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@mamacneil
Created November 21, 2018 13:04
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Lecture 11 - Tufte
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Perceptions\n",
"\n",
"Without thinking about it, we each bring our own baggage to how we percieve the world. Our experiences, culture, and values all shape our perceptions. Among the most difficult tasks for scientists is to convey information as clearly as possible, so that it can transcend as many of these individal biases as possible and so that the greatest number of people percieve our results in the same way."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[This example from Zoni Nation](https://github.com/zonination/perceptions/blob/master/README.md) illustrates one way in which data can help us understand how people commonly percieve lanugage:"
]
},
{
"attachments": {
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"
}
},
"cell_type": "markdown",
"metadata": {},
"source": [
"![joy1.png](attachment:joy1.png)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Tufte\n",
"\n",
"The grand patron of scientific graphics - **visualization** - is [Edward Tufte](https://www.edwardtufte.com/tufte/). *'a statistician and artist, and Professor Emeritus of Political Science, Statistics, and Computer Science at Yale University*'. If that sounds like a lot of things it is, the dude is utterly remarkable and, by all accounts, affable as hell. Tufte wrote (and self-published) four now classic books on visualization that, by coming up with princples underlying good visualizations, transformed discussion around how to graph data and convey information. Add [*Visual Display of Quantitative Information*](https://www.edwardtufte.com/tufte/books_vdqi) to your holiday gift list; it's specatcular. Today's lecture is entirely devoted to his design principles and how to implement them in R."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## \"Design cannot rescue failed content.\" - E.T.\n",
"\n",
"\n",
"### Visualization excellence\n",
"1. Consists of complex ideas communicated with clarity, precision, and efficiency\n",
"\n",
"2. Presents the greatest number of ideas in the shortest time with the least ink in the smallest space\n",
"\n",
"3. Is nearly always multivariate\n",
"\n",
"4. Requires telling the truth about the data\n",
"\n",
"\n",
"Acheiving these principles isn't necessarily easy - excellence isn't after all - but it is acheiveable. By keeping these ideas in mind and continually refining your visualization ideas, excellent graphics can follow. In addition, Tufte has complied so rules to help us along."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The Rules:\n",
"\n",
"1. Show Your Data\n",
"2. Use Graphics\n",
"3. Avoid Chartjunk\n",
"4. Utilize Data-ink\n",
"5. Use Labels\n",
"6. Utilize Micro/Macro\n",
"7. Separate Layers\n",
"8. Use Multiples\n",
"9. Utilize Color\n",
"10. Understand Narrative"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1. Show Your Data\n",
"\n",
"It may seem obvious, but soooo many graphics that end up being used in scientific publications do not show the underlying data used to create them. For example:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"library(ggplot2)\n",
"# Make plots a resonable size\n",
"options(repr.plot.width=4, repr.plot.height=4)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"mtcars2 <- mtcars\n",
"mtcars2$am <- factor(\n",
" mtcars$am, labels = c('automatic', 'manual')\n",
")\n",
"ggplot(mtcars2, aes(hp, mpg, color = am)) +\n",
" geom_smooth() +\n",
" theme(legend.position = 'bottom')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is an interesting graph, showing the relationship between gas consumption and engine displacement for automatic and manual transmissions. Taken at face value, it appears that manual transmissions likely become more efficient around 100 horsepower, then become dramatically less efficient above that before settling back down. However intution tells us that this is highly unlkely, as there is no mechanism by which an increase and decline should happen. Increase with horsepower maybe (dudes hooning with a big engine for example) but not a subsequent decline. But when the data are presented:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ggplot(mtcars2, aes(hp, mpg, color = am)) + geom_point() + geom_smooth() +\n",
