Regardless of the quality of your analyses and data-related findings, if you cannot effectively communicate them, their impact will be severely limited. Technical skills in this module will focus on a step-by-step walk through the process of choosing, creating, and modifying data visualizations in R using ggplot (following ‘Data Visualization: A Practical Introduction’ by Healy (2018)). Discussions will include general design principles applicable to other data visualization software used in industry and academia (eg. Python, Tableau, PowerBI). Case studies and ‘real world’ examples are incorporated throughout. Ethics components include incorporating reproducibility with data visualization, building awareness of the decision making that goes into sharing data visually, and addressing inequity in data visualization by focusing on accessible design.

This course is designed for those who have a degree in something other than Computer Science/Statistics who are looking to enhance their data science and data visualization skills for their career.

Students will...

1. Develop their ability to create and customize data visualizations start to finish in R
2. Build an understanding of general design principles for creating accessible/equitable data visualizations in R and other software
3. Build an understanding of data visualization as purposeful/telling a story (and the ethical/professional implications thereof)

• Instructor: Ciara Zogheib (She/Her).
  • To contact me, please email me at [email protected], and include 'DSI Data Visualization' in the subject line!
  • I'll do my best to respond promptly, but please be patient!

The workshop will be held over three weeks, three days a week. Two of the three days will be 2-hours long and the last day of each will be 3-hours. Being mindful of online fatigue, there will be one break during each class where students are encouraged to stretch, grab a drink and snacks, or ask any additional questions.

• Camera is optional although highly encouraged. We understand that not everyone may have the space at home to have the camera on.

• Monday 13 March, 6pm-8pm: Overview and introduction, setting up ggplot in R
• Thursday 16 March, 6pm-8pm: Making preliminary ggplots; intro to reproducible data visualization
• Saturday 18 March, 9am-noon: Modifying our ggplots – tables, labels, and notes; choosing the right data visualization
• Monday 20 March, 6pm-8pm: Refining our plots
• Thursday 23 March, 6pm-8pm: Accessible data visualization
• Saturday 25 March, 9am-noon: Data visualization as advocacy; working with models
• Monday 27 March, 6pm-8pm: Professional skills: Industry case study – Richard Wintle
• Thursday 30 March, 6pm-8pm: Mapping data; interactive data visualization
• Saturday 1 April, 9am-noon: Visualization: Review and Practice

• Mondays: On Monday, March 13 (first day of the course), tutorial will take place at 5:00 PM - 6:00 PM (before class). Other Monday tutorials will take place after class (8:00 PM - 9:00 PM)
• Thursdays: On Thursdays, tutorials will take place at 5:00 PM - 6:00 PM (before class).
• Saturdays: On Saturdays, tutorials will take place before class (8:30 AM - 9:00 AM) and after class (12:00 PM - 12:30 PM)

The course is a live-coding class. Students are expected to follow along with the coding. Students should be active participants while coding and are encouraged to ask questions throughout. Although slides will be available for students to reference, they should be referenced before or after class, as during class will be dedicated to coding with the instructor.

Below are the folders contained in this repo with a description of what they contain and information on how to use them.

This folder contains the assignments for the workshop. Students are expected to complete them one week after the content has been delivered.

This folder contains the pdf version of the slides. They contain all information that was discussed in class and are a great resource in the future if students need to reassess their knowledge.

• We wish to acknowledge this land on which the University of Toronto operates. For thousands of years it has been the traditional land of the Huron-Wendat, the Seneca, and most recently, the Mississaugas of the Credit River. Today, this meeting place is still the home to many Indigenous people from across Turtle Island and we are grateful to have the opportunity to work on this land.