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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>Tips for effective data visualization</title>
<meta charset="utf-8" />
<script src="libs/header-attrs/header-attrs.js"></script>
<link href="libs/font-awesome/css/all.min.css" rel="stylesheet" />
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<link href="libs/panelset/panelset.css" rel="stylesheet" />
<script src="libs/panelset/panelset.js"></script>
<link rel="stylesheet" href="../xaringan-themer.css" type="text/css" />
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</head>
<body>
<textarea id="source">
class: center, middle, inverse, title-slide
.title[
# Tips for effective data visualization
]
.subtitle[
## <br><br> College of the Atlantic
]
---
class: middle
# Designing effective visualizations
---
## Keep it simple
.pull-left-narrow[
<img src="img/pie-3d.jpg" width="100%" style="display: block; margin: auto;" />
]
.pull-right-wide[
<img src="u2-d14-effective-dataviz_files/figure-html/pie-to-bar-1.png" width="100%" style="display: block; margin: auto;" />
]
---
## Use color to draw attention
.pull-left[
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-2-1.png" width="100%" style="display: block; margin: auto;" />
]
.pull-right[
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-3-1.png" width="100%" style="display: block; margin: auto;" />
]
---
## Tell a story
<img src="img/time-series-story.png" width="80%" style="display: block; margin: auto;" />
.footnote[
Credit: Angela Zoss and Eric Monson, Duke DVS
]
---
class: middle
# Principles for effective visualizations
---
## Principles for effective visualizations
- Order matters
- Put long categories on the y-axis
- Keep scales consistent
- Select meaningful colors
- Use meaningful and nonredundant labels
---
## Data
In September 2019, YouGov survey asked 1,639 GB adults the following question:
.pull-left[
> In hindsight, do you think Britain was right/wrong to vote to leave EU?
>
>- Right to leave
>- Wrong to leave
>- Don't know
]
.pull-right[
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-6-1.png" width="100%" style="display: block; margin: auto;" />
]
.footnote[
Source: [YouGov Survey Results](https://d25d2506sfb94s.cloudfront.net/cumulus_uploads/document/x0msmggx08/YouGov%20-%20Brexit%20and%202019%20election.pdf), retrieved Oct 7, 2019
]
---
class: middle
# Order matters
---
## Alphabetical order is rarely ideal
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-7-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(x = opinion)) +
geom_bar()
```
]
]
---
## Order by frequency
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-8-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
`fct_infreq`: Reorder factors' levels by frequency
```r
*ggplot(brexit, aes(x = fct_infreq(opinion))) +
geom_bar()
```
]
]
---
## Clean up labels
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-9-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(x = opinion)) +
geom_bar() +
* labs(
* x = "Opinion",
* y = "Count"
* )
```
]
]
---
## Alphabetical order is rarely ideal
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-10-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(x = region)) +
geom_bar()
```
]
]
---
## Use inherent level order
.panelset[
.panel[.panel-name[Relevel]
`fct_relevel`: Reorder factor levels using a custom order
```r
brexit <- brexit %>%
mutate(
* region = fct_relevel(
region,
"london", "rest_of_south", "midlands_wales", "north", "scot"
)
)
```
]
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-11-1.png" width="60%" style="display: block; margin: auto;" />
]
]
---
## Clean up labels
.panelset[
.panel[.panel-name[Recode]
`fct_recode`: Change factor levels by hand
```r
brexit <- brexit %>%
mutate(
* region = fct_recode(
region,
London = "london",
`Rest of South` = "rest_of_south",
`Midlands / Wales` = "midlands_wales",
North = "north",
Scotland = "scot"
)
)
```
]
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/recode-plot-1.png" width="60%" style="display: block; margin: auto;" />
]
]
---
class: middle
# Put long categories on the y-axis
---
## Long categories can be hard to read
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-12-1.png" width="60%" style="display: block; margin: auto;" />
---
## Move them to the y-axis
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-13-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
*ggplot(brexit, aes(y = region)) +
geom_bar()
```
]
]
---
## And reverse the order of levels
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-14-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
`fct_rev`: Reverse order of factor levels
```r
*ggplot(brexit, aes(y = fct_rev(region))) +
geom_bar()
```
]
]
---
## Clean up labels
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-15-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = fct_rev(region))) +
geom_bar() +
* labs(
* x = "Count",
* y = "Region"
* )
```
]
]
---
class: middle
# Pick a purpose
---
## Segmented bar plots can be hard to read
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-16-1.png" width="60%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
*ggplot(brexit, aes(y = region, fill = opinion)) +
geom_bar()
```
]
]
---
## Use facets
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-17-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = region)) +
geom_bar() +
* facet_wrap(~region, nrow = 1)
```
]
]
