Last Day: scrollytelling + wrap up

.title[
# Last Day: scrollytelling + wrap up
]
.author[
### MACS 40700 <br /> University of Chicago
]

---

# Announcements

---

## Announcements
* TODAY!! wrap + conference/work time
* All grades back
* 3/11 final due!!

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## Agenda

* Scrollytelling
* Work time
* Recap
* Learning objectives

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# Scrollytelling

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## getting started

* download our repo: `usethis::use_course("MACS40700/scrollytelling")`
* navigate to the folder in the terminal
* in TERMINAL: `quarto add qmd-lab/closeread` **IN THE EXACT FOLDER**
* be nice to coding gods
* SOURCE: https://closeread.dev/

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## Closeread errors

* using cloud storage for device
* wrong package libraries
* added closeread to wrong directory file (one level up)

---
# Closeread: overview

* Doc setup (front matter)
* Sections: By default, all elements with a Closeread section appear as the narrative, scrolling by, unless you’ve indicated that they should be a sticky.
* Stickies: Sticky elements are placed in the main column of the Closeread section and will be transparent. 
* Triggers: The primary role of triggers is to make a sticky element appear.
* Overall design (e.g. layouts)

---
## Setting up your doc: make it a closeread doc

``` r
---
title: My First Closeread
format: closeread-html
---
```

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## Adding sections:

``` r
:::{.cr-section} # opens the section

::: # closes the section
```

* can wrap the whole doc in this
* can add additional sections

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## Stickies: focus effects

* Scaling
* Panning
* Zooming
* Highlighting
* Combos (you can mix and match)

---

## Layout options

* sidebar-left (default)
* sidebar-right
* overlay-left
* overlay-center
* overlay-right

``` r
---
format:
  closeread-html:
    cr-section:
      layout: "overlay-center"
---
```

---
### Example: Minard's map

``` r
knitr::include_url("https://closeread.dev/gallery/examples/minards-map/")
```

---
# Recap

* Foundational components
    * 'Layer cake' approach
    * Using Github and RMD files
    * Basic three: labeling axes/title, use of color palette, tell one thing
    * Faceting/gghighlight
  
--

* 'Advanced' Visualizations
    * Tableau
    * Shiny
    * Plotly
    * Websites
    * Scrollytelling (brief intro)

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# Learning Objectives
*By the end of the course, students will be able to:*

1. Understand the principles of designing and creating effective data visualizations.

1. Evaluate, critique, and improve upon one’s own and others’ data visualizations based on how good a job the visualization does for communicating a message clearly and correctly.

1. Post-process and refine plots for effective communication.

1. Master using R and a variety of modern data visualization packages to create data visualizations.

1. Work reproducibly individually and collaboratively using Git and GitHub.

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# What we did

* Assignments on github (items 1, 2, 5 and 5)
* In-class applications and analysis (items 1,2, 3, 4)
* Final project (items 1-5)

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# How we did it

* Build a community of inquiry -- can offer feedback and critique
* Strong engagement
* Challenging ourselves to think through beyond the superficial
* Continuing to build, scaffold, and refine

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# Looking ahead: evaluations
Role of evaluations to help understand how the course contributes to your learning.

* Please fill them out!
* Be specific!
  * NO: 'I didn't like this class'
  * YES: 'I didn't like this class because I wanted more assignments'
* Think about elements that were/not helpful for learning -- I tried to build a course that would meet people where they were with their level of experience and allow them to deepen their skillset in a meaningful way
* Looking ahead: Python? R? Tableau? Scrollytelling?

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# Specific questions on evals (extra Qs)

* What were the most helpful skills/topics that we covered in the course and why?

* What additional skills or topics do you wish we had covered? Please be specific.

* Would you prefer to have content that is less specific about coding (examples, how-to) and incorporate multiple languages or keep it to one language?

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# Thank you and good luck on your final project!