Built site for gh-pages

Author: jreades

.nojekyll

@@ -1 +1 @@
-080f2edb
+a7f7976f

assessments/Group_Work.pdf

@@ -414,9 +414,9 @@ <h2>Nulls: None vs.&nbsp;NaN</h2>
 <p>Beware of using logic with things that are <em>not</em> what they appear:</p>
 <ul>
 <li><code>None</code> is Python’s way of saying that something has <strong>no value at all</strong> (not <code>0</code> or <code>""</code>… but <em>None</em>). It is a <strong>class</strong>.</li>
-<li>NaN (Not a Number) is a special numeric data type provided by the <code>numpy</code> package to deal with things like -ve and +ve infinity and similar ‘issues’.</li>
+<li>NaN (Not a Number) is a special numeric data type provided by the <code>numpy</code> package to deal with things that aren’t numbers. -ve and +ve infinity are handled by a similarly special <code>np.inf</code>.</li>
 </ul>
-<p><code>np.nan</code> should be used whenever you are dealing with <em>data</em> (<em>e.g.</em> see Pandas!).</p>
+<p><code>np.nan</code> should be used whenever you are dealing with errors/nulls in <em>data</em> (<em>e.g.</em> see Pandas!).</p>
 </section>
 <section id="none-vs.-nan" class="slide level2">
 <h2>None vs.&nbsp;NaN</h2>

lectures/6.1-Logic.html

@@ -6421,7 +6421,7 @@
     "href": "lectures/6.1-Logic.html#nulls-none-vs.-nan",
     "title": "Logic",
     "section": "Nulls: None vs. NaN",
-    "text": "Nulls: None vs. NaN\nBeware of using logic with things that are not what they appear:\n\nNone is Python’s way of saying that something has no value at all (not 0 or \"\"… but None). It is a class.\nNaN (Not a Number) is a special numeric data type provided by the numpy package to deal with things like -ve and +ve infinity and similar ‘issues’.\n\nnp.nan should be used whenever you are dealing with data (e.g. see Pandas!)."
+    "text": "Nulls: None vs. NaN\nBeware of using logic with things that are not what they appear:\n\nNone is Python’s way of saying that something has no value at all (not 0 or \"\"… but None). It is a class.\nNaN (Not a Number) is a special numeric data type provided by the numpy package to deal with things that aren’t numbers. -ve and +ve infinity are handled by a similarly special np.inf.\n\nnp.nan should be used whenever you are dealing with errors/nulls in data (e.g. see Pandas!)."
   },
   {
     "objectID": "lectures/6.1-Logic.html#none-vs.-nan",