" theme(legend.position = 'bottom')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This makes far more sense - the loess smoother fit to the data is clearly **overfitting** leading to a big spike due to adjacent low and high points prior to a gap in the data. By just looking at the points:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ggplot(mtcars2, aes(hp, mpg, color = am)) +\n",
" geom_point() + theme(legend.position = 'bottom')"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"the patern is far more clear - it looks like they have roughly paralell trends that can be better represented with a different smoother:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ggplot(mtcars2, aes(hp, mpg, color = am)) + geom_point() + stat_smooth(method = \"gam\", formula = y ~ s(x), size = 1) + theme(legend.position = 'bottom')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"or"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ggplot(mtcars2, aes(hp, mpg, color = am)) + geom_point() + stat_smooth(method = \"lm\", formula = y ~ poly(x, 2), size = 1) + theme(legend.position = 'bottom')"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"Choosing a smoother is an arbitrary decision that depends entirely on your objectives (like any statistical analysis) - this is why biological knowledge trumps statistical wizardry - with mechanistic models being the best (captures a process), liner models being the most general (capture overall trends), and smoothers being the most data-specific (captures patterns in the data you have, not in the data you might collect in the future). \n",
"\n",
"But the important principle here is that the data are **not hidden**!!\n",
"\n",
"This also applies to boxplots:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ToothGrowth$dose <- as.factor(ToothGrowth$dose)\n",
"head(ToothGrowth)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"p = ggplot(ToothGrowth, aes(x=dose, y=len)) + \n",
" geom_boxplot()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"p"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"p + geom_jitter(shape=16, position=position_jitter(0.1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Use Graphics\n",
"\n",
"Graphics here refers to little drawings - things that convey information directly and more succinctly than any text could. Small graphics in particular can enhance a plot in ways that words cannot. For example silhouettes added to a fitted model can elevate the information content and add connection to the natural world, reminding us that these are living things we're studying:\n",
"\n",
"\n",
"<img src=\"Figure_2.png\" alt=\"Drawing\" style=\"width: 800px;\"/>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3. Avoid chartjunk\n",
"\n",
"There was a time, in and around the 1980's when 'graphics' began to appear in print media like newspapers. It was remarkably awful:\n",
"\n",
"\n",
"<img src=\"chartjunk.jpg\" alt=\"Drawing\" style=\"width: 800px;\"/>\n",
"\n",
"Chartjunk refers to any visual elements in a visualization that are not necessary to understand information represented on the graph or that distract from understanding this information."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"# Task 1\n",
"---\n",
"\n",
"Chartjunk aside, in terms of information conent what else is wrong with this graphic?"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Your answer here (feel free to add cells to complete your answer)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"While the pie-eating clock is awful (or any pie chart for that matter), there are more subtle examples, even in R:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"height = c(1,2,3)\n",
"bardensity = c(10,10,20)\n",
"barangle = c(45,135,90)\n",
"barplot(height, density = bardensity, angle = barangle) "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These plots could simply use colours, or, more often than not, could avoid using barplots altogether. And they also display an interesting visual issue: Moiré vibration! What's that? Look deeply into the figure:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"options(repr.plot.width=7, repr.plot.height=4)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"plot(NA,NA, xlim=c(0,100), ylim=c(0,100), ylab=NA, xlab=NA, yaxt='n', xaxt='n', bty = \"n\")\n",
"for(i in seq(-15,500,6)) {\n",
" abline(i, -3, lwd=4)\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Annoying isn't it? Now you know. \n",
"\n",
"Textured fill lines - don't use 'em; rely on colours instead (but more on this in Lecture 12)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 4. Utilize data-ink\n",
