7 Basic xarray - opening multifile datasets.ipynb

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   "metadata": {},
   "source": [
    "# Opening multifile datasets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In many cases large datasets are spead over multiple files, so no individual file becomes too large, and operating on a subset of the data is easier without having to read the whole dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "xarray can open multiple files as a single xarray `Dataset` with the `open_mfdataset` command. Pass it either a list of files to open, or a wildcard string that matches the desired files. \n",
    "\n",
    "This is useful as it can skip wasteful steps of creating intermediate datasets which are aggregations of existing data. Just load it all up and select out what is required."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Start with the required imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Wildcards only work when accessing files on a local filesystem, for opendap it is necessary to  pass a list of urls. Below a list of urls are created from the individual filenames which are joined to a prefix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['http://dapds00.nci.org.au/thredds/dodsC/rr3/CMIP5/output1/CSIRO-BOM/ACCESS1-3/historical/day/atmos/day/r1i1p1/latest/tas/tas_day_ACCESS1-3_historical_r1i1p1_18500101-18741231.nc',\n",
       " 'http://dapds00.nci.org.au/thredds/dodsC/rr3/CMIP5/output1/CSIRO-BOM/ACCESS1-3/historical/day/atmos/day/r1i1p1/latest/tas/tas_day_ACCESS1-3_historical_r1i1p1_18750101-18991231.nc',\n",
       " 'http://dapds00.nci.org.au/thredds/dodsC/rr3/CMIP5/output1/CSIRO-BOM/ACCESS1-3/historical/day/atmos/day/r1i1p1/latest/tas/tas_day_ACCESS1-3_historical_r1i1p1_19000101-19241231.nc']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files = ['tas_day_ACCESS1-3_historical_r1i1p1_18500101-18741231.nc', \n",
    "        'tas_day_ACCESS1-3_historical_r1i1p1_18750101-18991231.nc',\n",
    "        'tas_day_ACCESS1-3_historical_r1i1p1_19000101-19241231.nc']\n",
    "prefix = 'http://dapds00.nci.org.au/thredds/dodsC/rr3/CMIP5/output1/CSIRO-BOM/ACCESS1-3/historical/day/atmos/day/r1i1p1/latest/tas/'\n",
    "urls = [prefix+file for file in files]\n",
    "urls"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This list is then passed to `open_mfdataset`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xarray.open_mfdataset(urls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting dataset is pretty big, the `nbytes` attribute gives the size of the dataset in bytes. In this case it is over 3GB. The `tas` variable has 27393 daily time steps. It doesn't take a long time to load the dataset, as it is only metadata, but loading the underlying data could be time consuming depending on how much needs to be read."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.198847672"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.nbytes/1000**3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (bnds: 2, lat: 145, lon: 192, time: 27393)\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1850-01-01T12:00:00 ... 1924-12-31T12:00:00\n",
       "  * lat        (lat) float64 -90.0 -88.75 -87.5 -86.25 ... 86.25 87.5 88.75 90.0\n",
       "  * lon        (lon) float64 0.0 1.875 3.75 5.625 ... 352.5 354.4 356.2 358.1\n",
       "    height     float64 1.5\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    time_bnds  (time, bnds) datetime64[ns] dask.array&lt;chunksize=(9131, 2), meta=np.ndarray&gt;\n",
       "    lat_bnds   (time, lat, bnds) float64 dask.array&lt;chunksize=(9131, 145, 2), meta=np.ndarray&gt;\n",
       "    lon_bnds   (time, lon, bnds) float64 dask.array&lt;chunksize=(9131, 192, 2), meta=np.ndarray&gt;\n",
       "    tas        (time, lat, lon) float32 dask.array&lt;chunksize=(9131, 145, 192), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    institution:                     CSIRO (Commonwealth Scientific and Indus...\n",
       "    institute_id:                    CSIRO-BOM\n",
       "    experiment_id:                   historical\n",
       "    source:                          ACCESS1.3 2011. Atmosphere: AGCM v1.0 (N...\n",
       "    model_id:                        ACCESS1.3\n",
       "    forcing:                         GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2,...\n",
       "    parent_experiment_id:            piControl\n",
       "    parent_experiment_rip:           r1i1p1\n",
       "    branch_time:                     90945.0\n",
       "    contact:                         The ACCESS wiki: http://wiki.csiro.au/co...\n",
       "    history:                         CMIP5 compliant file produced from raw A...\n",
       "    references:                      See http://wiki.csiro.au/confluence/disp...\n",
       "    initialization_method:           1\n",
       "    physics_version:                 1\n",
