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_bookdown.yml

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ui:
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chapter_name: "Chapter "
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delete_merged_file: true
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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"]
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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", "appendixA.Rmd"]

appendixA.Rmd

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

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setup.Rmd

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## Overview
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Throughout this book, we have assumed that you are working on a web-based platform
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(e.g., JupyterHub) that already has Jupyter, R, a number of R packages, and Git set up and ready to use.
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In this chapter, you'll learn how to install all of that software on your own computer in case
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you don't have a preconfigured JupyterHub available to you.
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In this chapter, you'll learn how to install all of that software
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needed to do this data science covered in this book on your own computer.
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## Chapter learning objectives
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By the end of the chapter, readers will be able to:
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- install Git and the miniconda Python distribution
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- install the Git version control software
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- install and launch a local instance of JupyterLab with the R kernel
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- download files from a JupyterHub for later local use
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## Installing software on your own computer
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In this section we will provide instructions for installing the software
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required by this book on our own computer.
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Given that installation instructions can vary widely based on the computer setup
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This section will provide instructions for installing the software required by
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this book on our own computers.
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Given that installation instructions can vary widely based on the computer setup,
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we have created instructions for multiple operating systems.
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In particular, the installation instructions below have been verified to work
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on a computer that:
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- runs one of the following operating systems: MacOS 10.15.X (Catalina); Ubuntu 20.04; Windows 10, version 2004.
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- runs one of the following operating systems: Ubuntu 20.04, macOS Big Sur (version 11.4.x or 11.5.x), Windows 10 Professional, Enterprise or Education (version 2004, 20H2, or 21H1).
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- can connect to networks via a wireless connection
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- uses a 64-bit CPU
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- uses English as the default language
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**For macOS users only:** Apple recently changed the default shell in the terminal to Zsh.
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However, the programs we need work better with the Bash shell. Thus, we recommend you change
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the default shell to Bash by opening the terminal
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([how to video](https://youtu.be/5AJbWEWwnbY)) and typing:
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```
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chsh -s /bin/bash
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```
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You will have to quit all instances of open terminals and then restart the
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terminal for this to take effect.
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### Git
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As shown in the version control chapter, Git is a very useful tool for version
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controlling your projects, as well as sharing your work with others.
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As shown in Chapter \@ref(Getting-started-with-version-control),
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Git is a very useful tool for version controlling your projects,
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as well as sharing your work with others. Here's how to install Git on
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the following operating systems:
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**Windows:** To install
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Git on Windows go to <https://git-scm.com/download/win> and download the windows
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version of git. Once the download has finished, run the installer and accept
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Git on Windows, go to <https://git-scm.com/download/win> and download the Windows
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version of Git. Once the download has finished, run the installer and accept
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the default configuration for all pages.
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**MacOS:** To install Git on Mac OS open the terminal and type the following command:
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**MacOS:** To install Git on Mac OS,
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open the terminal ([how-to video](https://youtu.be/5AJbWEWwnbY))
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and type the following command:
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```
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xcode-select --install
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```
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**Ubuntu:** To install Git on Ubuntu open the terminal and type the following commands:
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**Ubuntu:** To install Git on Ubuntu, open the terminal
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and type the following commands:
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```
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sudo apt update
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### Miniconda
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To run Jupyter notebooks on our computers we will need to install a program
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similar to the one we used as our web-based platform. One such program is
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JupyterLab. But JupyterLab relies on Python; we can install this via
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To run Jupyter notebooks on our computers,
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we will need to install the web-based platform JupyterLab.
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But JupyterLab relies on Python; we can install this via
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the [miniconda Python package distribution](https://docs.conda.io/en/latest/miniconda.html).
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**Windows:** To install miniconda on Windows, download
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the [Python 3.8 64-bit version from here](https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe).
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Once the download has finished, run the installer and accept the default
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configuration for all pages. After installation, you can open the Anaconda Prompt
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the [latest Python 64-bit version from here](https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe).
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Once the download has finished, run the installer
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and accept the default configuration for all pages.
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After installation, you can open the Anaconda Prompt
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by opening the Start Menu and searching for the program called
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"Anaconda Prompt (miniconda3)". When this opens you will see a prompt similar to
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"Anaconda Prompt (miniconda3)".
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When this opens, you will see a prompt similar to
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`(base) C:\Users\your_name`.
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**MacOS:** To install miniconda on MacOS, download
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the [Python 3.8 64-bit version from here](https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.pkg).
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the [latest Python 64-bit version from here](https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.pkg).
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After the download has finished, run the installer and accept the default
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configuration for all pages.
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**Ubuntu:** To install miniconda on Ubuntu, we first download
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the [Python 3.8 64-bit version from here](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh).
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the [latest Python 64-bit version from here](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh).
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After the download has finished, open the terminal and execute the following
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commands:
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```
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bash path/to/Miniconda3-latest-Linux-x86_64.sh
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```
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> Note: most often this file is downloaded to the Downloads directory, and thus the command will look like this:
