12-31T00:00:00.000000000&#x27;, &#x27;1995-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-12-31T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-12-31T00:00:00.000000000&#x27;, &#x27;2015-12-31T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-31T00:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-bd3c4e6e-2648-4dc9-93e1-631186291806' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd3c4e6e-2648-4dc9-93e1-631186291806' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89f6844a-9c10-47db-a92b-2f12277fae8b' class='xr-var-data-in' type='checkbox'><label for='data-89f6844a-9c10-47db-a92b-2f12277fae8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-b63f7304-f6fa-401b-bfa3-8a28bf3adf59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b63f7304-f6fa-401b-bfa3-8a28bf3adf59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-569ca23f-3c7b-43e4-a29c-421b98c6f30e' class='xr-var-data-in' type='checkbox'><label for='data-569ca23f-3c7b-43e4-a29c-421b98c6f30e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e2dd5cb-1535-4837-a297-66d570675784' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e2dd5cb-1535-4837-a297-66d570675784' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.0005707 -0.0005493 ... nan nan</div><input id='attrs-a845b758-c08e-4b3c-9315-9b16ac761069' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a845b758-c08e-4b3c-9315-9b16ac761069' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a25c5ea0-fe70-4d37-a59e-0c2e32c86987' class='xr-var-data-in' type='checkbox'><label for='data-a25c5ea0-fe70-4d37-a59e-0c2e32c86987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-5.70684671e-04, -5.49256802e-04, -5.38418710e-04, ...,\n",
       "         -4.15881485e-04, -5.20139933e-04, -5.83092391e-04],\n",
       "        [-5.15530526e-04, -5.89827716e-04, -6.42200292e-04, ...,\n",
       "         -1.39196709e-04, -3.24239343e-04, -4.26093728e-04],\n",
       "        [-1.40964985e-05, -1.79181501e-04, -2.83718109e-04, ...,\n",
       "         -1.24106809e-04, -7.90158883e-05, -3.50972005e-05],\n",
       "        ...,\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan],\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan],\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan]],\n",
       "\n",
       "       [[-5.70684671e-04, -5.49256802e-04, -5.38418710e-04, ...,\n",
       "         -4.15881485e-04, -5.20139933e-04, -5.83092391e-04],\n",
       "        [-5.15530526e-04, -5.89827716e-04, -6.42200292e-04, ...,\n",
       "         -1.39196709e-04, -3.24239343e-04, -4.26093728e-04],\n",
       "        [-1.40964985e-05, -1.79181501e-04, -2.83718109e-04, ...,\n",
       "         -1.24106809e-04, -7.90158883e-05, -3.50972005e-05],\n",
       "...\n",
       "                     nan,             nan,             nan],\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan],\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan]],\n",
       "\n",
       "       [[ 1.06710559e-02,  1.02710230e-02,  1.00688301e-02, ...,\n",
       "          7.78120104e-03,  9.72755440e-03,  1.09023023e-02],\n",
       "        [ 9.64192580e-03,  1.10286605e-02,  1.20063955e-02, ...,\n",
       "          2.61675660e-03,  6.07069675e-03,  7.97217432e-03],\n",
       "        [ 2.81734596e-04,  3.36324517e-03,  5.31468447e-03, ...,\n",
       "          2.31115357e-03,  1.49352022e-03,  6.73671544e-04],\n",
       "        ...,\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan],\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan],\n",
       "        [            nan,             nan,             nan, ...,\n",
       "                     nan,             nan,             nan]]],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-824babba-1ce3-45d0-b09e-3fa36aadebb2' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-824babba-1ce3-45d0-b09e-3fa36aadebb2' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, time: 13)\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1960-12-31 1965-12-31 ... 2020-12-31\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float32 -0.0005707 -0.0005493 ... nan nan"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_anom_resample = ds_anom.resample(time='5Y').mean(dim='time')\n",
    "ds_anom_resample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fba9061fb50>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 343,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_anom.sst.sel(lon=300, lat=50).plot()\n",
    "ds_anom_resample.sst.sel(lon=300, lat=50).plot(marker='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fba72e33fd0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 316,
       "width": 389
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(ds_anom_resample.sel(time='2015-01-01', method='nearest') -\n",
    " ds_anom_resample.sel(time='1965-01-01', method='nearest')).sst.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rolling is also similar to pandas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "    month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 ... 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e1309c9e-4106-4763-b231-f772dfd6da8a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e1309c9e-4106-4763-b231-f772dfd6da8a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 89</li><li><span class='xr-has-index'>lon</span>: 180</li><li><span class='xr-has-index'>time</span>: 708</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ff233c0e-cba6-4f2c-ae89-75a65a81ec91' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ff233c0e-cba6-4f2c-ae89-75a65a81ec91' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>88.0 86.0 84.0 ... -86.0 -88.0</div><input id='attrs-1a923087-3aae-4b01-934d-72dfbdd6c3a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a923087-3aae-4b01-934d-72dfbdd6c3a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bddf874b-3d8e-4782-ba08-19281b439430' class='xr-var-data-in' type='checkbox'><label for='data-bddf874b-3d8e-4782-ba08-19281b439430' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>actual_range :</span></dt><dd>[ 88. -88.]</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([ 88.,  86.,  84.,  82.,  80.,  78.,  76.,  74.,  72.,  70.,  68.,  66.,\n",
       "        64.,  62.,  60.,  58.,  56.,  54.,  52.,  50.,  48.,  46.,  44.,  42.,\n",
       "        40.,  38.,  36.,  34.,  32.,  30.,  28.,  26.,  24.,  22.,  20.,  18.,\n",
       "        16.,  14.,  12.,  10.,   8.,   6.,   4.,   2.,   0.,  -2.,  -4.,  -6.,\n",
       "        -8., -10., -12., -14., -16., -18., -20., -22., -24., -26., -28., -30.,\n",
       "       -32., -34., -36., -38., -40., -42., -44., -46., -48., -50., -52., -54.,\n",
       "       -56., -58., -60., -62., -64., -66., -68., -70., -72., -74., -76., -78.,\n",