       "    tracking_id:                     d9824016-bde8-4883-b111-9385b3d023cd\n",
       "    version_number:                  v20130227\n",
       "    product:                         output\n",
       "    experiment:                      historical\n",
       "    frequency:                       day\n",
       "    creation_date:                   2013-02-26T01:40:45Z\n",
       "    Conventions:                     CF-1.4\n",
       "    project_id:                      CMIP5\n",
       "    table_id:                        Table day (01 February 2012) b6353e99198...\n",
       "    title:                           ACCESS1.3 model output prepared for CMIP...\n",
       "    parent_experiment:               pre-industrial control\n",
       "    modeling_realm:                  atmos\n",
       "    realization:                     1\n",
       "    cmor_version:                    2.8.0\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-c18ca46e-b97e-433d-a347-5860777ceac3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c18ca46e-b97e-433d-a347-5860777ceac3' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 145</li><li><span class='xr-has-index'>lon</span>: 192</li><li><span class='xr-has-index'>time</span>: 27393</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ee2ece62-74b7-437b-924e-6ce35c8d4409' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ee2ece62-74b7-437b-924e-6ce35c8d4409' 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'>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'>1850-01-01T12:00:00 ... 1924-12-...</div><input id='attrs-8f9a06da-b90c-4ddd-ba77-c09022f2f4b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f9a06da-b90c-4ddd-ba77-c09022f2f4b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e58673de-87e1-43c5-87a8-5679a72a0f86' class='xr-var-data-in' type='checkbox'><label for='data-e58673de-87e1-43c5-87a8-5679a72a0f86' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-01T12:00:00.000000000&#x27;, &#x27;1850-01-02T12:00:00.000000000&#x27;,\n",
       "       &#x27;1850-01-03T12:00:00.000000000&#x27;, ..., &#x27;1924-12-29T12:00:00.000000000&#x27;,\n",
       "       &#x27;1924-12-30T12:00:00.000000000&#x27;, &#x27;1924-12-31T12:00:00.000000000&#x27;],\n",
       "      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'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -87.5 ... 88.75 90.0</div><input id='attrs-b9215d48-a891-482b-be98-fce3e8e7f072' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9215d48-a891-482b-be98-fce3e8e7f072' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73a384fd-507d-47b3-90ca-4a93b22fb98c' class='xr-var-data-in' type='checkbox'><label for='data-73a384fd-507d-47b3-90ca-4a93b22fb98c' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-90.  , -88.75, -87.5 , -86.25, -85.  , -83.75, -82.5 , -81.25, -80.  ,\n",
       "       -78.75, -77.5 , -76.25, -75.  , -73.75, -72.5 , -71.25, -70.  , -68.75,\n",
       "       -67.5 , -66.25, -65.  , -63.75, -62.5 , -61.25, -60.  , -58.75, -57.5 ,\n",
       "       -56.25, -55.  , -53.75, -52.5 , -51.25, -50.  , -48.75, -47.5 , -46.25,\n",
       "       -45.  , -43.75, -42.5 , -41.25, -40.  , -38.75, -37.5 , -36.25, -35.  ,\n",
       "       -33.75, -32.5 , -31.25, -30.  , -28.75, -27.5 , -26.25, -25.  , -23.75,\n",
       "       -22.5 , -21.25, -20.  , -18.75, -17.5 , -16.25, -15.  , -13.75, -12.5 ,\n",
       "       -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,  -5.  ,  -3.75,  -2.5 ,  -1.25,\n",
       "         0.  ,   1.25,   2.5 ,   3.75,   5.  ,   6.25,   7.5 ,   8.75,  10.  ,\n",
       "        11.25,  12.5 ,  13.75,  15.  ,  16.25,  17.5 ,  18.75,  20.  ,  21.25,\n",
       "        22.5 ,  23.75,  25.  ,  26.25,  27.5 ,  28.75,  30.  ,  31.25,  32.5 ,\n",
       "        33.75,  35.  ,  36.25,  37.5 ,  38.75,  40.  ,  41.25,  42.5 ,  43.75,\n",
       "        45.  ,  46.25,  47.5 ,  48.75,  50.  ,  51.25,  52.5 ,  53.75,  55.  ,\n",
       "        56.25,  57.5 ,  58.75,  60.  ,  61.25,  62.5 ,  63.75,  65.  ,  66.25,\n",
       "        67.5 ,  68.75,  70.  ,  71.25,  72.5 ,  73.75,  75.  ,  76.25,  77.5 ,\n",
       "        78.75,  80.  ,  81.25,  82.5 ,  83.75,  85.  ,  86.25,  87.5 ,  88.75,\n",
       "        90.  ])</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'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.875 3.75 ... 356.2 358.1</div><input id='attrs-465ad0b0-d73c-42da-99f2-838dd18e7dbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-465ad0b0-d73c-42da-99f2-838dd18e7dbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dfd480f-721c-4184-a417-3e9df3288b60' class='xr-var-data-in' type='checkbox'><label for='data-7dfd480f-721c-4184-a417-3e9df3288b60' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.   ,   1.875,   3.75 ,   5.625,   7.5  ,   9.375,  11.25 ,  13.125,\n",
