formatting correction to AWS Cloud tutorial

Author: andrewdelman

ECCO-ACCESS/Cloud_access_to_ECCO_datasets/Tutorial_AWS_Cloud_getting_started.ipynb

@@ -1578,8 +1578,7 @@
        "</svg>\n",
        "        </td>\n",
        "    </tr>\n",
-       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f32cc987-2e88-4d70-a5cb-55efa53fba6b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f32cc987-2e88-4d70-a5cb-55efa53fba6b' class='xr-section-summary' >Data variables: <span>(2)</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>THETA</span></div><div class='xr-var-dims'>(time, k, tile, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-017bc9fe-1330-4753-abf8-ffb7f1e50a27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-017bc9fe-1330-4753-abf8-ffb7f1e50a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfdbc550-0143-4d88-8d6a-79b2ba511441' class='xr-var-data-in' type='checkbox'><label for='data-bfdbc550-0143-4d88-8d6a-79b2ba511441' 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>Potential temperature </dd><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>coverage_content_type :</span></dt><dd>modelResult</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>comment :</span></dt><dd>Sea water potential temperature is the temperature a parcel of sea water would have if moved adiabatically to sea level pressure. Note: the equation of state is a modified UNESCO formula by Jackett and McDougall (1995), which uses the model variable potential temperature as input assuming a horizontally and temporally constant pressure of $p_0=-g \r",
-       "ho_{0} z$.</dd><dt><span>valid_min :</span></dt><dd>-2.2909388542175293</dd><dt><span>valid_max :</span></dt><dd>36.032955169677734</dd></dl></div><div class='xr-var-data'><table>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-f32cc987-2e88-4d70-a5cb-55efa53fba6b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f32cc987-2e88-4d70-a5cb-55efa53fba6b' class='xr-section-summary' >Data variables: <span>(2)</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>THETA</span></div><div class='xr-var-dims'>(time, k, tile, j, i)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-017bc9fe-1330-4753-abf8-ffb7f1e50a27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-017bc9fe-1330-4753-abf8-ffb7f1e50a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfdbc550-0143-4d88-8d6a-79b2ba511441' class='xr-var-data-in' type='checkbox'><label for='data-bfdbc550-0143-4d88-8d6a-79b2ba511441' 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>Potential temperature </dd><dt><span>units :</span></dt><dd>degree_C</dd><dt><span>coverage_content_type :</span></dt><dd>modelResult</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd><dt><span>comment :</span></dt><dd>Sea water potential temperature is the temperature a parcel of sea water would have if moved adiabatically to sea level pressure. Note: the equation of state is a modified UNESCO formula by Jackett and McDougall (1995), which uses the model variable potential temperature as input assuming a horizontally and temporally constant pressure of $p_0=-g \\rho_{0} z$.</dd><dt><span>valid_min :</span></dt><dd>-2.2909388542175293</dd><dt><span>valid_max :</span></dt><dd>36.032955169677734</dd></dl></div><div class='xr-var-data'><table>\n",
        "    <tr>\n",
        "        <td>\n",
        "            <table style=\"border-collapse: collapse;\">\n",
@@ -2563,7 +2562,7 @@
    "source": [
     "In this case opening the files took about the same amount of time, and the additional overhead from the `distributed` client slowed down the computation (note the warning above about sending a large graph). So here it would be better to not use `distributed` for the computation.\n",
     "\n",
-    "### Method 2: Download S3 files to local instance (get)\n",
+    "### Method 2: Download (get) S3 files to local instance\n",
     "\n",
     "While the ability to open files from S3 without using up disk storage on your instance is useful, it is often more convenient to just download a copy of the files you need to your instance. As you might expect, since you are already on the cloud it is substantially quicker to download the files than it would be to your own machine, and computations are also more efficient when the source data are already local to your instance."
    ]