       "       -80., -82., -84., -86., -88.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 2.0 4.0 ... 354.0 356.0 358.0</div><input id='attrs-7660772e-b3e7-4ccc-9536-097ff6946996' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7660772e-b3e7-4ccc-9536-097ff6946996' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7279df6-918f-4b84-a6d0-dec237711aac' class='xr-var-data-in' type='checkbox'><label for='data-e7279df6-918f-4b84-a6d0-dec237711aac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>actual_range :</span></dt><dd>[  0. 358.]</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>coordinate_defines :</span></dt><dd>center</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   2.,   4.,   6.,   8.,  10.,  12.,  14.,  16.,  18.,  20.,  22.,\n",
       "        24.,  26.,  28.,  30.,  32.,  34.,  36.,  38.,  40.,  42.,  44.,  46.,\n",
       "        48.,  50.,  52.,  54.,  56.,  58.,  60.,  62.,  64.,  66.,  68.,  70.,\n",
       "        72.,  74.,  76.,  78.,  80.,  82.,  84.,  86.,  88.,  90.,  92.,  94.,\n",
       "        96.,  98., 100., 102., 104., 106., 108., 110., 112., 114., 116., 118.,\n",
       "       120., 122., 124., 126., 128., 130., 132., 134., 136., 138., 140., 142.,\n",
       "       144., 146., 148., 150., 152., 154., 156., 158., 160., 162., 164., 166.,\n",
       "       168., 170., 172., 174., 176., 178., 180., 182., 184., 186., 188., 190.,\n",
       "       192., 194., 196., 198., 200., 202., 204., 206., 208., 210., 212., 214.,\n",
       "       216., 218., 220., 222., 224., 226., 228., 230., 232., 234., 236., 238.,\n",
       "       240., 242., 244., 246., 248., 250., 252., 254., 256., 258., 260., 262.,\n",
       "       264., 266., 268., 270., 272., 274., 276., 278., 280., 282., 284., 286.,\n",
       "       288., 290., 292., 294., 296., 298., 300., 302., 304., 306., 308., 310.,\n",
       "       312., 314., 316., 318., 320., 322., 324., 326., 328., 330., 332., 334.,\n",
       "       336., 338., 340., 342., 344., 346., 348., 350., 352., 354., 356., 358.],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-6bf821d5-e366-4ac2-8f09-b8f4822ac1b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bf821d5-e366-4ac2-8f09-b8f4822ac1b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b4b53b3-8c7a-465a-b341-3fb4cda650b7' class='xr-var-data-in' type='checkbox'><label for='data-5b4b53b3-8c7a-465a-b341-3fb4cda650b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 ... 6 7 8 9 10 11 12</div><input id='attrs-0c96bc43-4e17-46ce-9233-5e7e4465bc69' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c96bc43-4e17-46ce-9233-5e7e4465bc69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5970afea-6aa7-4579-ac5f-e98b8892b943' class='xr-var-data-in' type='checkbox'><label for='data-5970afea-6aa7-4579-ac5f-e98b8892b943' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "...\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,\n",
       "        7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11,\n",
       "       12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,\n",
       "        5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9,\n",
       "       10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,\n",
       "        3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,\n",
       "        8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,\n",
       "        1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,\n",
       "        6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10,\n",
       "       11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,\n",
       "        4,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,\n",
       "        9, 10, 11, 12,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12,  1,\n",
       "        2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-10203a83-5a83-4f64-8708-3a497228e576' class='xr-section-summary-in' type='checkbox'  checked><label for='section-10203a83-5a83-4f64-8708-3a497228e576' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>sst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a91428bb-f93a-45ce-8ec2-9d2176762116' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a91428bb-f93a-45ce-8ec2-9d2176762116' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-070425e7-0e6b-4aa1-8baa-cf7cffa7f953' class='xr-var-data-in' type='checkbox'><label for='data-070425e7-0e6b-4aa1-8baa-cf7cffa7f953' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]],\n",
       "\n",
       "       [[nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        ...,\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan],\n",
       "        [nan, nan, nan, ..., nan, nan, nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4839bd95-cc95-4e21-83e7-1124eca47a67' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4839bd95-cc95-4e21-83e7-1124eca47a67' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lat: 89, lon: 180, time: 708)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 88.0 86.0 84.0 82.0 80.0 ... -82.0 -84.0 -86.0 -88.0\n",
       "  * lon      (lon) float32 0.0 2.0 4.0 6.0 8.0 ... 350.0 352.0 354.0 356.0 358.0\n",
       "  * time     (time) datetime64[ns] 1960-01-01 1960-02-01 ... 2018-12-01\n",
       "    month    (time) int64 1 2 3 4 5 6 7 8 9 10 11 ... 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables:\n",
       "    sst      (time, lat, lon) float64 nan nan nan nan nan ... nan nan nan nan"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_anom_rolling = ds_anom.rolling(time=12, center=True).mean()\n",
    "ds_anom_rolling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fbac0538c10>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 343,
       "width": 384
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_anom.sst.sel(lon=300, lat=50).plot(label='monthly anom')\n",
    "ds_anom_resample.sst.sel(lon=300, lat=50).plot(marker='o', label='5 year resample')\n",
    "ds_anom_rolling.sst.sel(lon=300, lat=50).plot(label='12 month rolling mean')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (X: 360, Y: 180, Z: 33)\n",
       "Coordinates:\n",
       "  * Z        (Z) float32 0.0 10.0 20.0 30.0 50.0 ... 4e+03 4.5e+03 5e+03 5.5e+03\n",
       "  * X        (X) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5\n",
       "  * Y        (Y) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "Data variables:\n",