       "        15.   ,  16.875,  18.75 ,  20.625,  22.5  ,  24.375,  26.25 ,  28.125,\n",
       "        30.   ,  31.875,  33.75 ,  35.625,  37.5  ,  39.375,  41.25 ,  43.125,\n",
       "        45.   ,  46.875,  48.75 ,  50.625,  52.5  ,  54.375,  56.25 ,  58.125,\n",
       "        60.   ,  61.875,  63.75 ,  65.625,  67.5  ,  69.375,  71.25 ,  73.125,\n",
       "        75.   ,  76.875,  78.75 ,  80.625,  82.5  ,  84.375,  86.25 ,  88.125,\n",
       "        90.   ,  91.875,  93.75 ,  95.625,  97.5  ,  99.375, 101.25 , 103.125,\n",
       "       105.   , 106.875, 108.75 , 110.625, 112.5  , 114.375, 116.25 , 118.125,\n",
       "       120.   , 121.875, 123.75 , 125.625, 127.5  , 129.375, 131.25 , 133.125,\n",
       "       135.   , 136.875, 138.75 , 140.625, 142.5  , 144.375, 146.25 , 148.125,\n",
       "       150.   , 151.875, 153.75 , 155.625, 157.5  , 159.375, 161.25 , 163.125,\n",
       "       165.   , 166.875, 168.75 , 170.625, 172.5  , 174.375, 176.25 , 178.125,\n",
       "       180.   , 181.875, 183.75 , 185.625, 187.5  , 189.375, 191.25 , 193.125,\n",
       "       195.   , 196.875, 198.75 , 200.625, 202.5  , 204.375, 206.25 , 208.125,\n",
       "       210.   , 211.875, 213.75 , 215.625, 217.5  , 219.375, 221.25 , 223.125,\n",
       "       225.   , 226.875, 228.75 , 230.625, 232.5  , 234.375, 236.25 , 238.125,\n",
       "       240.   , 241.875, 243.75 , 245.625, 247.5  , 249.375, 251.25 , 253.125,\n",
       "       255.   , 256.875, 258.75 , 260.625, 262.5  , 264.375, 266.25 , 268.125,\n",
       "       270.   , 271.875, 273.75 , 275.625, 277.5  , 279.375, 281.25 , 283.125,\n",
       "       285.   , 286.875, 288.75 , 290.625, 292.5  , 294.375, 296.25 , 298.125,\n",
       "       300.   , 301.875, 303.75 , 305.625, 307.5  , 309.375, 311.25 , 313.125,\n",
       "       315.   , 316.875, 318.75 , 320.625, 322.5  , 324.375, 326.25 , 328.125,\n",
       "       330.   , 331.875, 333.75 , 335.625, 337.5  , 339.375, 341.25 , 343.125,\n",
       "       345.   , 346.875, 348.75 , 350.625, 352.5  , 354.375, 356.25 , 358.125])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-e92aff71-f67d-4006-802c-2828dcb8d313' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e92aff71-f67d-4006-802c-2828dcb8d313' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5e0da65-bd9f-456b-9fdd-cd6b56164999' class='xr-var-data-in' type='checkbox'><label for='data-c5e0da65-bd9f-456b-9fdd-cd6b56164999' 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>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-20e6a079-4f6a-48e0-8258-b4ea952ffcff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-20e6a079-4f6a-48e0-8258-b4ea952ffcff' class='xr-section-summary' >Data variables: <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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(9131, 2), meta=np.ndarray&gt;</div><input id='attrs-d32798ad-9e8c-47ed-9fc3-205ebb30d078' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d32798ad-9e8c-47ed-9fc3-205ebb30d078' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65b9a151-245b-4264-a04c-07bb1153354f' class='xr-var-data-in' type='checkbox'><label for='data-65b9a151-245b-4264-a04c-07bb1153354f' 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'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(time, lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(9131, 192, 2), meta=np.ndarray&gt;</div><input id='attrs-f74227c9-05a8-4039-9c94-77d016d0b03b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f74227c9-05a8-4039-9c94-77d016d0b03b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d67c5daa-1be7-48e8-9675-370d1367ae99' class='xr-var-data-in' type='checkbox'><label for='data-d67c5daa-1be7-48e8-9675-370d1367ae99' 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'><table>\n",
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       "    branch_time:                     90945.0\n",
       "    contact:                         The ACCESS wiki: http://wiki.csiro.au/co...\n",
       "    history:                         CMIP5 compliant file produced from raw A...\n",
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       "    table_id:                        Table day (01 February 2012) b6353e99198...\n",
       "    title:                           ACCESS1.3 model output prepared for CMIP...\n",
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   "source": [
    "Note also that extra information in the data variables section\n",
    "\n",
    "`dask.array<shape=(27393, 145, 192), chunksize=(9131, 145, 192)>`\n",
    "\n",
    "Dask is beyond the scope of this introduction, but xarray has assigned a dask chunking to the data variables as they are split across files. In particular the `time` dimension is split into three with 9131 values per file.\n",
    "\n",
    "Regardless of chunking, this data set can be used as if it were a single file for the purposes of manipulations and calculations."
