install.packages("tidyverse")
install.packages("rstatix")
install.packages("ggResidpanel")
2 Setup
2.1 Installation
Required software
- Download R and install it using default options. (Note: choose the “base” version for Windows)
- Download RStudio and install it using default options.
Setting up RStudio
After installing RStudio, change some of its default options (you only need to do this once):
- From the upper menu go to Tools > Global Options…
- Untick the option “Restore .RData to workspace on startup.”
- Change “Save workspace to .RData on exit” option to “Never”
- Press OK
For this course we’ll be using Visual Studio Code. This provides support for various programming languages (including Python and R). It works on Windows, MacOS and Linux. It’s also open-source and free.
Please refer to the installation instructions and make sure that you verify that Python code will run.
A brief sequence of events:
- Install Visual Studio Code
- Install the VS Code Python extension
- Install a Python interpreter
- Windows: install from Python.org or use the Microsoft Store
- MacOS: install the Homebrew package manager, then use this to install Python
- Linux: comes with Python 3, but needs
pip
to install additional packages
2.2 Packages
We will be using the following packages throughout this course:
Install the required packages. Run the following code in the console:
Testing your installation
On the RStudio panel named “Console” type library(tidyverse)
and press Enter
A message similar to this should print:
── Attaching packages ─────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.2.1 ✔ purrr 0.3.2
✔ tibble 2.1.3 ✔ dplyr 0.8.3
✔ tidyr 1.0.0 ✔ stringr 1.4.0
✔ readr 1.3.1 ✔ forcats 0.4.0
── Conflicts ────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
If instead you get the message:
Error in library(tidyverse) : there is no package called ‘tidyverse’
then your package installation did not work. Please ask the instructors for assistance before the course.
NumPy
The numpy
package provides fundamental data science functionality to Python. For more information see: https://numpy.org/doc/stable/#
It can be installed via pip
pip install numpy
or conda
-c conda-forge numpy conda install
pandas
The pandas
package provides data structures to Python. For more information see: https://pandas.pydata.org/docs/getting_started/install.html.
It can be installed via pip
pip install pandas
or conda
conda install pandas
pingouin
The pingouin
package provides statistical functionality to Python. For more information see: https://pingouin-stats.org.
It can be installed via pip
pip install pingouin
or conda
-c conda-forge pingouin conda install
patchworklib
The patchworklib
package provides an easy way for assembling figures. This package is required to run the course-specific dgplots()
function. For more information see: https://pypi.org/project/patchworklib/.
It can be installed via pip
pip install patchworklib
plotnine
The plotnine
packages provides a grammar of graphics to Python - an equivalent to the ggplot2
package in R. For more information see: https://plotnine.readthedocs.io/en/stable/#.
It can be installed via pip
pip install plotnine
or conda
-c conda-forge plotnine conda install
2.2.1 scikit-posthocs
The scikit-posthocs
package provides post-hoc functionality. For more information see: https://scikit-posthocs.readthedocs.io/en/latest/
It can be installed via pip
-posthocs pip install scikit
2.2.2 statsmodels
The statsmodels
package provides statistical functionality. For more information see: https://www.statsmodels.org/stable/index.html.
It can be installed via pip
pip install statsmodels
or conda
-c conda-forge statsmodels conda install