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> Note: most often, this file is downloaded to the Downloads directory,
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and thus the command will look like this:
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> ```
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> bash Downloads/Miniconda3-latest-Linux-x86_64.sh
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> ```
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The instructions for the installation will then appear:
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(1) Press Enter.
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(2) Once the licence agreement shows, you can press space scroll down, or press `q` to skip reading it.
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(2) Once the licence agreement shows, you can press space scroll down or press `q` to skip reading it.
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(3) Type `yes` and press enter to accept the licence agreement.
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(4) Press enter to accept the default installation location.
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(5) Type `yes` and press enter to instruct the installer to run `conda init`, which makes `conda` available from the terminal/shell.
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```
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conda install -c conda-forge -y jupyterlab
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conda install -y nodejs=10.*
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conda install -y nodejs
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pip install --upgrade jupyterlab-git
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jupyter lab build
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```
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To test that your JupyterLab installation is functional, you can type
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`jupyter lab` into the Anaconda Prompt (Windows) or terminal (MacOS and Ubuntu) and press enter. This should open a new
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`jupyter lab` into the Anaconda Prompt (Windows)
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or terminal (MacOS and Ubuntu) and press enter. This should open a new
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tab in your default browser with the JupyterLab interface. To exit out of
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JupyterLab you can click `File -> Shutdown`, or go to the terminal from which
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you launched JupyterLab, hold `Ctrl`, and press `c` twice.
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you launched JupyterLab, hold `Ctrl`, and press `C` twice.
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### R and the IRkernel
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To have R available to you in JupyterLab, you will need to install the R programming language and the IRkernel.
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To have R available to you in JupyterLab,
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you will need to install the R programming language and the IRkernel R package.
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To install these, type the following into
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the Anaconda Prompt (Windows) or terminal (MacOS and Ubuntu):
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```
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conda install -c conda-forge -y r-base
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conda install -c conda-forge -y r-base">=4.1.1"
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conda install -c conda-forge -y r-irkernel
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```
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To improve the experience of using R in JupyterLab, we will add an extension
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that allows us to setup keyboard shortcuts for inserting text.
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By default, this extension creates shortcuts for inserting two of the most common R
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operators: `<-` and `%>%`. Type the following in the Anaconda Prompt (Windows)
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By default,
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this extension creates shortcuts for inserting two of the most common R
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operators: `<-` and `|>`. Type the following in the Anaconda Prompt (Windows)
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or terminal (MacOS and Ubuntu) and press enter:
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```
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jupyter labextension install @techrah/text-shortcuts
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jupyter lab build
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```
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### R packages
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To install the packages used in this book, type the following in the Anaconda Prompt (Windows) or terminal (MacOS and Ubuntu) and press enter:
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To install the packages used in this book,
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type the following in the Anaconda Prompt (Windows)
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or terminal (MacOS and Ubuntu) and press enter:
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```
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conda install -c conda-forge -y \
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r-rsqlite \
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r-testthat \
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r-tidymodels \
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r-tidyverse \
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r-tinytex \
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unixodbc
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```
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To be able to render `.ipynb` files to `.pdf` you need to install a LaTeX
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distribution. These can be quite large, so we will opt to use `tinytex`, a
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light-weight cross-platform, portable, and easy-to-maintain LaTeX distribution
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based on TeX Live. To install it open JupyterLab by typing `jupyter lab`
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based on TeX Live.
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**MacOS:** To install `tinytex`
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we need to make sure that `/usr/local/bin` is writable.
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To do this, type the following in the terminal:
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```
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sudo chown -R $(whoami):admin /usr/local/bin
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```
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> *Note: You might be asked to enter your password during installation.*
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**All operating systems:**
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To install LaTeX open JupyterLab by typing `jupyter lab`
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in the Anaconda Prompt (Windows) or terminal (MacOS and Ubuntu) and press enter.
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Then from JupyterLab open an R console and type the commands listed below and
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press Shift + enter to install `tinytex`:
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press `Shift` + `enter` to install `tinytex`:
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```
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tinytex::install_tinytex()
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"upquote"))
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```
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## Moving files to your computer
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This section will help you
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save your work from the JupyterHub web-based platform to your own computer.
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First in JupyterHub, open a terminal by clicking "terminal" in the Launcher tab.
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Next, type the following in the terminal to create a
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compressed `.zip` archive for the work you are interested in downloading:
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**Ubuntu:**
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To append the TinyTex executables to our `PATH` we need to edit our `.bashrc file`.
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The TinyTex executables are usually installed in `~/bin`.
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Thus, add the lines below to the bottom of your `.bashrc` file
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(which you can open by `nano ~/.bashrc` and save the file:
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```
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zip -r hub_folder.zip your_folder
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# Append TinyTex executables to the path
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export PATH="$PATH:~/bin"
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```
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After the compressing process is complete, right-click on `hub_folder.zip`
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in the JupyterHub file browser
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and click "Download". You should be able to use your computer's software to unzip
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the compressed folder by double-clicking on it.
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> Note: If you used `nano` to open your `.bashrc` file,
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follow the keyboard shortcuts at the bottom of the nano text editor
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to save and close the file.
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## Finishing up installation
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It is good practice to restart all the programs you used when installing this
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software stack before you proceed to doing your data analysis.
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This will ensure all the software and settings you put in place are
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correctly sourced. This includes JupyterLab, terminal or Anaconda Prompt.

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