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   "source": [
    "Now it is possible to specify a spatial subset containing Australia, using `sel`"
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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       ".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;tas&#x27; (time: 27393, lat: 37, lon: 27)&gt;\n",
       "dask.array&lt;getitem, shape=(27393, 37, 27), dtype=float32, chunksize=(9131, 37, 27), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1850-01-01T12:00:00 ... 1924-12-31T12:00:00\n",
       "  * lat      (lat) float64 -50.0 -48.75 -47.5 -46.25 ... -8.75 -7.5 -6.25 -5.0\n",
       "  * lon      (lon) float64 110.6 112.5 114.4 116.2 ... 153.8 155.6 157.5 159.4\n",
       "    height   float64 1.5\n",
       "Attributes:\n",
       "    standard_name:     air_temperature\n",
       "    long_name:         Near-Surface Air Temperature\n",
       "    units:             K\n",
       "    cell_methods:      time: mean\n",
       "    cell_measures:     area: areacella\n",
       "    history:           2013-02-26T01:40:45Z altered by CMOR: Treated scalar d...\n",
       "    associated_files:  baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'tas'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 27393</li><li><span class='xr-has-index'>lat</span>: 37</li><li><span class='xr-has-index'>lon</span>: 27</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-9eff5249-a9c7-47b7-a5f1-46ec081eefde' class='xr-array-in' type='checkbox' checked><label for='section-9eff5249-a9c7-47b7-a5f1-46ec081eefde' 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>dask.array&lt;chunksize=(9131, 37, 27), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 109.46 MB </td> <td> 36.49 MB </td></tr>\n",
       "    <tr><th> Shape </th><td> (27393, 37, 27) </td> <td> (9131, 37, 27) </td></tr>\n",
       "    <tr><th> Count </th><td> 12 Tasks </td><td> 3 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
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       "  <text x=\"35.294118\" y=\"80.706734\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,80.706734)\">27393</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-2d8ff544-50fe-43b2-b505-68725d10d04b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2d8ff544-50fe-43b2-b505-68725d10d04b' 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'>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'>1850-01-01T12:00:00 ... 1924-12-...</div><input id='attrs-736752ca-68f3-4cbc-a927-bf836e52e045' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-736752ca-68f3-4cbc-a927-bf836e52e045' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad00169c-a192-4d7b-af87-1150061ef353' class='xr-var-data-in' type='checkbox'><label for='data-ad00169c-a192-4d7b-af87-1150061ef353' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1850-01-01T12:00:00.000000000&#x27;, &#x27;1850-01-02T12:00:00.000000000&#x27;,\n",
       "       &#x27;1850-01-03T12:00:00.000000000&#x27;, ..., &#x27;1924-12-29T12:00:00.000000000&#x27;,\n",
       "       &#x27;1924-12-30T12:00:00.000000000&#x27;, &#x27;1924-12-31T12:00:00.000000000&#x27;],\n",
       "      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'>float64</div><div class='xr-var-preview xr-preview'>-50.0 -48.75 -47.5 ... -6.25 -5.0</div><input id='attrs-2ce460cb-7a86-45f1-9841-d85a17cb352f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ce460cb-7a86-45f1-9841-d85a17cb352f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c28d6c18-4629-4fc0-8701-8fae6be48252' class='xr-var-data-in' type='checkbox'><label for='data-c28d6c18-4629-4fc0-8701-8fae6be48252' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-50.  , -48.75, -47.5 , -46.25, -45.  , -43.75, -42.5 , -41.25, -40.  ,\n",
       "       -38.75, -37.5 , -36.25, -35.  , -33.75, -32.5 , -31.25, -30.  , -28.75,\n",
       "       -27.5 , -26.25, -25.  , -23.75, -22.5 , -21.25, -20.  , -18.75, -17.5 ,\n",
       "       -16.25, -15.  , -13.75, -12.5 , -11.25, -10.  ,  -8.75,  -7.5 ,  -6.25,\n",
