push website: david edits to module 1 and module 2

Author: rsokl

docs/.doctrees/Module1_GettingStartedWithPython/GettingStartedWithPython.doctree

@@ -430,14 +430,14 @@ <h2>What is Python?<a class="headerlink" href="#What-is-Python?" title="Permalin
 <h2>Python Scripts<a class="headerlink" href="#Python-Scripts" title="Permalink to this headline">¶</a></h2>
 <p>You can save the the valid code from the preceding section in a text
 file using a simple text editor, and <em>voilà</em> you have written a <strong>Python
-script</strong>: a text file whose contents is Python code. It is standard to
-save this text file using the suffix <code class="docutils literal"><span class="pre">.py</span></code> (e.g. <code class="docutils literal"><span class="pre">my_code.py</span></code>),
-rather than the familiar <code class="docutils literal"><span class="pre">.txt</span></code> (e.g. <code class="docutils literal"><span class="pre">my_text.txt</span></code>). There is
-nothing special about the <code class="docutils literal"><span class="pre">.py</span></code> suffix other than it helps to
-differentiate files that contain Python code from run-of-the-mill text
-files, which contain plain English.</p>
+script</strong>: a text file containing Python code. It is standard to save
+this text file using the suffix <code class="docutils literal"><span class="pre">.py</span></code> (e.g. <code class="docutils literal"><span class="pre">my_code.py</span></code>), rather
+than the familiar <code class="docutils literal"><span class="pre">.txt</span></code> (e.g. <code class="docutils literal"><span class="pre">my_text.txt</span></code>). There is nothing
+special about the <code class="docutils literal"><span class="pre">.py</span></code> suffix; it simply helps differentiate files
+that contain Python code from run-of-the-mill text files, which contain
+plain English.</p>
 <p>Although you can use simple text editors to write Python scripts
-(e.g.&nbsp;notepad (Win), TextEdit (Mac), vim (Linux)), there are much more
+(e.g.&nbsp;notepad (Win), TextEdit (Mac), nano (Linux)), there are much more
 sophisticated editors that provide an “integrated development
 environment” (IDE) for writing code. An IDE, configured to support
 Python, will warn you if you have written code that violates Python’s
@@ -486,7 +486,7 @@ <h2>What is a Python Interpreter and What Does it Mean to “Install Python”?<
 <div class="admonition warning">
 <p class="first fa fa-exclamation-circle"><strong>About Installing Python</strong>:</p>
 <p class="last">Do not download and install Python from python.org. There isn’t anything
-wrong with this, however a later section will provide you with explicit
+wrong with this, but a later section will provide you with explicit
 instructions for installing Python on your machine.</p>
 </div>
 <p>If you “install Python on your computer” from
@@ -522,7 +522,7 @@ <h2>What is a Python Interpreter and What Does it Mean to “Install Python”?<
 <p>It may be confusing to think that the Python language is interpreted by
 using a program written in another language. How, then, is that language
 interpreted? The answer, in the case of CPython, is that C code need not
-be interpreted; programs exist for Windows, Macs, and Linux that can
+be interpreted; programs exist for Windows, Mac, and Linux that can
 translate C code directly into machine instructions.</p>
 </div>
 <div class="section" id="Why-Python?">
@@ -531,7 +531,7 @@ <h2>Why Python?<a class="headerlink" href="#Why-Python?" title="Permalink to thi
 likely the <a class="reference external" href="https://cacm.acm.org/blogs/blog-cacm/176450-python-is-now-the-most-popular-introductory-teaching-language-at-top-u-s-universities/fulltext">most popular introductory language at
 universities</a>.
 First and foremost, its syntax is designed to be intuitive and readable.
-For example, following Python code:</p>
+For example, the following Python code:</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="k">print</span><span class="p">(</span><span class="s2">&quot;Hello world&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
@@ -540,7 +540,7 @@ <h2>Why Python?<a class="headerlink" href="#Why-Python?" title="Permalink to thi
 
 <span class="kt">int</span> <span class="nf">main</span><span class="p">()</span>
 <span class="p">{</span>
-    <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;Hello world&quot;</span><span class="p">;</span>
+    <span class="n">std</span><span class="o">::</span><span class="n">cout</span> <span class="o">&lt;&lt;</span> <span class="s">&quot;Hello world&quot;</span> <span class="o">&lt;&lt;</span> <span class="n">std</span><span class="o">::</span><span class="n">endl</span><span class="p">;</span>
     <span class="k">return</span> <span class="mi">0</span><span class="p">;</span>
 <span class="p">}</span>
 </pre></div>

docs/.doctrees/Module1_GettingStartedWithPython/Getting_Started_With_IDEs_and_Notebooks.doctree