"\n",
"When graphics get printed, they use ink to do it, and data-ink refers to the percentage of ink used that conveys information. The general principle is to remove as much ink from a graphic as possible while retaining ink that helps convey your information most effectively. **Remember: above all else convey information as clearly as possible**.\n",
"\n",
"How can data-ink be reduced? Well Tufte has extreme examples:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"boxplot(len ~ dose+supp, data=ToothGrowth)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"Can, in the right hands become:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"panel.tuftebxp <- \n",
"function (x, y, box.ratio = 1, box.width = box.ratio/(1 + box.ratio), horizontal=FALSE,\n",
" pch = box.dot$pch, col = box.dot$col, \n",
" alpha = box.dot$alpha, cex = box.dot$cex, font = box.dot$font, \n",
" fontfamily = box.dot$fontfamily, fontface = box.dot$fontface, \n",
" fill = box.rectangle$fill, varwidth = FALSE, notch = FALSE, \n",
" notch.frac = 0.5, ..., levels.fos = if (horizontal) sort(unique(y)) else sort(unique(x)), \n",
" stats = boxplot.stats, coef = 1.5, do.out = TRUE, identifier = \"bwplot\") \n",
"{\n",
" if (all(is.na(x) | is.na(y))) \n",
" return()\n",
" x <- as.numeric(x)\n",
" y <- as.numeric(y)\n",
" box.dot <- trellis.par.get(\"box.dot\")\n",
" box.rectangle <- trellis.par.get(\"box.rectangle\")\n",
" box.umbrella <- trellis.par.get(\"box.umbrella\")\n",
" plot.symbol <- trellis.par.get(\"plot.symbol\")\n",
" fontsize.points <- trellis.par.get(\"fontsize\")$points\n",
" cur.limits <- current.panel.limits()\n",
" xscale <- cur.limits$xlim\n",
" yscale <- cur.limits$ylim\n",
" if (!notch) \n",
" notch.frac <- 0\n",
" #removed horizontal code\n",
" blist <- tapply(y, factor(x, levels = levels.fos), stats, \n",
" coef = coef, do.out = do.out)\n",
" blist.stats <- t(sapply(blist, \"[[\", \"stats\"))\n",
" blist.out <- lapply(blist, \"[[\", \"out\")\n",
" blist.height <- box.width\n",
" if (varwidth) {\n",
" maxn <- max(table(x))\n",
" blist.n <- sapply(blist, \"[[\", \"n\")\n",
" blist.height <- sqrt(blist.n/maxn) * blist.height\n",
" }\n",
" blist.conf <- if (notch) \n",
" sapply(blist, \"[[\", \"conf\")\n",
" else t(blist.stats[, c(2, 4), drop = FALSE])\n",
" ybnd <- cbind(blist.stats[, 3], blist.conf[2, ], blist.stats[, \n",
" 4], blist.stats[, 4], blist.conf[2, ], blist.stats[, \n",
" 3], blist.conf[1, ], blist.stats[, 2], blist.stats[, \n",
" 2], blist.conf[1, ], blist.stats[, 3])\n",
" xleft <- levels.fos - blist.height/2\n",
" xright <- levels.fos + blist.height/2\n",
" xbnd <- cbind(xleft + notch.frac * blist.height/2, xleft, \n",
" xleft, xright, xright, xright - notch.frac * blist.height/2, \n",
" xright, xright, xleft, xleft, xleft + notch.frac * \n",
" blist.height/2)\n",
" xs <- cbind(xbnd, NA_real_)\n",
" ys <- cbind(ybnd, NA_real_)\n",
" panel.segments(rep(levels.fos, 2), c(blist.stats[, 2], \n",
" blist.stats[, 4]), rep(levels.fos, 2), c(blist.stats[, \n",
" 1], blist.stats[, 5]), col = box.umbrella$col, alpha = box.umbrella$alpha, \n",
" lwd = box.umbrella$lwd, lty = box.umbrella$lty, identifier = paste(identifier, \n",
" \"whisker\", sep = \".\"))\n",
"\n",
" if (all(pch == \"|\")) {\n",
" mult <- if (notch) \n",
" 1 - notch.frac\n",
" else 1\n",
" panel.segments(levels.fos - mult * blist.height/2, \n",
" blist.stats[, 3], levels.fos + mult * blist.height/2, \n",
" blist.stats[, 3], lwd = box.rectangle$lwd, lty = box.rectangle$lty, \n",
" col = box.rectangle$col, alpha = alpha, identifier = paste(identifier, \n",
" \"dot\", sep = \".\"))\n",
" }\n",
" else {\n",
" panel.points(x = levels.fos, y = blist.stats[, 3], \n",
" pch = pch, col = col, alpha = alpha, cex = cex, \n",
" identifier = paste(identifier, \n",
" \"dot\", sep = \".\"))\n",
" }\n",
" panel.points(x = rep(levels.fos, sapply(blist.out, length)), \n",
" y = unlist(blist.out), pch = plot.symbol$pch, col = plot.symbol$col, \n",
" alpha = plot.symbol$alpha, cex = plot.symbol$cex*0.5, \n",
" identifier = paste(identifier, \"outlier\", sep = \".\"))\n",
"\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"library(lattice)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"bwplot(len ~ dose+supp, data=ToothGrowth, panel= \n",
" function(x,y, ...) panel.tuftebxp(x=x,y=y,...))"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"The key with data-ink is to remove every possible bit of ink from a plot, then add back only a minimum level of detail needed to satisfy yourself on what looks 'right'."