       "        -5.  ])</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'>float64</div><div class='xr-var-preview xr-preview'>110.6 112.5 114.4 ... 157.5 159.4</div><input id='attrs-ba8877cf-a2a8-41f7-99cb-bb29ba6ca207' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba8877cf-a2a8-41f7-99cb-bb29ba6ca207' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba80e695-9f90-43a9-88e9-17e847c337bf' class='xr-var-data-in' type='checkbox'><label for='data-ba80e695-9f90-43a9-88e9-17e847c337bf' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([110.625, 112.5  , 114.375, 116.25 , 118.125, 120.   , 121.875, 123.75 ,\n",
       "       125.625, 127.5  , 129.375, 131.25 , 133.125, 135.   , 136.875, 138.75 ,\n",
       "       140.625, 142.5  , 144.375, 146.25 , 148.125, 150.   , 151.875, 153.75 ,\n",
       "       155.625, 157.5  , 159.375])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-82ccf81f-bc9c-4557-86e9-22e7efb6b9bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82ccf81f-bc9c-4557-86e9-22e7efb6b9bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecfc1da2-e1e1-4892-9a37-16c41fb98633' class='xr-var-data-in' type='checkbox'><label for='data-ecfc1da2-e1e1-4892-9a37-16c41fb98633' 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>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>standard_name :</span></dt><dd>height</dd></dl></div><div class='xr-var-data'><pre>array(1.5)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e33d7c48-f236-4ee3-a5d6-5a0542201fb3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e33d7c48-f236-4ee3-a5d6-5a0542201fb3' 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>standard_name :</span></dt><dd>air_temperature</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd><dt><span>history :</span></dt><dd>2013-02-26T01:40:45Z altered by CMOR: Treated scalar dimension: &#x27;height&#x27;. 2013-02-26T01:40:45Z altered by CMOR: replaced missing value flag (-1.07374e+09) with standard missing value (1e+20).</dd><dt><span>associated_files :</span></dt><dd>baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation gridspecFile: gridspec_atmos_fx_ACCESS1-3_historical_r0i0p0.nc areacella: areacella_fx_ACCESS1-3_historical_r0i0p0.nc</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'tas' (time: 27393, lat: 37, lon: 27)>\n",
       "dask.array<getitem, shape=(27393, 37, 27), dtype=float32, chunksize=(9131, 37, 27), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * time     (time) datetime64[ns] 1850-01-01T12:00:00 ... 1924-12-31T12:00:00\n",
       "  * lat      (lat) float64 -50.0 -48.75 -47.5 -46.25 ... -8.75 -7.5 -6.25 -5.0\n",
       "  * lon      (lon) float64 110.6 112.5 114.4 116.2 ... 153.8 155.6 157.5 159.4\n",
       "    height   float64 1.5\n",
       "Attributes:\n",
       "    standard_name:     air_temperature\n",
       "    long_name:         Near-Surface Air Temperature\n",
       "    units:             K\n",
       "    cell_methods:      time: mean\n",
       "    cell_measures:     area: areacella\n",
       "    history:           2013-02-26T01:40:45Z altered by CMOR: Treated scalar d...\n",
       "    associated_files:  baseURL: http://cmip-pcmdi.llnl.gov/CMIP5/dataLocation..."
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tas_aus = ds.tas.sel(lat=slice(-50,-5), lon=slice(110,160))\n",
    "tas_aus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Confirm it is correct by plotting the first time point"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f9e40055ac0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tas_aus.isel(time=0).plot(size=6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So `tas_aus` is a 75 year daily temperature dataset of Australia. Any calculation can now be performed, e.g. analysing variability in space, time, season ... there are many possibilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:analysis3-20.10]",
   "language": "python",
   "name": "conda-env-analysis3-20.10-py"
  },
  "language_info": {
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