       "    basin    (Z, Y, X) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  IRIDL</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-05a53cc8-3c3f-4074-85f8-4a492f6e4e5f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-05a53cc8-3c3f-4074-85f8-4a492f6e4e5f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>X</span>: 360</li><li><span class='xr-has-index'>Y</span>: 180</li><li><span class='xr-has-index'>Z</span>: 33</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-56347509-1d27-42d3-96fc-5f73f3d28c75' class='xr-section-summary-in' type='checkbox'  checked><label for='section-56347509-1d27-42d3-96fc-5f73f3d28c75' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Z</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 10.0 20.0 ... 5e+03 5.5e+03</div><input id='attrs-256e37e9-cca1-443d-b92c-b97fe9d12d3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-256e37e9-cca1-443d-b92c-b97fe9d12d3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65e0f25d-b4b2-4076-80c5-af7e737663ad' class='xr-var-data-in' type='checkbox'><label for='data-65e0f25d-b4b2-4076-80c5-af7e737663ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([   0.,   10.,   20.,   30.,   50.,   75.,  100.,  125.,  150.,  200.,\n",
       "        250.,  300.,  400.,  500.,  600.,  700.,  800.,  900., 1000., 1100.,\n",
       "       1200., 1300., 1400., 1500., 1750., 2000., 2500., 3000., 3500., 4000.,\n",
       "       4500., 5000., 5500.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-23217211-fcb6-488c-b55f-7d084e7dcd0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23217211-fcb6-488c-b55f-7d084e7dcd0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e04be613-73b8-49ba-be62-be25e0265790' class='xr-var-data-in' type='checkbox'><label for='data-e04be613-73b8-49ba-be62-be25e0265790' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>pointwidth :</span></dt><dd>1.0</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>gridtype :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-f1d9264a-f641-4f9b-85dc-a798af2a3106' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1d9264a-f641-4f9b-85dc-a798af2a3106' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b26ea90a-f453-47ab-81c2-d09f95a7ffbd' class='xr-var-data-in' type='checkbox'><label for='data-b26ea90a-f453-47ab-81c2-d09f95a7ffbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>pointwidth :</span></dt><dd>1.0</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>degree_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-82cda0bd-4dea-4484-8425-5bc4517d9bb8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-82cda0bd-4dea-4484-8425-5bc4517d9bb8' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>basin</span></div><div class='xr-var-dims'>(Z, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd09fe9a-c217-4ba8-832f-9bccfb7ece4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd09fe9a-c217-4ba8-832f-9bccfb7ece4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-837b95d2-410a-4090-bea1-041f0f20b194' class='xr-var-data-in' type='checkbox'><label for='data-837b95d2-410a-4090-bea1-041f0f20b194' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>basin code</dd><dt><span>units :</span></dt><dd>ids</dd><dt><span>scale_max :</span></dt><dd>58</dd><dt><span>CLIST :</span></dt><dd>Atlantic Ocean\n",
       "Pacific Ocean \n",
       "Indian Ocean\n",
       "Mediterranean Sea\n",
       "Baltic Sea\n",
       "Black Sea\n",
       "Red Sea\n",
       "Persian Gulf\n",
       "Hudson Bay\n",
       "Southern Ocean\n",
       "Arctic Ocean\n",
       "Sea of Japan\n",
       "Kara Sea\n",
       "Sulu Sea\n",
       "Baffin Bay\n",
       "East Mediterranean\n",
       "West Mediterranean\n",
       "Sea of Okhotsk\n",
       "Banda Sea\n",
       "Caribbean Sea\n",
       "Andaman Basin\n",
       "North Caribbean\n",
       "Gulf of Mexico\n",
       "Beaufort Sea\n",
       "South China Sea\n",
       "Barents Sea\n",
       "Celebes Sea\n",
       "Aleutian Basin\n",
       "Fiji Basin\n",
       "North American Basin\n",
       "West European Basin\n",
       "Southeast Indian Basin\n",
       "Coral Sea\n",
       "East Indian Basin\n",
       "Central Indian Basin\n",
       "Southwest Atlantic Basin\n",
       "Southeast Atlantic Basin\n",
       "Southeast Pacific Basin\n",
       "Guatemala Basin\n",
       "East Caroline Basin\n",
       "Marianas Basin\n",
       "Philippine Sea\n",
       "Arabian Sea\n",
       "Chile Basin\n",
       "Somali Basin\n",
       "Mascarene Basin\n",
       "Crozet Basin\n",
       "Guinea Basin\n",
       "Brazil Basin\n",
       "Argentine Basin\n",
       "Tasman Sea\n",
       "Atlantic Indian Basin\n",
       "Caspian Sea\n",
       "Sulu Sea II\n",
       "Venezuela Basin\n",
       "Bay of Bengal\n",
       "Java Sea\n",
       "East Indian Atlantic Basin</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>58</dd><dt><span>scale_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[2138400 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-368380ec-2222-4df0-b1e4-b1012482b3f1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-368380ec-2222-4df0-b1e4-b1012482b3f1' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>IRIDL</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (X: 360, Y: 180, Z: 33)\n",
       "Coordinates:\n",
       "  * Z        (Z) float32 0.0 10.0 20.0 30.0 50.0 ... 4e+03 4.5e+03 5e+03 5.5e+03\n",
       "  * X        (X) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5\n",
       "  * Y        (Y) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "Data variables:\n",
       "    basin    (Z, Y, X) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  IRIDL"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basin = xr.open_dataset('http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NODC/.WOA09/.Masks/.basin/dods')\n",
    "basin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       ".xr-attrs dt {\n",
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       "  grid-column: 1;\n",
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       "\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (Z: 33, lat: 180, lon: 360)\n",
       "Coordinates:\n",
       "  * Z        (Z) float32 0.0 10.0 20.0 30.0 50.0 ... 4e+03 4.5e+03 5e+03 5.5e+03\n",
       "  * lon      (lon) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5\n",
       "  * lat      (lat) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "Data variables:\n",
       "    basin    (Z, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  IRIDL</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-27eb147a-3e33-4095-8b11-aa94326ee7d4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-27eb147a-3e33-4095-8b11-aa94326ee7d4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Z</span>: 33</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-69018bfb-fa22-4d7e-8f69-8008ad561cd2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-69018bfb-fa22-4d7e-8f69-8008ad561cd2' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Z</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 10.0 20.0 ... 5e+03 5.5e+03</div><input id='attrs-60c295c1-6fff-45d4-bed2-cc8355f5efa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60c295c1-6fff-45d4-bed2-cc8355f5efa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dc42960-c648-4d1e-b77e-6a95af921347' class='xr-var-data-in' type='checkbox'><label for='data-1dc42960-c648-4d1e-b77e-6a95af921347' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([   0.,   10.,   20.,   30.,   50.,   75.,  100.,  125.,  150.,  200.,\n",