@@ -223,9 +223,9 @@ <h2>What You Will Learn<a class="headerlink" href="#What-You-Will-Learn" title="
 it directly in your computer’s terminal.</li>
 <li>The IPython shell is a much nicer version of the Python shell - it
 provides syntax highlighting, autocompletion, and other features.</li>
-<li>Jupyter notebook is a powerful tool for prototyping and experimenting
-with code, as well as visualizing data and writing nicely-formatted
-text. We will be using this throughout the course.</li>
+<li>The Jupyter Notebook is a powerful tool for prototyping and
+experimenting with code, as well as visualizing data and writing
+nicely-formatted text. We will be using this throughout the course.</li>
 </ul>
 </div>
 <div class="section" id="Integrated-Development-Environments">
@@ -237,7 +237,7 @@ <h2>Integrated Development Environments<a class="headerlink" href="#Integrated-D
 a simple text editor to write Python code (and it is a big mistake use
 word-processing software, like Microsoft Word, to do so). Instead we
 want an “integrated development environment” (IDE) that will facilitate
-our code writing.</p>
+our code-writing.</p>
 <p>First and foremost, a good IDE will provide a text editor that will:</p>
 <ul class="simple">
 <li>check your code for syntax errors (a misspelled function name, a
@@ -282,7 +282,7 @@ <h3>Recommended IDEs<a class="headerlink" href="#Recommended-IDEs" title="Permal
 <li>works with many different languages, so you only need to familiarize
 yourself with one IDE</li>
 <li>a huge number of extensions can be downloaded to add functionality to
-the editor, these are created by a large community of open-source
+the editor; these are created by a large community of open-source
 developers.</li>
 </ul>
 <p><strong>Cons</strong></p>

docs/.doctrees/Module1_GettingStartedWithPython/Informal_Intro_Python.doctree

@@ -397,7 +397,7 @@ <h1>An Informal Introduction to Python<a class="headerlink" href="#An-Informal-I
 doing so, we will learn about the Python standard library, and how to
 make use of its modules, like the math module. IPython’s autocompletion
 and documentation-display utilities will provide a nice means for
-exploring the library and the functionality built-in to the different
+exploring the library and the functionality built into the different
 types of Python objects. A quick glimpse at Python’s strings and lists
 will hint at the common interface Python provides for working with
 sequences of objects, while highlighting some of the nice features of
@@ -681,7 +681,7 @@ <h2>Messing with Strings<a class="headerlink" href="#Messing-with-Strings" title
 </div>
 <p>Of course, strings are useful beyond merely containing text! Let’s
 explore some ways to manipulate strings. First, we’ll write a string and
-assign a variable named <code class="docutils literal"><span class="pre">sentence</span></code> to it:</p>
+assign it to a variable named <code class="docutils literal"><span class="pre">sentence</span></code>:</p>
 <div class="nbinput nblast docutils container">
 <div class="prompt highlight-none"><div class="highlight"><pre>
 <span></span>In [13]:
@@ -860,7 +860,7 @@ <h2>Messing with Strings<a class="headerlink" href="#Messing-with-Strings" title
 </div>
 <div class="section" id="Playing-with-Lists">
 <h2>Playing with Lists<a class="headerlink" href="#Playing-with-Lists" title="Permalink to this headline">¶</a></h2>
-<p>A list is one of several types of containers that are built-in to
+<p>A list is one of several types of containers that are built into
 Python’s standard library. It can hold a sequence of Python objects. We
 can create a list of numbers:</p>
 <div class="nbinput docutils container">
@@ -980,8 +980,8 @@ <h2>Playing with Lists<a class="headerlink" href="#Playing-with-Lists" title="Pe
 </pre></div>
 </div>
 </div>
-<p>Negative integers can be used index relative to the end (right-side) of
-the list.</p>
+<p>Negative integers can be used to index relative to the end (right-side)
+of the list.</p>
 <div class="nbinput docutils container">
 <div class="prompt highlight-none"><div class="highlight"><pre>
 <span></span>In [13]:

docs/.doctrees/Module1_GettingStartedWithPython/Installing_Python.doctree

@@ -214,13 +214,13 @@ <h1>Installing Python<a class="headerlink" href="#Installing-Python" title="Perm
 and other useful Python libraries on your machine via the Anaconda
 platform. Installing the Anaconda platform will install the following:</p>
 <ul class="simple">
-<li>Python, specifically the CPython interpreter that we discussed in the
+<li>Python; specifically the CPython interpreter that we discussed in the
 previous section.</li>
 <li>A number of useful Python packages, like matplotlib, NumPy, and
 SciPy.</li>
 <li>Jupyter, which provides an interactive “notebook” environment for
 prototyping code.</li>
-<li>conda, a package manager that will allow you to install and update
+<li>conda: a package manager that will allow you to install and update
 Python and additional Python packages, while handling all
 compatibility issues for you.</li>
 </ul>
@@ -238,7 +238,7 @@ <h1>Installing Python<a class="headerlink" href="#Installing-Python" title="Perm
 <div class="admonition note">
 <p class="first fa fa-exclamation-circle"><strong>Takeaway</strong>:</p>
 <p class="last">“Anaconda” is a collection of the CPython interpreter and a number of
-very popular Python libraries for doing data science related work. It
+very popular Python libraries for doing data science-related work. It
 also provides a package manager for downloading/updating Python
 packages, and an environment manager for maintaining independent
 installations of Python side-by-side.</p>

