Introduction

.title[
# Introduction
]
.subtitle[
## Data Visualization
]
.author[
### Johan Larsson
]
.author[
### Behnaz Pirzamanbein
]
.institute[
### The Department of Statistics, Lund University
]

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# Why visualize?

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<div class="figure" style="text-align: center">
<img src="introduction_files/figure-html/unnamed-chunk-2-1.png" alt="Interest in data visualization as a fraction of the maximum interest recorderd (using Google Trends). The blue line represents a moving average." width="576" />
<p class="caption">Interest in data visualization as a fraction of the maximum interest recorderd (using Google Trends). The blue line represents a moving average.</p>
</div>

---

## Visualization as communication

* main goal is to **communicate** patterns in data
* we are wired to learn from **seeing**

<div class="figure" style="text-align: center">
<img src="images/napoleon.png" alt="Charles Minard's visualization of Napoleon's Russian campaign of 1812." width="853" height="30%" />
<p class="caption">Charles Minard's visualization of Napoleon's Russian campaign of 1812.</p>
</div>

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.pull-left[
<table class="table" style="font-size: 13px; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;"> region </th>
   <th style="text-align:right;"> employment (%) </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Stockholms län </td>
   <td style="text-align:right;"> 72.7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Hallands län </td>
   <td style="text-align:right;"> 72.1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Jönköpings län </td>
   <td style="text-align:right;"> 70.9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Västra Götalands län </td>
   <td style="text-align:right;"> 70.0 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Kronobergs län </td>
   <td style="text-align:right;"> 69.3 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Uppsala län </td>
   <td style="text-align:right;"> 68.4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gotlands län </td>
   <td style="text-align:right;"> 68.2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Östergötlands län </td>
   <td style="text-align:right;"> 67.4 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Värmlands län </td>
   <td style="text-align:right;"> 67.1 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Jämtlands län </td>
   <td style="text-align:right;"> 66.2 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Örebro län </td>
   <td style="text-align:right;"> 66.0 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Västmanlands län </td>
   <td style="text-align:right;"> 65.7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Gävleborgs län </td>
   <td style="text-align:right;"> 65.0 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Västerbottens län </td>
   <td style="text-align:right;"> 64.9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Kalmar län </td>
   <td style="text-align:right;"> 64.9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Skåne län </td>
   <td style="text-align:right;"> 64.8 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Dalarnas län </td>
   <td style="text-align:right;"> 64.7 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Västernorrlands län </td>
   <td style="text-align:right;"> 64.6 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Blekinge län </td>
   <td style="text-align:right;"> 63.9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Norrbottens län </td>
   <td style="text-align:right;"> 62.9 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Södermanlands län </td>
   <td style="text-align:right;"> 62.8 </td>
  </tr>
</tbody>
</table>
]

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.pull-right[
<img src="introduction_files/figure-html/unnamed-chunk-5-1.png" width="324" style="display: block; margin: auto;" />
]

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class: section-title

# An example

## GDP per capita and life expectancy across time

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## First attempt

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## Transforming the axis

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## Grouping time, adding population

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## Animated plots (using **gganimate**)

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## Knowledge and understanding

* demonstrate knowledge of the theoretical and practical construction of
  visualisations, and
* demonstrate understanding of how the type of data impacts the visualisation
  and what components are appropriate.

## Competence and skills

* demonstrate the skill to independently, using software, visualise various
  types of data,
* demonstrate the ability to make appropriate choices in designing
  visualisations, and
* demonstrate the ability to in writing present and discuss visualisations
  in dialogue with others.

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## Judgement and approach

* demonstrate the ability to assess visualisations with respect to
  clarity, accessibility and ethics, and
* demonstrate insight into the importance of the design of visualisations
  with respect to communicative properties, accessibility and ethics.

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# Course structure

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## Topics

* introduction to R and R Studio
* introduction to ggplot2
* basics of data visualizations
* visualizations with one variable
* visualizations with several variables
* maps
* interactive and animated visualizations

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## Learning activities

* lectures
* text
* worked examples

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## Examination

### Assessment

* quizzes
* assignments
* project

The assignment and project will be reviewed through peer-feedback.
]

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# Good luck!

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## References

<a name=bib-reinsel2018></a>[Reinsel, D., J. Gantz, and J.
Rydning](#cite-reinsel2018) (2018). _The Digitization of the World:
From Edge to Core_. US44413318. MA, USA: IDC, p. 28.