       "        250.,  300.,  400.,  500.,  600.,  700.,  800.,  900., 1000., 1100.,\n",
       "       1200., 1300., 1400., 1500., 1750., 2000., 2500., 3000., 3500., 4000.,\n",
       "       4500., 5000., 5500.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-52998c6a-a92d-4a54-a6a0-99a9734ab4cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52998c6a-a92d-4a54-a6a0-99a9734ab4cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46346429-b72d-49b7-b841-92edb0a91d4e' class='xr-var-data-in' type='checkbox'><label for='data-46346429-b72d-49b7-b841-92edb0a91d4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>pointwidth :</span></dt><dd>1.0</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>gridtype :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-cef93a3c-d634-499e-b4ee-6645369f4402' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cef93a3c-d634-499e-b4ee-6645369f4402' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96230aed-bc34-4c2d-a619-b82c3c627dd5' class='xr-var-data-in' type='checkbox'><label for='data-96230aed-bc34-4c2d-a619-b82c3c627dd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>pointwidth :</span></dt><dd>1.0</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>degree_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-50279101-8680-40fd-9ad6-f1dc748102d0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-50279101-8680-40fd-9ad6-f1dc748102d0' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>basin</span></div><div class='xr-var-dims'>(Z, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-45e10d9f-e626-4b80-b443-2d0d40e22b52' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45e10d9f-e626-4b80-b443-2d0d40e22b52' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e040fdc-a420-431e-bddf-81fa5a4b5fd6' class='xr-var-data-in' type='checkbox'><label for='data-2e040fdc-a420-431e-bddf-81fa5a4b5fd6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>basin code</dd><dt><span>units :</span></dt><dd>ids</dd><dt><span>scale_max :</span></dt><dd>58</dd><dt><span>CLIST :</span></dt><dd>Atlantic Ocean\n",
       "Pacific Ocean \n",
       "Indian Ocean\n",
       "Mediterranean Sea\n",
       "Baltic Sea\n",
       "Black Sea\n",
       "Red Sea\n",
       "Persian Gulf\n",
       "Hudson Bay\n",
       "Southern Ocean\n",
       "Arctic Ocean\n",
       "Sea of Japan\n",
       "Kara Sea\n",
       "Sulu Sea\n",
       "Baffin Bay\n",
       "East Mediterranean\n",
       "West Mediterranean\n",
       "Sea of Okhotsk\n",
       "Banda Sea\n",
       "Caribbean Sea\n",
       "Andaman Basin\n",
       "North Caribbean\n",
       "Gulf of Mexico\n",
       "Beaufort Sea\n",
       "South China Sea\n",
       "Barents Sea\n",
       "Celebes Sea\n",
       "Aleutian Basin\n",
       "Fiji Basin\n",
       "North American Basin\n",
       "West European Basin\n",
       "Southeast Indian Basin\n",
       "Coral Sea\n",
       "East Indian Basin\n",
       "Central Indian Basin\n",
       "Southwest Atlantic Basin\n",
       "Southeast Atlantic Basin\n",
       "Southeast Pacific Basin\n",
       "Guatemala Basin\n",
       "East Caroline Basin\n",
       "Marianas Basin\n",
       "Philippine Sea\n",
       "Arabian Sea\n",
       "Chile Basin\n",
       "Somali Basin\n",
       "Mascarene Basin\n",
       "Crozet Basin\n",
       "Guinea Basin\n",
       "Brazil Basin\n",
       "Argentine Basin\n",
       "Tasman Sea\n",
       "Atlantic Indian Basin\n",
       "Caspian Sea\n",
       "Sulu Sea II\n",
       "Venezuela Basin\n",
       "Bay of Bengal\n",
       "Java Sea\n",
       "East Indian Atlantic Basin</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>58</dd><dt><span>scale_min :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>[2138400 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c2e6909-cff2-44e5-aa25-1c7b2f752cf2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c2e6909-cff2-44e5-aa25-1c7b2f752cf2' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>IRIDL</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (Z: 33, lat: 180, lon: 360)\n",
       "Coordinates:\n",
       "  * Z        (Z) float32 0.0 10.0 20.0 30.0 50.0 ... 4e+03 4.5e+03 5e+03 5.5e+03\n",
       "  * lon      (lon) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5\n",
       "  * lat      (lat) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "Data variables:\n",
       "    basin    (Z, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  IRIDL"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basin = basin.rename({'X': 'lon', 'Y': 'lat'})\n",
    "basin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "tags": [
     "scroll-output"
    ]
   },
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;basin&#x27; (lat: 180, lon: 360)&gt;\n",
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       "Coordinates:\n",
       "    Z        float32 0.0\n",
       "  * lon      (lon) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5\n",
       "  * lat      (lat) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "Attributes:\n",
       "    long_name:  basin code\n",
       "    units:      ids\n",
       "    scale_max:  58\n",
       "    CLIST:      Atlantic Ocean\\nPacific Ocean \\nIndian Ocean\\nMediterranean S...\n",
       "    valid_min:  1\n",
       "    valid_max:  58\n",
       "    scale_min:  1</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'basin'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-11fea3b7-d972-4c9d-afaa-a225740a5fb7' class='xr-array-in' type='checkbox' checked><label for='section-11fea3b7-d972-4c9d-afaa-a225740a5fb7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan nan nan nan nan nan nan nan ... 11.0 11.0 11.0 11.0 11.0 11.0 11.0</span></div><div class='xr-array-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [11., 11., 11., ..., 11., 11., 11.],\n",
       "       [11., 11., 11., ..., 11., 11., 11.],\n",