docs/.doctrees/Module1_GettingStartedWithPython/Jupyter_Notebooks.doctree

@@ -380,22 +380,22 @@
 </style>
 <div class="section" id="Jupyter-Notebooks">
 <h1>Jupyter Notebooks<a class="headerlink" href="#Jupyter-Notebooks" title="Permalink to this headline">¶</a></h1>
-<p>In recent years, the Jupyter notebook has become as a massively popular
+<p>In recent years, the Jupyter Notebook has become a massively popular
 tool for doing research-oriented work in Python and other languages
 alike. Its emergence marked a paradigm shift in the way data science is
 conducted.</p>
 <p>A Jupyter notebook is similar to the IPython console, but, instead of
-only being able to only work with a single line of code at a time, you
-can easily and edit and re-execute <em>any</em> code that had been written in a
+only being able to work with a single line of code at a time, you can
+easily edit and re-execute <em>any</em> code that had been written in a
 notebook. Furthermore, you can save a notebook, and thus return to it
 later. Additionally, a notebook provides many terrific features. For
 instance, you can embed visualizations of data within a notebook, and
 write blocks of nicely-formatted text (using the <a class="reference external" href="https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet">Markdown
 syntax</a>),
 for presenting and explaining the contents of the notebook.</p>
-<p>In this way, a Jupyter notebook is stands out as an excellent tool for
-many practical applications in. You could work on a notebook while you
-are working through sections of this website, for instance, testing out
+<p>In this way, the Jupyter Notebook stands out as an excellent tool for
+many practical applications. You could work on a notebook while you are
+working through sections of this website, for instance, testing out
 snippets of code, and answering reading-comprehension questions as you
 proceed through the text, and using markdown-headers to visually
 separate different portions of the notebook. When I do research, I am
@@ -458,14 +458,14 @@ <h2>Notebook Cells<a class="headerlink" href="#Notebook-Cells" title="Permalink
 <span class="n">y</span> <span class="o">=</span> <span class="mi">4</span>
 </pre></div>
 </div>
-<p>then press <code class="docutils literal"><span class="pre">&lt;SHIFT&gt;+&lt;RETURN&gt;</span></code>. This will execute all of the code
-within the given cell (in this instance, assigning the variables <code class="docutils literal"><span class="pre">x</span></code>
-and <code class="docutils literal"><span class="pre">y</span></code> with the values 3 and 4, respectively) and then creates a new
-cell below. In the next cell type the code:</p>
+<p>then press <code class="docutils literal"><span class="pre">&lt;SHIFT&gt;+&lt;ENTER&gt;</span></code>. This will execute all of the code within
+the given cell (in this instance, assigning the variables <code class="docutils literal"><span class="pre">x</span></code> and
+<code class="docutils literal"><span class="pre">y</span></code> with the values 3 and 4, respectively) and then creates a new cell
+below. In the next cell type the code:</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">x</span> <span class="o">+</span> <span class="n">y</span>
 </pre></div>
 </div>
-<p>and hit <code class="docutils literal"><span class="pre">&lt;SHIFT&gt;+&lt;RETURN&gt;</span></code> to execute this code. The number 7 will
+<p>and hit <code class="docutils literal"><span class="pre">&lt;SHIFT&gt;+&lt;ENTER&gt;</span></code> to execute this code. The number 7 will
 appear beneath the cell - this, of course, is the value that is returned
 when <code class="docutils literal"><span class="pre">3</span> <span class="pre">+</span> <span class="pre">4</span></code> is evaluated:</p>
 <div class="figure" id="id3">
@@ -1361,9 +1361,9 @@ <h2>Familiarizing Yourself with Jupyter Notebooks<a class="headerlink" href="#Fa
 <p><strong>Command Mode (Press ``&lt;ESC&gt;`` to activate)</strong></p>
 <p>When in command mode, you can use keyboard shortcuts to
 create/delete/cut/paste notebook cells, and to change a cell’s type
-between code and markdown mode. Your selected cell will be surrounded by
-a <em>blue</em> border when you are in command mode. For a complete listing of
-keyboard shortcuts, toward the top of the notebook click
+between code and markdown modes. Your selected cell will be surrounded
+by a <em>blue</em> border when you are in command mode. For a complete listing
+of keyboard shortcuts, toward the top of the notebook click
 <code class="docutils literal"><span class="pre">Help</span> <span class="pre">&gt;</span> <span class="pre">Keyboard</span> <span class="pre">Shortcuts</span></code>. The most critical shortcuts are:</p>
 <ul class="simple">
 <li>create a new cell above the current cell: <code class="docutils literal"><span class="pre">a</span></code></li>
@@ -1383,7 +1383,7 @@ <h2>Familiarizing Yourself with Jupyter Notebooks<a class="headerlink" href="#Fa
 <li>execute current cell and then create a new cell below:
 <code class="docutils literal"><span class="pre">&lt;SHIFT&gt;+&lt;ENTER&gt;</span></code></li>
 </ul>
-<p>By default, a cell will be a code-type cell, meaning that it’s content
+<p>By default, a cell will be a code-type cell, meaning that its content
 will be formatted and executed as Python code. Just as you saw when
 using the IPython notebook, <code class="docutils literal"><span class="pre">&lt;TAB&gt;</span></code> can be used to perform
 autocomplete. Additionally, when your cursor is on the name of a Python
@@ -1401,7 +1401,7 @@ <h3>Markdown Cells<a class="headerlink" href="#Markdown-Cells" title="Permalink
 page</a>
 as a reference for various markdown stylings. Using markdown cells
 allows you to create section and subsection headers for your notebook,
-you can <a class="reference external" href="http://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Working%20With%20Markdown%20Cells.html#LaTeX-equations">render latex math
+you can <a class="reference external" href="http://jupyter-notebook.readthedocs.io/en/stable/examples/Notebook/Working%20With%20Markdown%20Cells.html#LaTeX-equations">render LaTeX math
 equations</a>,
 embed images and videos in your notebook, and much more. In fact, every
 page in this website was created using Jupyter notebooks! Markdown-type

