merging dev into wrangling

Author: ttimbers

_bookdown.yml

@@ -3,4 +3,4 @@ language:
   ui:
     chapter_name: "Chapter "
 delete_merged_file: true
-rmd_files: ["index.Rmd", "intro.Rmd", "reading.Rmd", "wrangling.Rmd", "viz.Rmd", "classification1.Rmd", "classification2.Rmd", "regression1.Rmd", "regression2.Rmd", "clustering.Rmd", "inference.Rmd", "jupyter.Rmd", "version-control.Rmd", "setup.Rmd", "references.Rmd"]
+rmd_files: ["index.Rmd", "intro.Rmd", "reading.Rmd", "wrangling.Rmd", "viz.Rmd", "classification1.Rmd", "classification2.Rmd", "regression1.Rmd", "regression2.Rmd", "clustering.Rmd", "inference.Rmd", "jupyter.Rmd", "version-control.Rmd", "setup.Rmd", "appendixA.Rmd", "references.Rmd"]

appendixA.Rmd

@@ -0,0 +1,19 @@
+# (APPENDIX) Appendix {-}
+
+# Download files from a JupyterHub for later local use {#appendixA}
+
+This section will help you
+save your work from the JupyterHub web-based platform to your own computer. 
+
+First, in JupyterHub, open a terminal by clicking "terminal" in the Launcher tab. 
+Next, type the following in the terminal to create a 
+compressed `.zip` archive for the work you are interested in downloading:
+
+```
+zip -r hub_folder.zip your_folder
+```
+
+After the compressing process is complete, right-click on `hub_folder.zip`
+in the JupyterHub file browser
+and click "Download". You should be able to use your computer's software to unzip
+the compressed folder by double-clicking on it. 

classification1.Rmd

@@ -26,7 +26,7 @@
 <meta name="author" content="Melissa Lee" />
 
 
-<meta name="date" content="2021-08-04" />
+<meta name="date" content="2021-09-23" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1" />
   <meta name="apple-mobile-web-app-capable" content="yes" />
@@ -299,13 +299,13 @@
 <li class="chapter" data-level="5.4.2" data-path="classification.html"><a href="classification.html#describing-the-variables-in-the-cancer-data-set"><i class="fa fa-check"></i><b>5.4.2</b> Describing the variables in the cancer data set</a></li>
 <li class="chapter" data-level="5.4.3" data-path="classification.html"><a href="classification.html#exploring-the-cancer-data"><i class="fa fa-check"></i><b>5.4.3</b> Exploring the cancer data</a></li>
 </ul></li>
-<li class="chapter" data-level="5.5" data-path="classification.html"><a href="classification.html#classification-with-k-nearest-neighbours"><i class="fa fa-check"></i><b>5.5</b> Classification with K-nearest neighbours</a>
+<li class="chapter" data-level="5.5" data-path="classification.html"><a href="classification.html#classification-with-k-nearest-neighbors"><i class="fa fa-check"></i><b>5.5</b> Classification with <span class="math inline">\(K\)</span>-nearest neighbors</a>
 <ul>
 <li class="chapter" data-level="5.5.1" data-path="classification.html"><a href="classification.html#distance-between-points"><i class="fa fa-check"></i><b>5.5.1</b> Distance between points</a></li>
 <li class="chapter" data-level="5.5.2" data-path="classification.html"><a href="classification.html#more-than-two-explanatory-variables"><i class="fa fa-check"></i><b>5.5.2</b> More than two explanatory variables</a></li>
-<li class="chapter" data-level="5.5.3" data-path="classification.html"><a href="classification.html#summary-of-k-nearest-neighbours-algorithm"><i class="fa fa-check"></i><b>5.5.3</b> Summary of K-nearest neighbours algorithm</a></li>
+<li class="chapter" data-level="5.5.3" data-path="classification.html"><a href="classification.html#summary-of-k-nearest-neighbors-algorithm"><i class="fa fa-check"></i><b>5.5.3</b> Summary of <span class="math inline">\(K\)</span>-nearest neighbors algorithm</a></li>
 </ul></li>
-<li class="chapter" data-level="5.6" data-path="classification.html"><a href="classification.html#k-nearest-neighbours-with-tidymodels"><i class="fa fa-check"></i><b>5.6</b> K-nearest neighbours with <code>tidymodels</code></a></li>
+<li class="chapter" data-level="5.6" data-path="classification.html"><a href="classification.html#k-nearest-neighbors-with-tidymodels"><i class="fa fa-check"></i><b>5.6</b> <span class="math inline">\(K\)</span>-nearest neighbors with <code>tidymodels</code></a></li>
 <li class="chapter" data-level="5.7" data-path="classification.html"><a href="classification.html#data-preprocessing-with-tidymodels"><i class="fa fa-check"></i><b>5.7</b> Data preprocessing with <code>tidymodels</code></a>
 <ul>
 <li class="chapter" data-level="5.7.1" data-path="classification.html"><a href="classification.html#centering-and-scaling"><i class="fa fa-check"></i><b>5.7.1</b> Centering and scaling</a></li>
@@ -488,8 +488,10 @@
 <li class="chapter" data-level="13.3.5" data-path="move-to-your-own-machine.html"><a href="move-to-your-own-machine.html#r-packages"><i class="fa fa-check"></i><b>13.3.5</b> R packages</a></li>
 <li class="chapter" data-level="13.3.6" data-path="move-to-your-own-machine.html"><a href="move-to-your-own-machine.html#latex"><i class="fa fa-check"></i><b>13.3.6</b> LaTeX</a></li>
 </ul></li>
-<li class="chapter" data-level="13.4" data-path="move-to-your-own-machine.html"><a href="move-to-your-own-machine.html#moving-files-to-your-computer"><i class="fa fa-check"></i><b>13.4</b> Moving files to your computer</a></li>
+<li class="chapter" data-level="13.4" data-path="move-to-your-own-machine.html"><a href="move-to-your-own-machine.html#finishing-up-installation"><i class="fa fa-check"></i><b>13.4</b> Finishing up installation</a></li>
 </ul></li>
+<li class="appendix"><span><b>Appendix</b></span></li>
+<li class="chapter" data-level="A" data-path="appendixA.html"><a href="appendixA.html"><i class="fa fa-check"></i><b>A</b> Download files from a JupyterHub for later local use</a></li>
 <li class="chapter" data-level="" data-path="references.html"><a href="references.html"><i class="fa fa-check"></i>References</a></li>
 <li class="divider"></li>
 <li><a href="https://github.com/rstudio/bookdown" target="blank">Published with bookdown</a></li>