Typo

docs/_build_html/_sources/index.rst.txt

@@ -284,7 +284,7 @@ After you run the cell, you should see something like this.
 .. image:: /_static/read_csv.png
 
 
-It is a ``DataFrame`` where ``pandas`` has structured the CSV data into rows and columns, just like Excel or another spreadsheet software might. The advantage offered here is that rather than manipulating the data through a haphazard series of clicks and keypunches, we will be gradually grinding down the data using a computer programming script that is 100% transparent and reproducible.
+It is a ``DataFrame`` where ``pandas`` has structured the CSV data into rows and columns, just like Excel or other spreadsheet software might. The advantage offered here is that rather than manipulating the data through a haphazard series of clicks and keypunches, we will be gradually grinding down the data using a computer programming script that is 100% transparent and reproducible.
 
 In order to do that, we need to store our ``DataFrame`` so it can be reused in subsequent cells. We can do this by saving in a `"variable" <https://en.wikipedia.org/wiki/Variable_(computer_science)>`_, which is a fancy computer programming word for a named shortcut where we save our work as we go.
 

docs/_build_html/index.html

@@ -329,7 +329,7 @@ <h2>Act 3: Hello data<a class="headerlink" href="#act-3-hello-data" title="Perma
 </div>
 <p>After you run the cell, you should see something like this.</p>
 <img alt="_images/read_csv.png" src="_images/read_csv.png" />
-<p>It is a <code class="docutils literal"><span class="pre">DataFrame</span></code> where <code class="docutils literal"><span class="pre">pandas</span></code> has structured the CSV data into rows and columns, just like Excel or another spreadsheet software might. The advantage offered here is that rather than manipulating the data through a haphazard series of clicks and keypunches, we will be gradually grinding down the data using a computer programming script that is 100% transparent and reproducible.</p>
+<p>It is a <code class="docutils literal"><span class="pre">DataFrame</span></code> where <code class="docutils literal"><span class="pre">pandas</span></code> has structured the CSV data into rows and columns, just like Excel or other spreadsheet software might. The advantage offered here is that rather than manipulating the data through a haphazard series of clicks and keypunches, we will be gradually grinding down the data using a computer programming script that is 100% transparent and reproducible.</p>
 <p>In order to do that, we need to store our <code class="docutils literal"><span class="pre">DataFrame</span></code> so it can be reused in subsequent cells. We can do this by saving in a <a class="reference external" href="https://en.wikipedia.org/wiki/Variable_(computer_science)">&#8220;variable&#8221;</a>, which is a fancy computer programming word for a named shortcut where we save our work as we go.</p>
 <p>Go back to your initial cell and change it to this. Then rerun it.</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">props</span> <span class="o">=</span> <span class="n">pandas</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">&quot;./docs/_static/prop-committees.csv&quot;</span><span class="p">)</span>

docs/index.rst

@@ -284,7 +284,7 @@ After you run the cell, you should see something like this.
 .. image:: /_static/read_csv.png
 
 
-It is a ``DataFrame`` where ``pandas`` has structured the CSV data into rows and columns, just like Excel or another spreadsheet software might. The advantage offered here is that rather than manipulating the data through a haphazard series of clicks and keypunches, we will be gradually grinding down the data using a computer programming script that is 100% transparent and reproducible.
+It is a ``DataFrame`` where ``pandas`` has structured the CSV data into rows and columns, just like Excel or other spreadsheet software might. The advantage offered here is that rather than manipulating the data through a haphazard series of clicks and keypunches, we will be gradually grinding down the data using a computer programming script that is 100% transparent and reproducible.
 
 In order to do that, we need to store our ``DataFrame`` so it can be reused in subsequent cells. We can do this by saving in a `"variable" <https://en.wikipedia.org/wiki/Variable_(computer_science)>`_, which is a fancy computer programming word for a named shortcut where we save our work as we go.