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Creating high-quality, effective data visualizations is a skill that involves more than learning how to write code in Python, R, or other languages. In this workshop, we will discuss some principles of visual perception and give suggestions for how to design data visualizations that are effective, accurate, and attractive. We will also discuss how to make your data visualizations more accessible, considering ideas like color-blind-friendly visualizations, text descriptions of visualizations, and providing access to underlying data.

ggplot2 is a plotting package for R that makes it simple to create complex plots from data stored in a data frame. It provides a programmatic interface for specifying what variables to plot, how they are displayed, and general visual properties. Therefore, researchers only need minimal changes if the underlying data change or if they decide to change from a bar plot to a scatterplot. This helps in creating publication quality plots with minimal amounts of adjustments and tweaking.

In this lesson, participants will learn:

* The basic principles of the “grammar of graphics”

This pair of workshops is an introduction to programming and plotting in Python for people with little or no previous programming experience. It will cover use of interpreters (Python 3), visualization (matplotlib), data wrangling (pandas), notebooks (JupyterLab), and data platforms (Anaconda).

The companion session is scheduled for June 22, 2022.

Please click here to learn more and to register for this workshop.

This pair of workshops is an introduction to programming and plotting in Python for people with little or no previous programming experience. It will cover use of interpreters (Python 3), visualization (matplotlib), data wrangling (pandas), notebooks (JupyterLab), and data platforms (Anaconda).

The companion session is scheduled for June 29, 2022.

Please click here to learn more and to register for this workshop.

Linux is an open-source operating system that is fundamentally relevant and empowering to research computing in many disciplines. Linux is available at Middlebury, from personal workstations to mid-level facilities to high-performance computing clusters, and this session will explore the landscape of Linux capabilities and tools on campus. This session pairs well with The Terminal and the Command Line workshop on June 7 and 9, 2022, although that workshop is not a prerequisite.

dplyr is a package for making tabular data manipulation easier by using a limited set of functions that can be combined to extract and summarize insights from your data. It pairs nicely with tidyr which enables you to swiftly convert between different data formats (long vs. wide) for plotting and analysis.

In this lesson, participants will learn:

* How to select specific observations, variables, and/or values from a dataset
* How to combine multiple commands into a single command
* How to create new columns or remove existing columns from a dataset

This is an introduction to R designed for participants with no, or little, programming experience.

Why should you learn R?

* R does not involve lots of pointing and clicking, and that’s a good thing
* R code is great for reproducibility — for yourself, or for other researchers
* R is interdisciplinary and extensible
* R works on data of all shapes and sizes — quantitative, qualitative, text, images, spatial, etc.
* R helps produce high-quality graphics
* R has a large and welcoming community

In this introduction you will learn:

The terminal and the command-line are gateways to robust and efficient computing tasks. The Unix shell is often at their core and has been around longer than most of its users have been alive. It has survived because it’s a powerful tool that allows users to perform complex and powerful tasks, often with just a few keystrokes or lines of code. It helps users automate repetitive tasks and easily combine smaller tasks into larger, more powerful workflows. Use of the shell is fundamental to a wide range of advanced computing tasks, including high-performance computing.

The Organizing and Managing Research Data workshop will focus on research data management: what it is, why it’s an important skill, and how it contributes to successful research. Whether you work alone or collaborate with other researchers, it is essential to organize, describe, and document your data and research processes effectively. You can free up mental energy for actually doing research, encourage reproducible research, and make your research team’s collaboration more efficient.

The terminal and the command-line are gateways to robust and efficient computing tasks. The Unix shell is often at their core and has been around longer than most of its users have been alive. It has survived because it’s a powerful tool that allows users to perform complex and powerful tasks, often with just a few keystrokes or lines of code. It helps users automate repetitive tasks and easily combine smaller tasks into larger, more powerful workflows. Use of the shell is fundamental to a wide range of advanced computing tasks, including high-performance computing.