       "       [11., 11., 11., ..., 11., 11., 11.]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-acf626ab-1e45-44e4-8916-ff54b3b6c49e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-acf626ab-1e45-44e4-8916-ff54b3b6c49e' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-6bdedb25-4a4f-4d24-bb58-1978fa52e7e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bdedb25-4a4f-4d24-bb58-1978fa52e7e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18b81c52-6dca-4050-92cd-a21cecc69e69' class='xr-var-data-in' type='checkbox'><label for='data-18b81c52-6dca-4050-92cd-a21cecc69e69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-2d779bef-8ce6-4cc5-b0c3-4b9bef4f0ee9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d779bef-8ce6-4cc5-b0c3-4b9bef4f0ee9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-018227b4-4a19-407b-a93a-e935ad98ebed' class='xr-var-data-in' type='checkbox'><label for='data-018227b4-4a19-407b-a93a-e935ad98ebed' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>pointwidth :</span></dt><dd>1.0</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>gridtype :</span></dt><dd>1</dd><dt><span>units :</span></dt><dd>degree_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-7caeec9f-73cd-4f76-90ad-c164b36d3c8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7caeec9f-73cd-4f76-90ad-c164b36d3c8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a3f4bc-e8f6-417d-9ca4-96560d3a0d0a' class='xr-var-data-in' type='checkbox'><label for='data-a3a3f4bc-e8f6-417d-9ca4-96560d3a0d0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>pointwidth :</span></dt><dd>1.0</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>degree_north</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7fb077c-031a-4b5f-9326-ee5f1683d1ec' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e7fb077c-031a-4b5f-9326-ee5f1683d1ec' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>basin code</dd><dt><span>units :</span></dt><dd>ids</dd><dt><span>scale_max :</span></dt><dd>58</dd><dt><span>CLIST :</span></dt><dd>Atlantic Ocean\n",
       "Pacific Ocean \n",
       "Indian Ocean\n",
       "Mediterranean Sea\n",
       "Baltic Sea\n",
       "Black Sea\n",
       "Red Sea\n",
       "Persian Gulf\n",
       "Hudson Bay\n",
       "Southern Ocean\n",
       "Arctic Ocean\n",
       "Sea of Japan\n",
       "Kara Sea\n",
       "Sulu Sea\n",
       "Baffin Bay\n",
       "East Mediterranean\n",
       "West Mediterranean\n",
       "Sea of Okhotsk\n",
       "Banda Sea\n",
       "Caribbean Sea\n",
       "Andaman Basin\n",
       "North Caribbean\n",
       "Gulf of Mexico\n",
       "Beaufort Sea\n",
       "South China Sea\n",
       "Barents Sea\n",
       "Celebes Sea\n",
       "Aleutian Basin\n",
       "Fiji Basin\n",
       "North American Basin\n",
       "West European Basin\n",
       "Southeast Indian Basin\n",
       "Coral Sea\n",
       "East Indian Basin\n",
       "Central Indian Basin\n",
       "Southwest Atlantic Basin\n",
       "Southeast Atlantic Basin\n",
       "Southeast Pacific Basin\n",
       "Guatemala Basin\n",
       "East Caroline Basin\n",
       "Marianas Basin\n",
       "Philippine Sea\n",
       "Arabian Sea\n",
       "Chile Basin\n",
       "Somali Basin\n",
       "Mascarene Basin\n",
       "Crozet Basin\n",
       "Guinea Basin\n",
       "Brazil Basin\n",
       "Argentine Basin\n",
       "Tasman Sea\n",
       "Atlantic Indian Basin\n",
       "Caspian Sea\n",
       "Sulu Sea II\n",
       "Venezuela Basin\n",
       "Bay of Bengal\n",
       "Java Sea\n",
       "East Indian Atlantic Basin</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>valid_max :</span></dt><dd>58</dd><dt><span>scale_min :</span></dt><dd>1</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'basin' (lat: 180, lon: 360)>\n",
       "array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [11., 11., 11., ..., 11., 11., 11.],\n",
       "       [11., 11., 11., ..., 11., 11., 11.],\n",
       "       [11., 11., 11., ..., 11., 11., 11.]], dtype=float32)\n",
       "Coordinates:\n",
       "    Z        float32 0.0\n",
       "  * lon      (lon) float32 0.5 1.5 2.5 3.5 4.5 ... 355.5 356.5 357.5 358.5 359.5\n",
       "  * lat      (lat) float32 -89.5 -88.5 -87.5 -86.5 -85.5 ... 86.5 87.5 88.5 89.5\n",
       "Attributes:\n",
       "    long_name:  basin code\n",
       "    units:      ids\n",
       "    scale_max:  58\n",
       "    CLIST:      Atlantic Ocean\\nPacific Ocean \\nIndian Ocean\\nMediterranean S...\n",
       "    valid_min:  1\n",
       "    valid_max:  58\n",
       "    scale_min:  1"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basin_surf = basin.basin[0]\n",
    "basin_surf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fba90665b20>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 332,
       "width": 387
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "basin_surf.plot(vmax=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fba80dd31f0>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 331,
       "width": 386
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "basin_surf_interp = basin_surf.interp_like(ds.sst, method='nearest')\n",
    "basin_surf_interp.plot(vmax=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "tags": [
     "scroll-output"
    ]
   },
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (time: 708, basin: 14)&gt;\n",
       "array([[-1.8       , -1.8       , 23.455315  , ..., -1.8       ,\n",
       "         3.3971915 , 24.182198  ],\n",
       "       [-1.8       , -1.8       , 23.722523  , ..., -1.8       ,\n",
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       "       [-1.8       , -1.8       , 24.601315  , ..., -1.8       ,\n",
       "        -0.26487017, 26.234186  ],\n",
       "       ...,\n",
       "       [ 0.6758096 ,  6.5041866 , 29.279472  , ..., 10.920225  ,\n",
       "        15.955018  , 29.419764  ],\n",
       "       [-0.7937473 ,  3.0715103 , 27.608444  , ...,  5.4078865 ,\n",
       "        10.673691  , 27.755806  ],\n",
       "       [-1.8       , -0.06061229, 25.881489  , ...,  0.5253577 ,\n",
       "         7.2676916 , 26.16315   ]], dtype=float32)\n",
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       "Attributes:\n",
       "    long_name:     Monthly Means of Sea Surface Temperature\n",
       "    units:         degC\n",
       "    var_desc:      Sea Surface Temperature\n",
       "    level_desc:    Surface\n",
       "    statistic:     Mean\n",
       "    dataset:       NOAA Extended Reconstructed SST V5\n",
       "    parent_stat:   Individual Values\n",
       "    actual_range:  [-1.8     42.32636]\n",
       "    valid_range:   [-1.8 45. ]\n",
       "    _ChunkSizes:   [  1  89 180]</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 708</li><li><span class='xr-has-index'>basin</span>: 14</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1429ba8f-9da3-4249-8a6b-1c7c9ea47579' class='xr-array-in' type='checkbox' checked><label for='section-1429ba8f-9da3-4249-8a6b-1c7c9ea47579' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-1.8 -1.8 23.46 13.2 1.804 7.341 ... 3.645 -1.8 0.5254 7.268 26.16</span></div><div class='xr-array-data'><pre>array([[-1.8       , -1.8       , 23.455315  , ..., -1.8       ,\n",
       "         3.3971915 , 24.182198  ],\n",
       "       [-1.8       , -1.8       , 23.722523  , ..., -1.8       ,\n",
       "         0.03573781, 24.59657   ],\n",
       "       [-1.8       , -1.8       , 24.601315  , ..., -1.8       ,\n",
