Instructor: Caitlin Havlak

Classes: Tue, Sep 12 - Tue, Oct 24 (1.5 credit module)

Time/Location: 9:30AM-12:30PM, Sing Tao Bldg Room 104

Office hours: Tue, 1PM-3PM, Office 313

Contact information: Slack or at caitlin@discoursemedia.org

Overview: This course will teach you to analyze and design data visualizations for exploration and publication. The focus of the class will be on the practical and theoretical aspects of data visualization, and will also cover research and analysis skills required to produce effective visualizations. It will cover both static and interactive approaches to visualization.

Audience: There are no prerequisites, and you are not assumed to have a programming background.

Timing: The 1.5 credit module will run over six weeks, with one three-hour class each week. There will be six assignments, with each released one week and due the next (except for the last one covering two weeks). Core material is covered in the lecture segment of the course and there are no required readings. There is no final exam. The standard format for each session is:

Marking: The breakdown of marks for the course is:

Participation: You are expected to attend all classes. If you must miss a class, you should email with an explanation; this email should be in advance of class not after the fact, unless the problem is illness or emergency.

Come to the first day of class with Tableau installed!

Short Syllabus

Note: There will be no class on October 10th, 2017. Use this time to develop your story idea for your final project.

September 12th, 2017

Lecture: Tasks & Data, Marks & Channels, Colour, lead by Tamara Munzner

Lab: Intro to Tableau

September 19th, 2017

Lecture: Chart types and best practices, lead by Tamara Munzner

Lab: Basic visual encoding

September 26th, 2017

Lecture: How to find story ideas with data analysis

Lab: Spatial data and an introduction to maps

October 3rd, 2017

Lecture: How to find data to support or drive stories, lead by Francesca Fionda

Lab: Data wrangling

October 17th, 2017

Lecture: Interactivity, lead by Tamara Munzner

Lab: Interactivity through actions in Tableau and pitches!

October 24th, 2017

Lecture: Tableau Stories and other visualization tools

Lab: Story boards and Adobe Illustrator

Sign up for the module's Slack team!

WEEK 1: Tasks and data, marks and channels, colour

September 12th, 2017


Lecture slides (Caitlin):PDF

Guest lecture: Tamara Munzner

Lecture slides (Tamara): PDF, PDF 4x4, Keynote

Lecture overview: Tasks & Data, Marks & Channels, Colour


Lab workbooks: Basic Visual Encoding, Vancouver Crime, Vancouver Elections

Lab overview: The objective of this lab is to work on a variety of exercises to get familiar with the Tableau interface. You should have already completed the steps listed here.

We will go through three example demos together. The first workbook will show a variety of ways to visually encode two variables using space and color channels. The second workbook takes a look at crime in Vancouver in 2003, 2013, 2014, 2015 and up to July 2016. The third workbook explores Vancouver mayoral races in 2008, 2011 and 2014.


Assignment workbooks: Music Sales

Assignment overview: This week's assignment has two parts:

(1) You will work on a Tableau workbook using a music sales dataset. The link to the workbook and instructions is provided above. If time allows, you'll have some class time to get started with the workbook. You'll need to finish the workbook on your own time.
(2) You will also analyze the Vancouver crime dataset further and write a brief reflection piece (less than 500 words) about your analysis, findings and process.

Work individually or in partners for this assignment.

By 9AM on September 19th, submit the brief reflection as a PDF and the Music Sales workbook by email, caitlin@discoursemedia.org with subject "JOURN Week 1".

Make sure to export your Music Sales workbook as a packaged workbook (File > Export Packaged Workbook...). This will ensure that the dataset remains connected to the workbook when you send it to me by email. See instructions for how to do this here.


Reading:

WEEK 2: Chart types and best practices

September 19th, 2017


Guest lecture: Tamara Munzner

Lecture slides (Tamara): PDF, PDF 4x4, Keynote

Lecture overview: Chart types and chart best practices


Lab workbooks: Back to the Future, Arrests Premier League , Market Share

Lab data: Back to the Future data (CSV)

Lab overview: The objective of this lab is to learn about the various types of visualizations offered in Tableau, from bar chart to gantt chart to word bubble.

There are many ways to describe data visually. The author of the visualization tries to convey a point of view by emphasizing some aspects of the data while toning down other aspects. The result can vary widely, from informative to confusing to misleading. Choose your vis type wisely.

We will go through three example demos together.


Assignment workbooks: Superstore workbook, Connected Scatterplot (PDF)

Assignment data: Minimum Wage 2015 (CSV)

Assignment overview: This week's assignment has three parts:

(1) Work through the Superstore workbook using the sample dataset in Tableau.
(2) Follow the instructions in the Connected Scatterplot PDF file.
(3) Write a short reflection on how the different visual encodings that you constructed in this assignment and that you worked through in the demos emphasize and downplay different aspects of the underlying dataset (max 500 words).

By 9AM on September 26th, submit the brief reflection as a PDF and both workbooks by email, caitlin@discoursemedia.org with subject "JOURN Week 2".

Make sure to export your workbooks as packaged workbooks (File > Export Packaged Workbook...). This will ensure that the dataset remains connected to the workbook when you send it to me by email. See instructions for how to do this here.