---
## Avoid redundancy?
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-18-1.png" width="90%" style="display: block; margin: auto;" />
---
## Redundancy can help tell a story
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-19-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1)
```
]
]
---
## Be selective with redundancy
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-20-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1) +
* guides(fill = "none")
```
]
]
---
## Use informative labels
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-21-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1) +
guides(fill = "none") +
labs(
* title = "Was Britain right/wrong to vote to leave EU?",
x = NULL, y = NULL
)
```
]
]
---
## A bit more info
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-22-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1) +
guides(fill = "none") +
labs(
title = "Was Britain right/wrong to vote to leave EU?",
* subtitle = "YouGov Survey Results, 2-3 September 2019",
* caption = "Source: https://d25d2506sfb94s.cloudfront.net/cumulus_uploads/document/x0msmggx08/YouGov%20-%20Brexit%20and%202019%20election.pdf",
x = NULL, y = NULL
)
```
]
]
---
## Let's do better
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-23-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1) +
guides(fill = "none") +
labs(
title = "Was Britain right/wrong to vote to leave EU?",
subtitle = "YouGov Survey Results, 2-3 September 2019",
* caption = "Source: bit.ly/2lCJZVg",
x = NULL, y = NULL
)
```
]
]
---
## Fix up facet labels
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-24-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region,
nrow = 1,
* labeller = label_wrap_gen(width = 12)
) +
guides(fill = "none") +
labs(
title = "Was Britain right/wrong to vote to leave EU?",
subtitle = "YouGov Survey Results, 2-3 September 2019",
caption = "Source: bit.ly/2lCJZVg",
x = NULL, y = NULL
)
```
]
]
---
class: middle
# Select meaningful colors
---
## Rainbow colors not always the right choice
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-25-1.png" width="90%" style="display: block; margin: auto;" />
---
## Manually choose colors when needed
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-26-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1, labeller = label_wrap_gen(width = 12)) +
guides(fill = "none") +
labs(title = "Was Britain right/wrong to vote to leave EU?",
subtitle = "YouGov Survey Results, 2-3 September 2019",
caption = "Source: bit.ly/2lCJZVg",
x = NULL, y = NULL) +
* scale_fill_manual(values = c(
* "Wrong" = "red",
* "Right" = "green",
* "Don't know" = "gray"
* ))
```
]
]
---
## Choosing better colors
.center[.large[
[colorbrewer2.org](https://colorbrewer2.org/)
]]
<img src="img/color-brewer.png" width="60%" style="display: block; margin: auto;" />
---
## Use better colors
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-28-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1, labeller = label_wrap_gen(width = 12)) +
guides(fill = "none") +
labs(title = "Was Britain right/wrong to vote to leave EU?",
subtitle = "YouGov Survey Results, 2-3 September 2019",
caption = "Source: bit.ly/2lCJZVg",
x = NULL, y = NULL) +
scale_fill_manual(values = c(
* "Wrong" = "#ef8a62",
* "Right" = "#67a9cf",
* "Don't know" = "gray"
))
```
]
]
---
## Select theme
.panelset[
.panel[.panel-name[Plot]
<img src="u2-d14-effective-dataviz_files/figure-html/unnamed-chunk-29-1.png" width="90%" style="display: block; margin: auto;" />
]
.panel[.panel-name[Code]
```r
ggplot(brexit, aes(y = opinion, fill = opinion)) +
geom_bar() +
facet_wrap(~region, nrow = 1, labeller = label_wrap_gen(width = 12)) +
guides(fill = "none") +
labs(title = "Was Britain right/wrong to vote to leave EU?",
subtitle = "YouGov Survey Results, 2-3 September 2019",
caption = "Source: bit.ly/2lCJZVg",
x = NULL, y = NULL) +
scale_fill_manual(values = c("Wrong" = "#ef8a62",
"Right" = "#67a9cf",
"Don't know" = "gray")) +
* theme_minimal()
```
]
]
---
.your-turn[
### .hand[Your turn!]
.midi[
- RStudio Cloud > `AE 07 - Brexit + Telling stories with dataviz` > `brexit.Rmd`.
- Change the visualisation in three different ways to tell slightly different stories with it each time.