       "        -0.26487017, 26.234186  ],\n",
       "       ...,\n",
       "       [ 0.6758096 ,  6.5041866 , 29.279472  , ..., 10.920225  ,\n",
       "        15.955018  , 29.419764  ],\n",
       "       [-0.7937473 ,  3.0715103 , 27.608444  , ...,  5.4078865 ,\n",
       "        10.673691  , 27.755806  ],\n",
       "       [-1.8       , -0.06061229, 25.881489  , ...,  0.5253577 ,\n",
       "         7.2676916 , 26.16315   ]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-8d69f5cb-07aa-4735-9be7-0bfebcdc0880' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8d69f5cb-07aa-4735-9be7-0bfebcdc0880' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01 ... 2018-12-01</div><input id='attrs-41289f7d-dea5-4f1b-b734-b4542a37fb2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41289f7d-dea5-4f1b-b734-b4542a37fb2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3cfd068-ae7f-47c3-bafa-627bdfe079fc' class='xr-var-data-in' type='checkbox'><label for='data-f3cfd068-ae7f-47c3-bafa-627bdfe079fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>delta_t :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>avg_period :</span></dt><dd>0000-01-00 00:00:00</dd><dt><span>prev_avg_period :</span></dt><dd>0000-00-07 00:00:00</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>actual_range :</span></dt><dd>[19723. 80750.]</dd><dt><span>_ChunkSizes :</span></dt><dd>1</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T00:00:00.000000000&#x27;, &#x27;1960-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;1960-03-01T00:00:00.000000000&#x27;, ..., &#x27;2018-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-01T00:00:00.000000000&#x27;, &#x27;2018-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-68a7cabd-937e-4ead-854c-ff6bded529e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68a7cabd-937e-4ead-854c-ff6bded529e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcf6b51b-03cf-429b-a4bc-9d53d4603927' class='xr-var-data-in' type='checkbox'><label for='data-bcf6b51b-03cf-429b-a4bc-9d53d4603927' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>basin</span></div><div class='xr-var-dims'>(basin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 12.0 53.0 56.0</div><input id='attrs-6e1c590a-6e3b-42bd-b765-f5d5db9e3d5f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6e1c590a-6e3b-42bd-b765-f5d5db9e3d5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c39ad06-c89a-42a0-8b55-d5bf56ffcf22' class='xr-var-data-in' type='checkbox'><label for='data-8c39ad06-c89a-42a0-8b55-d5bf56ffcf22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 53., 56.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7ea3eaa3-bdd6-4579-94a0-b63f1a78e113' class='xr-section-summary-in' type='checkbox'  ><label for='section-7ea3eaa3-bdd6-4579-94a0-b63f1a78e113' class='xr-section-summary' >Attributes: <span>(10)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Monthly Means of Sea Surface Temperature</dd><dt><span>units :</span></dt><dd>degC</dd><dt><span>var_desc :</span></dt><dd>Sea Surface Temperature</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Mean</dd><dt><span>dataset :</span></dt><dd>NOAA Extended Reconstructed SST V5</dd><dt><span>parent_stat :</span></dt><dd>Individual Values</dd><dt><span>actual_range :</span></dt><dd>[-1.8     42.32636]</dd><dt><span>valid_range :</span></dt><dd>[-1.8 45. ]</dd><dt><span>_ChunkSizes :</span></dt><dd>[  1  89 180]</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.DataArray 'sst' (time: 708, basin: 14)>\n",
       "array([[-1.8       , -1.8       , 23.455315  , ..., -1.8       ,\n",
       "         3.3971915 , 24.182198  ],\n",
       "       [-1.8       , -1.8       , 23.722523  , ..., -1.8       ,\n",
       "         0.03573781, 24.59657   ],\n",
       "       [-1.8       , -1.8       , 24.601315  , ..., -1.8       ,\n",
       "        -0.26487017, 26.234186  ],\n",
       "       ...,\n",
       "       [ 0.6758096 ,  6.5041866 , 29.279472  , ..., 10.920225  ,\n",
       "        15.955018  , 29.419764  ],\n",
       "       [-0.7937473 ,  3.0715103 , 27.608444  , ...,  5.4078865 ,\n",
       "        10.673691  , 27.755806  ],\n",
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       "         7.2676916 , 26.16315   ]], dtype=float32)\n",
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       "Attributes:\n",
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       "    units:         degC\n",
       "    var_desc:      Sea Surface Temperature\n",
       "    level_desc:    Surface\n",
       "    statistic:     Mean\n",
       "    dataset:       NOAA Extended Reconstructed SST V5\n",
       "    parent_stat:   Individual Values\n",
       "    actual_range:  [-1.8     42.32636]\n",
       "    valid_range:   [-1.8 45. ]\n",
       "    _ChunkSizes:   [  1  89 180]"
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     },
     "execution_count": 33,
     "metadata": {},
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    }
   ],
   "source": [
    "ds.sst.groupby(basin_surf_interp).first()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;sst&#x27; (month: 12, basin: 14)&gt;\n",
       "array([[18.931244  , 20.88606   , 22.068876  , 15.7806225 ,  2.9009485 ,\n",
       "         8.286119  , 25.862597  , 21.052422  , -1.7988946 ,  2.5364153 ,\n",
       "        -1.2113837 ,  5.99166   ,  6.69535   , 26.615591  ],\n",
       "       [18.998413  , 20.938007  , 22.466644  , 15.171556  ,  1.6216687 ,\n",
       "         7.475156  , 25.31563   , 20.009794  , -1.8000002 ,  2.86857   ,\n",
       "        -1.2622244 ,  4.981395  ,  5.473524  , 26.889442  ],\n",
       "       [19.013428  , 20.972063  , 22.608067  , 15.258743  ,  1.4993656 ,\n",
       "         7.793447  , 25.649214  , 20.699417  , -1.8000002 ,  2.6315544 ,\n",
       "        -1.2847868 ,  5.1045027 ,  5.522258  , 28.037973  ],\n",
       "       [18.989248  , 20.968798  , 22.381023  , 16.224312  ,  3.0491576 ,\n",
       "        10.017782  , 26.88303   , 23.203306  , -1.7996598 ,  2.094409  ,\n",
       "        -1.2763202 ,  6.663208  ,  9.4189415 , 29.374727  ],\n",
       "       [19.068415  , 21.018923  , 21.714952  , 18.613165  ,  6.4635086 ,\n",
       "        14.915698  , 28.640142  , 26.750372  , -1.7467502 ,  1.571553  ,\n",
       "        -1.1642531 ,  9.768522  , 15.095652  , 29.972607  ],\n",
       "       [19.352161  , 21.17309   , 20.790792  , 21.979132  , 11.794082  ,\n",
       "        20.411827  , 29.786642  , 29.794815  , -0.96558964,  1.1652179 ,\n",
       "        -0.8448692 , 14.277155  , 20.739882  , 29.463205  ],\n",
       "       [19.71806   , 21.479403  , 20.011818  , 24.690279  , 16.125217  ,\n",
       "        23.58809   , 30.706587  , 31.815105  ,  2.8862731 ,  0.8692938 ,\n",
       "        -0.30307108, 18.744436  , 24.158962  , 28.86987   ],\n",