docs/.doctrees/Module1_GettingStartedWithPython/Numerical_Work_In_Python.doctree

@@ -196,16 +196,16 @@
 <div class="section" id="Doing-Numerical-Work-in-Python">
 <h1>Doing Numerical Work in Python<a class="headerlink" href="#Doing-Numerical-Work-in-Python" title="Permalink to this headline">¶</a></h1>
 <p>Python’s elegant and flexible syntax makes it a particularly attractive
-language, however this makes Python considerably slower than other, more
-stringent languages (e.g., the C programming language). This is a
-non-issue in many circumstances. It is, however, a major roadblock when
-one is doing serious numerical work.</p>
+language. However, this also makes Python considerably slower than
+other, more stringent languages (e.g., the C programming language). This
+is a non-issue in many circumstances. It is, however, a major roadblock
+when one is doing serious numerical work.</p>
 <p>Fortunately, there are several packages that you can use in Python,
-which allow you to do mathematical computations that actually are
+which allow you to do mathematical computations that are actually
 executed behind the scenes in a faster language. Offloading the work to
 a different language allows the computations to become blazingly fast,
-and we, the coders, can stick to writing Python. The two best packages
-for this (both of which are already packaged in Anaconda) are:</p>
+and we, the programmers, can stick to writing Python. The two best
+packages for this (both of which are already packaged in Anaconda) are:</p>
 <div class="section" id="NumPy">
 <h2>NumPy<a class="headerlink" href="#NumPy" title="Permalink to this headline">¶</a></h2>
 <p>The fundamental package for scientific computing with Python. NumPy
@@ -230,12 +230,12 @@ <h2>NumPy<a class="headerlink" href="#NumPy" title="Permalink to this headline">
 </div>
 <div class="section" id="Numba">
 <h2>Numba<a class="headerlink" href="#Numba" title="Permalink to this headline">¶</a></h2>
-<p>Numba gives you the power to speed up your applications with high
-performance functions written directly in Python. Where NumPy restricts
-you to using numpy-functions on numpy-arrays, Numba allows you to write
-your own custom functions in Python and it will optimize your functions
-to get C-like efficiency. This isn’t a magic bullet - Numba can
-“translate” only a small subset of the Python language thus far. You
+<p>Numba gives you the power to speed up your applications with
+high-performance functions written directly in Python. Where NumPy
+restricts you to using NumPy functions on NumPy arrays, Numba allows you
+to write your own custom functions in Python and it will optimize your
+functions to get C-like efficiency. This isn’t a magic bullet - Numba
+can “translate” only a small subset of the Python language thus far. You
 have to tailor your code to be “compatible” with Numba, which can be
 limiting.</p>
 <p>We will not be using this package in this course, but it is a tremendous