]
]
---
## Acknowledgements
* This course builds on the materials from [Data Science in a Box](https://datasciencebox.org/) developed by Mine Çetinkaya-Rundel and are adapted under the [Creative Commons Attribution Share Alike 4.0 International](https://github.com/rstudio-education/datascience-box/blob/master/LICENSE.md)
</textarea>
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var slide, slides = slideshow.getSlides(), els = el[0].children;
for (var i = 1; i < slides.length; i++) {
slide = slides[i];
if (slide.properties.continued === "true" || slide.properties.count === "false") {
els[i - 1].className += ' has-continuation';
}
}
var s = d.createElement("style");
s.type = "text/css"; s.innerHTML = "@media print { .has-continuation { display: none; } }";
d.head.appendChild(s);
})(document);
// delete the temporary CSS (for displaying all slides initially) when the user
// starts to view slides
(function() {
var deleted = false;
slideshow.on('beforeShowSlide', function(slide) {
if (deleted) return;
var sheets = document.styleSheets, node;
for (var i = 0; i < sheets.length; i++) {
node = sheets[i].ownerNode;
if (node.dataset["target"] !== "print-only") continue;
node.parentNode.removeChild(node);
}
deleted = true;
});
})();
// add `data-at-shortcutkeys` attribute to <body> to resolve conflicts with JAWS
// screen reader (see PR #262)
(function(d) {
let res = {};
d.querySelectorAll('.remark-help-content table tr').forEach(tr => {
const t = tr.querySelector('td:nth-child(2)').innerText;
tr.querySelectorAll('td:first-child .key').forEach(key => {
const k = key.innerText;
if (/^[a-z]$/.test(k)) res[k] = t; // must be a single letter (key)
});
});
d.body.setAttribute('data-at-shortcutkeys', JSON.stringify(res));
})(document);
(function() {
"use strict"
// Replace <script> tags in slides area to make them executable
var scripts = document.querySelectorAll(
'.remark-slides-area .remark-slide-container script'
);
if (!scripts.length) return;
for (var i = 0; i < scripts.length; i++) {
var s = document.createElement('script');
var code = document.createTextNode(scripts[i].textContent);
s.appendChild(code);
var scriptAttrs = scripts[i].attributes;
for (var j = 0; j < scriptAttrs.length; j++) {
s.setAttribute(scriptAttrs[j].name, scriptAttrs[j].value);
}
scripts[i].parentElement.replaceChild(s, scripts[i]);
}
})();
(function() {
var links = document.getElementsByTagName('a');
for (var i = 0; i < links.length; i++) {
if (/^(https?:)?\/\//.test(links[i].getAttribute('href'))) {
links[i].target = '_blank';
}
}
})();
// adds .remark-code-has-line-highlighted class to <pre> parent elements
// of code chunks containing highlighted lines with class .remark-code-line-highlighted
(function(d) {
const hlines = d.querySelectorAll('.remark-code-line-highlighted');
const preParents = [];
const findPreParent = function(line, p = 0) {
if (p > 1) return null; // traverse up no further than grandparent
const el = line.parentElement;
return el.tagName === "PRE" ? el : findPreParent(el, ++p);
};
for (let line of hlines) {
let pre = findPreParent(line);
if (pre && !preParents.includes(pre)) preParents.push(pre);
}
preParents.forEach(p => p.classList.add("remark-code-has-line-highlighted"));
})(document);</script>
<script>
slideshow._releaseMath = function(el) {
var i, text, code, codes = el.getElementsByTagName('code');
for (i = 0; i < codes.length;) {
code = codes[i];
if (code.parentNode.tagName !== 'PRE' && code.childElementCount === 0) {
text = code.textContent;
if (/^\\\((.|\s)+\\\)$/.test(text) || /^\\\[(.|\s)+\\\]$/.test(text) ||
/^\$\$(.|\s)+\$\$$/.test(text) ||
/^\\begin\{([^}]+)\}(.|\s)+\\end\{[^}]+\}$/.test(text)) {
code.outerHTML = code.innerHTML; // remove <code></code>
continue;
}
}
i++;
}
};
slideshow._releaseMath(document);
</script>
<!-- dynamically load mathjax for compatibility with self-contained -->
<script>
(function () {
var script = document.createElement('script');
script.type = 'text/javascript';
script.src = 'https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-MML-AM_CHTML';
if (location.protocol !== 'file:' && /^https?:/.test(script.src))
script.src = script.src.replace(/^https?:/, '');
document.getElementsByTagName('head')[0].appendChild(script);
})();
</script>
</body>
</html>