       "       [19.959143  , 21.723642  , 19.603079  , 25.818441  , 17.186897  ,\n",
       "        24.277603  , 31.248007  , 32.692772  ,  5.3934736 ,  0.68534446,\n",
       "         0.16548847, 21.910128  , 24.577526  , 28.628706  ],\n",
       "       [19.816757  , 21.665964  , 19.646137  , 24.763577  , 14.3625765 ,\n",
       "        21.748938  , 31.174229  , 32.241535  ,  4.6783195 ,  0.6313895 ,\n",
       "         0.03611656, 20.365383  , 21.501966  , 28.853634  ],\n",
       "       [19.467312  , 21.347132  , 20.05091   , 22.60426   , 10.456942  ,\n",
       "        17.874405  , 30.591843  , 30.352285  ,  2.3623    ,  0.72350246,\n",
       "        -0.554342  , 16.454807  , 16.766832  , 29.040428  ],\n",
       "       [19.136904  , 21.059431  , 20.721912  , 19.869085  ,  7.2571416 ,\n",
       "        13.941229  , 28.884726  , 27.106995  ,  0.03359437,  1.0484893 ,\n",
       "        -0.97754955, 12.12734   , 12.716839  , 28.491669  ],\n",
       "       [18.968773  , 20.906147  , 21.460379  , 17.377382  ,  4.863486  ,\n",
       "        10.682313  , 27.186651  , 23.71751   , -1.7128265 ,  1.7405492 ,\n",
       "        -1.1221472 ,  8.642129  ,  9.399436  , 27.350985  ]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "    Z        float32 0.0\n",
       "  * basin    (basin) float64 1.0 2.0 3.0 4.0 5.0 ... 10.0 11.0 12.0 53.0 56.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'sst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>month</span>: 12</li><li><span class='xr-has-index'>basin</span>: 14</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-55b1ff2c-c449-4eb2-a7bc-b5a0207a7a9b' class='xr-array-in' type='checkbox' checked><label for='section-55b1ff2c-c449-4eb2-a7bc-b5a0207a7a9b' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>18.93 20.89 22.07 15.78 2.901 8.286 ... 1.741 -1.122 8.642 9.399 27.35</span></div><div class='xr-array-data'><pre>array([[18.931244  , 20.88606   , 22.068876  , 15.7806225 ,  2.9009485 ,\n",
       "         8.286119  , 25.862597  , 21.052422  , -1.7988946 ,  2.5364153 ,\n",
       "        -1.2113837 ,  5.99166   ,  6.69535   , 26.615591  ],\n",
       "       [18.998413  , 20.938007  , 22.466644  , 15.171556  ,  1.6216687 ,\n",
       "         7.475156  , 25.31563   , 20.009794  , -1.8000002 ,  2.86857   ,\n",
       "        -1.2622244 ,  4.981395  ,  5.473524  , 26.889442  ],\n",
       "       [19.013428  , 20.972063  , 22.608067  , 15.258743  ,  1.4993656 ,\n",
       "         7.793447  , 25.649214  , 20.699417  , -1.8000002 ,  2.6315544 ,\n",
       "        -1.2847868 ,  5.1045027 ,  5.522258  , 28.037973  ],\n",
       "       [18.989248  , 20.968798  , 22.381023  , 16.224312  ,  3.0491576 ,\n",
       "        10.017782  , 26.88303   , 23.203306  , -1.7996598 ,  2.094409  ,\n",
       "        -1.2763202 ,  6.663208  ,  9.4189415 , 29.374727  ],\n",
       "       [19.068415  , 21.018923  , 21.714952  , 18.613165  ,  6.4635086 ,\n",
       "        14.915698  , 28.640142  , 26.750372  , -1.7467502 ,  1.571553  ,\n",
       "        -1.1642531 ,  9.768522  , 15.095652  , 29.972607  ],\n",
       "       [19.352161  , 21.17309   , 20.790792  , 21.979132  , 11.794082  ,\n",
       "        20.411827  , 29.786642  , 29.794815  , -0.96558964,  1.1652179 ,\n",
       "        -0.8448692 , 14.277155  , 20.739882  , 29.463205  ],\n",
       "       [19.71806   , 21.479403  , 20.011818  , 24.690279  , 16.125217  ,\n",
       "        23.58809   , 30.706587  , 31.815105  ,  2.8862731 ,  0.8692938 ,\n",
       "        -0.30307108, 18.744436  , 24.158962  , 28.86987   ],\n",
       "       [19.959143  , 21.723642  , 19.603079  , 25.818441  , 17.186897  ,\n",
       "        24.277603  , 31.248007  , 32.692772  ,  5.3934736 ,  0.68534446,\n",
       "         0.16548847, 21.910128  , 24.577526  , 28.628706  ],\n",
       "       [19.816757  , 21.665964  , 19.646137  , 24.763577  , 14.3625765 ,\n",
       "        21.748938  , 31.174229  , 32.241535  ,  4.6783195 ,  0.6313895 ,\n",
       "         0.03611656, 20.365383  , 21.501966  , 28.853634  ],\n",
       "       [19.467312  , 21.347132  , 20.05091   , 22.60426   , 10.456942  ,\n",
       "        17.874405  , 30.591843  , 30.352285  ,  2.3623    ,  0.72350246,\n",
       "        -0.554342  , 16.454807  , 16.766832  , 29.040428  ],\n",
       "       [19.136904  , 21.059431  , 20.721912  , 19.869085  ,  7.2571416 ,\n",
       "        13.941229  , 28.884726  , 27.106995  ,  0.03359437,  1.0484893 ,\n",
       "        -0.97754955, 12.12734   , 12.716839  , 28.491669  ],\n",
       "       [18.968773  , 20.906147  , 21.460379  , 17.377382  ,  4.863486  ,\n",
       "        10.682313  , 27.186651  , 23.71751   , -1.7128265 ,  1.7405492 ,\n",
       "        -1.1221472 ,  8.642129  ,  9.399436  , 27.350985  ]],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-1029a5f6-eb5e-4d30-8a06-3298285b64a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1029a5f6-eb5e-4d30-8a06-3298285b64a7' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month</span></div><div class='xr-var-dims'>(month)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-1ac551aa-044b-482c-ac2c-d81dac34ee40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ac551aa-044b-482c-ac2c-d81dac34ee40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4515f39-5c64-41f0-8570-38049908274c' class='xr-var-data-in' type='checkbox'><label for='data-a4515f39-5c64-41f0-8570-38049908274c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-d9adbf59-57f4-4637-90c6-73bc8a9fea4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9adbf59-57f4-4637-90c6-73bc8a9fea4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16389597-d2ba-4a99-8c98-a57a20308d15' class='xr-var-data-in' type='checkbox'><label for='data-16389597-d2ba-4a99-8c98-a57a20308d15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>gridtype :</span></dt><dd>0</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>basin</span></div><div class='xr-var-dims'>(basin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 2.0 3.0 4.0 ... 12.0 53.0 56.0</div><input id='attrs-4acbf07d-b756-4bef-a4b9-48c1d2ffffe8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4acbf07d-b756-4bef-a4b9-48c1d2ffffe8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea0898b4-1a13-497c-aed0-dea44f35ae54' class='xr-var-data-in' type='checkbox'><label for='data-ea0898b4-1a13-497c-aed0-dea44f35ae54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11., 12., 53., 56.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67030027-f8e5-4363-8549-e64015d2c5fd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-67030027-f8e5-4363-8549-e64015d2c5fd' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'sst' (month: 12, basin: 14)>\n",
       "array([[18.931244  , 20.88606   , 22.068876  , 15.7806225 ,  2.9009485 ,\n",
