All workshops will be online. Participants from all schools are welcome.

Effective Data Visualization

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  5pm - 6:30pm

Visualization is a powerful way to reveal patterns in data, attract attention, and get your message across to an audience quickly and clearly. But, there are many steps in that journey from exploration to information to influence, and many choices to make when putting it all together to tell your story. I will cover some basic guidelines for effective visualization, point out a few common pitfalls to avoid, and run through a critique and iterations of an existing visualization to help you start seeing better choices beyond the program defaults.

Geospatial Data in R: Mapping

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  1pm - 3pm

This workshop introduces the use of the R analysis language for producing maps. We will demonstrate the advantages of a code-driven approach to visualize geospatial data. Participants will gain the skills to create a variety of map types quickly and efficiently for a website, presentation, or publication. In addition to working on hands-on coding exercises, we will also focus on practical guidance for designing effective maps. This workshop is a companion to Geospatial Data in R: Processing and Analysis (Feb 7), which emphasizes data analysis more than visualization. Prerequisites: Attendees will need basic familiarity with R and RStudio to follow along with the exercises. Knowledge of tidyverse packages such as ggplot2 and dplyr is also helpful.

Adobe Illustrator for Diagrams

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  10am - 12pm

Part of the DataFest workshop series. In this workshop, you will learn the basics of using Adobe Illustrator, the professional standard in vector graphics software for creating diagrams and infographics. Many people avoid using it because of its steep learning curve, but you will see that it is quite easy to combine simple shapes to create interesting and clear diagrams, and to give all your work that professional edge. There are no prerequisites.

R for data science: getting started, EDA, data wrangling

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  10am - 12pm

R is a "data-first" coding language that enables reproducible workflows. In this workshop, you will learn the fundamentals of R and the Tidyverse in order to quickly get started. You will learn how to access and install RStudio, how to wrangle data for analysis, how to explore data (EDA), and a brief introduction to visualization.

R for data science: visualization, pivot, join, regression

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  10am - 12pm

R and the Tidyverse are a data-first coding language that enables reproducible workflows. In this workshop which follows "R for data science: getting started, EDA, and data wrangling," you’ll learn about creating visualizations using ggplot2, making interactive charts for use in dashboards, and reshaping and merging data. This workshop will include a brief introduction to using models in R.

Python for Data Science: Pandas 101

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  10am - 12pm

Part of the DataFest workshop series. Python can be a great option for exploration, analysis and visualization of tabular data, such as spreadsheets and CSV files, if you know which tools to use and how to get started. This workshop will take you through some practical examples of using Python and specifically the Pandas module to load data from files, access that data, and start visualizing it with the Pandas built-in plotting functions. You will also gain experience working in JupyterLab, a flexible programming environment which provides Jupyter Notebooks, a file browser, and more. Note: Some experience with the Python programming language is recommended.

Intro to Tableau: Easy charts and maps

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  6:30pm - 8:30pm

Part of the DataFest workshop series. Tableau Public (available for both Windows and Mac) is an incredibly useful visualization tool that allows individuals to explore their data using a wide variety of visual representations. The software also can produce interactive, web-based visualization dashboards. This workshop will focus on using Tableau Public to create data visualizations, starting with an overview of Tableau's data assumptions, common data manipulation and loading, and the terminology used. Activities will include a sample data visualization and mapping project, which provides hands-on experience using Tableau’s basic chart types and dashboard creation tools. We will also discuss publishing to the Tableau Public web server and related services and tools, like the full Tableau Desktop application (free for full-time students).