Reading:

WEEK 3: Data analysis and an introduction to maps

September 26th, 2017


Lecture slides: PDF

Lecture overview: How to find story ideas with data analysis

Lecture data: Teacher Statistics (Source: BC Data Catalogue)


Lab workbooks: Intro to Maps

Lab data: 2016 Crime Data (CSV, JSON, SHAPEFILE)

Lab overview: The objective of this lab is to introduce the student to spatial data and the creation of maps.

We will go through two example demos together. The first workbook will introduce basic concepts of spatial visualizations. The second workbook will show the student how to make the same map using three different spatial data file types, i.e., shapefile, CSV and JSON.


Assignment worksheets: Small Multiples (PDF)

Assignment data: Drought Severeness dataset

Assignment overview: This week's assignment has two parts:

(1) Follow the instructions in the Small Multiples PDF document provided above.
(2) Find your own dataset and construct a story based on your analysis of the dataset.

Data source suggestions:

By 9AM on October 3rd, submit the Small Multiples workbook and a PDF copy of your news story by email, caitlin@discoursemedia.org with subject "JOURN Week 3". Make sure to export your workbooks as packaged workbooks (File > Export Packaged Workbook...). This will ensure that the dataset remains connected to the workbook when you send it to me by email. See instructions for how to do this here.


Reading:

WEEK 4: How to find data to support or drive stories

October 3rd, 2017


Guest lecture: Francesca Fionda

Lecture slides: PDF

Lecture overview: How to find data to support or drive stories (e.g., strategic searching, FOIs, research skills)

Supplementary documents:


Lab worksheet: PDF

Lab lecture: PDF

Lab workbook: Simple Survey Example (if time allows)

Lab data: Market rental pricing dataset, Income dataset, CMHC dataset

Lab overview: The objective of this lab is to enable students to wrangle datasets into clean and compatible formats for use in Tableau.


Assignment data: Angus Reid Institute survey responses by gender, province, age, education, household income

Assignment workbooks: Angus Reid workbook

Assignment background information: Survey questions, messy original survey data

Assignment overview: This week's assignment has two parts:

(1) Explore the survey data conducted by the Angus Reid Institute on Canadian perspectives on women in politics. There are eight questions in the survey. Responses for each question are broken down by gender, province, education level, household income and age. There is a separate spreadsheet for each of these parameters. You will find these spreadsheets linked to above.

Start by completing the workbook (link above), then explore the dataset in more detail. Beyond what is covered in the workbook, you will need to connect the other spreadsheets to the workbook. What other key information do you get from the other parameters, i.e., age, gender, household income, education level?

Provide a write-up describing your design and your findings. No more than 500 words. What story (or stories) are you trying to tell? What is the most compelling story in this dataset? Note that you are not being asked to submit a story this week, just the reflection/rationale.

(2) Write a pitch for your final project.

By 9AM on October 17th, submit your reflection (part I) and pitch (part II) by email, caitlin@discoursemedia.org with subject "JOURN Week 4". Please submit both documents in PDF format.


Reading:

Note: there is no class on October 10th, 2017!

WEEK 5: Interactivity and pitches

October 17th, 2017


Guest lecture: Tamara Munzner

Lecture slides: PDF

Lecture overview: Interactivity


Lab workbooks: Seattle Construction, Internet Use

Lab overview: The objective of this lab is to learn how to add basic interactivity to Tableau dashboards.


Assignment worksheets: Home Price Index (PDF)

Assignment data: House Price Index dataset

Assignment overview: This week's assignment will have two parts:

(1) Add interactivity to a past workbook that we have worked on. This could be a demo or assignment workbook.

(2) Recreate a New York Times data visualization using the worksheet linked to above but with Canadian housing data. We will use actions and calculated fields in Tableau.

By 9AM on October 24th, submit two Tableau packaged workbooks: (1) a past workbook that you have added interactivity to, and (2) the NYTimes workbook. As always, send the workbooks to caitlin@discoursemedia.org with subject "JOURN Week 5". Make sure to export your workbooks as a packaged workbook (File > Export Packaged Workbook...). This will ensure that the dataset remains connected to the workbook when you send it to me by email. See instructions for how to do this here.


Reading:

WEEK 6: Tableau "Stories" and other visualization tools

October 24th, 2017


Lecture slides: PDF (navigate w/ spacebar or arrow keys).

Guest lecture: Matthew Brehmer, Microsoft Research

Lecture overview: Sometimes Tableau can't do everything you need it to. What other tools are out there? What are your next steps in learning how to be a data journalist?


Lab workbooks: Story workbook

Lab data: Energy Access Data (CSV)

Lab overview: The objective of this lab is to introduce the story feature in Tableau and learn to produce static graphics in Adobe Illustrator.


Assignment overview: This is your final project worth 30 per cent of your mark.

By 9AM on October 31st, submit both documents in PDF format, send your Tableau file as a packaged workbook (tbwx format, not tbw format), and send the URL for your Tableau Public uploads by email, caitlin@discoursemedia.org with subject "JOURN Week 6".

Make sure to export your Music Sales workbook as a packaged workbook (File > Export Packaged Workbook...). This will ensure that the dataset remains connected to the workbook when you send it to me by email. See instructions for how to do this here.


Reading:

Other resources:

Further readings: Training and data: Previous versions of this course:

Credit:

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