       "         8.286119  , 25.862597  , 21.052422  , -1.7988946 ,  2.5364153 ,\n",
       "        -1.2113837 ,  5.99166   ,  6.69535   , 26.615591  ],\n",
       "       [18.998413  , 20.938007  , 22.466644  , 15.171556  ,  1.6216687 ,\n",
       "         7.475156  , 25.31563   , 20.009794  , -1.8000002 ,  2.86857   ,\n",
       "        -1.2622244 ,  4.981395  ,  5.473524  , 26.889442  ],\n",
       "       [19.013428  , 20.972063  , 22.608067  , 15.258743  ,  1.4993656 ,\n",
       "         7.793447  , 25.649214  , 20.699417  , -1.8000002 ,  2.6315544 ,\n",
       "        -1.2847868 ,  5.1045027 ,  5.522258  , 28.037973  ],\n",
       "       [18.989248  , 20.968798  , 22.381023  , 16.224312  ,  3.0491576 ,\n",
       "        10.017782  , 26.88303   , 23.203306  , -1.7996598 ,  2.094409  ,\n",
       "        -1.2763202 ,  6.663208  ,  9.4189415 , 29.374727  ],\n",
       "       [19.068415  , 21.018923  , 21.714952  , 18.613165  ,  6.4635086 ,\n",
       "        14.915698  , 28.640142  , 26.750372  , -1.7467502 ,  1.571553  ,\n",
       "        -1.1642531 ,  9.768522  , 15.095652  , 29.972607  ],\n",
       "       [19.352161  , 21.17309   , 20.790792  , 21.979132  , 11.794082  ,\n",
       "        20.411827  , 29.786642  , 29.794815  , -0.96558964,  1.1652179 ,\n",
       "        -0.8448692 , 14.277155  , 20.739882  , 29.463205  ],\n",
       "       [19.71806   , 21.479403  , 20.011818  , 24.690279  , 16.125217  ,\n",
       "        23.58809   , 30.706587  , 31.815105  ,  2.8862731 ,  0.8692938 ,\n",
       "        -0.30307108, 18.744436  , 24.158962  , 28.86987   ],\n",
       "       [19.959143  , 21.723642  , 19.603079  , 25.818441  , 17.186897  ,\n",
       "        24.277603  , 31.248007  , 32.692772  ,  5.3934736 ,  0.68534446,\n",
       "         0.16548847, 21.910128  , 24.577526  , 28.628706  ],\n",
       "       [19.816757  , 21.665964  , 19.646137  , 24.763577  , 14.3625765 ,\n",
       "        21.748938  , 31.174229  , 32.241535  ,  4.6783195 ,  0.6313895 ,\n",
       "         0.03611656, 20.365383  , 21.501966  , 28.853634  ],\n",
       "       [19.467312  , 21.347132  , 20.05091   , 22.60426   , 10.456942  ,\n",
       "        17.874405  , 30.591843  , 30.352285  ,  2.3623    ,  0.72350246,\n",
       "        -0.554342  , 16.454807  , 16.766832  , 29.040428  ],\n",
       "       [19.136904  , 21.059431  , 20.721912  , 19.869085  ,  7.2571416 ,\n",
       "        13.941229  , 28.884726  , 27.106995  ,  0.03359437,  1.0484893 ,\n",
       "        -0.97754955, 12.12734   , 12.716839  , 28.491669  ],\n",
       "       [18.968773  , 20.906147  , 21.460379  , 17.377382  ,  4.863486  ,\n",
       "        10.682313  , 27.186651  , 23.71751   , -1.7128265 ,  1.7405492 ,\n",
       "        -1.1221472 ,  8.642129  ,  9.399436  , 27.350985  ]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * month    (month) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "    Z        float32 0.0\n",
       "  * basin    (basin) float64 1.0 2.0 3.0 4.0 5.0 ... 10.0 11.0 12.0 53.0 56.0"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basin_mean_sst = ds_mm.sst.groupby(basin_surf_interp).mean()\n",
    "basin_mean_sst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = basin_mean_sst.to_dataframe()\n",
    "df = df.drop(columns=['Z'])\n",
    "df = df.reset_index().drop(columns=['month']).set_index('basin')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "tags": [
     "scroll-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1                 Atlantic Ocean\n",
       "2                 Pacific Ocean \n",
       "3                   Indian Ocean\n",
       "4              Mediterranean Sea\n",
       "5                     Baltic Sea\n",
       "6                      Black Sea\n",
       "7                        Red Sea\n",
       "8                   Persian Gulf\n",
       "9                     Hudson Bay\n",
       "10                Southern Ocean\n",
       "11                  Arctic Ocean\n",
       "12                  Sea of Japan\n",
       "13                      Kara Sea\n",
       "14                      Sulu Sea\n",
       "15                    Baffin Bay\n",
       "16            East Mediterranean\n",
       "17            West Mediterranean\n",
       "18                Sea of Okhotsk\n",
       "19                     Banda Sea\n",
       "20                 Caribbean Sea\n",
       "21                 Andaman Basin\n",
       "22               North Caribbean\n",
       "23                Gulf of Mexico\n",
       "24                  Beaufort Sea\n",
       "25               South China Sea\n",
       "26                   Barents Sea\n",
       "27                   Celebes Sea\n",
       "28                Aleutian Basin\n",
       "29                    Fiji Basin\n",
       "30          North American Basin\n",
       "31           West European Basin\n",
       "32        Southeast Indian Basin\n",
       "33                     Coral Sea\n",
       "34             East Indian Basin\n",
       "35          Central Indian Basin\n",
       "36      Southwest Atlantic Basin\n",
       "37      Southeast Atlantic Basin\n",
       "38       Southeast Pacific Basin\n",
       "39               Guatemala Basin\n",
       "40           East Caroline Basin\n",
       "41                Marianas Basin\n",
       "42                Philippine Sea\n",
       "43                   Arabian Sea\n",
       "44                   Chile Basin\n",
       "45                  Somali Basin\n",
       "46               Mascarene Basin\n",
       "47                  Crozet Basin\n",
       "48                  Guinea Basin\n",
       "49                  Brazil Basin\n",
       "50               Argentine Basin\n",
       "51                    Tasman Sea\n",
       "52         Atlantic Indian Basin\n",
       "53                   Caspian Sea\n",
       "54                   Sulu Sea II\n",
       "55               Venezuela Basin\n",
       "56                 Bay of Bengal\n",
       "57                      Java Sea\n",
       "58    East Indian Atlantic Basin\n",
       "dtype: object"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basin_names = basin_surf.attrs['CLIST'].split('\\n')\n",
    "basin_df = pd.Series(basin_names, index=np.arange(1, len(basin_names)+1))\n",
    "basin_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.join(basin_df.rename('basin_name'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = df.groupby('basin_name').mean().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='basin_name'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 402,
       "width": 368
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2.plot.bar(x='basin_name')"
   ]
  },
  {
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}