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"---\n",
"# Task 2\n",
"---\n",
"\n",
"Plot the median value of the ToothGrowth length as a black dot (`pch` and `bg` are important here), and use the `lines()` function to plot approximate 50% ($\\pm$1 SD) and 95% ($\\pm$2 SD) confidence intervals as thick and thin lines respectively. Hints: you'll need to specifiy `ylim` values in `plot` to see the entire line, and use `lwd` in lines to make the thicker 50% line."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Your answer here (feel free to add cells to complete your answer)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## 5. Use labels\n",
"\n",
"Used judiciously, text labels on graphics convey much deeper meaning and enable connections to be made among graphics. The previous figure shows this in country labels on panel C:\n",
"\n",
"<img src=\"Figure_2.png\" alt=\"Drawing\" style=\"width: 800px;\"/>\n",
"\n",
"Without lables, these dots would fall flat; with it, the figure appeals to our nationalistic tendencies."
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"---\n",
"# Task 3\n",
"---\n",
"\n",
"Plot `hp` versus `mpg` in the `mtcars2` data and label the dots of four cars of interest to you in the data."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Your answer here (feel free to add cells to complete your answer)\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## 6. Utilize Micro/Macro\n",
"\n",
"A more subtle but still important rule, Tufte recommends adding detail to clarify meaning. Often this is an approach where a visualization contains enormous detail, so that an overall pattern emerges:\n",
"\n",
"\n",
"<img src=\"F1large.jpg\" alt=\"Drawing\" style=\"width: 800px;\"/>\n",
"\n",
"Or this example from the [New York Times](https://archive.nytimes.com/www.nytimes.com/interactive/2012/05/05/sports/baseball/mariano-rivera-and-his-peers.html?ref=baseball)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 7. Separate Layers\n",
"\n",
"Visually separating elements through the use of colour or shading is a critical skill to develop in producing good graphics. Visual separation allows information elements to be clear on their own, but also tied to a cohesive whole:\n",
"\n",
"<img src=\"Figure_2.png\" alt=\"Drawing\" style=\"width: 800px;\"/>\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 8. Use Multiples\n",
"\n",
"Among the most important graphic techniques emphasized by Tufte is the use of 'small multiples' repeated panels that convey (often temporal) differences (often in maps). For example this figure is highly effective:\n",
"\n",
"<img src=\"vouchermaps.png\" alt=\"Drawing\" style=\"width: 800px;\"/>\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Or something like:\n",
"\n",
"<img src=\"addl.png\" alt=\"Drawing\" style=\"width: 800px;\"/>\n",
"\n",
"\n",
"Or this from the [New York Times](https://www.nytimes.com/interactive/2018/01/21/world/year-in-weather.html#egtk)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These visualizations allow your eye to pass from one panel to the other, encouraging you to make connections among them. A graphical home-run."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"# Task 4\n",
"---\n",
"\n",
"Select a good colour scheme from ColorBrewer and use those values to differentiate the boxplots from `ggplot` object `p` above"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Your answer here (feel free to add cells to complete your answer)\n",
"p"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## 9. Utilize colour\n",
"\n",
"Colour, and mastery of it, will set your visualizations apart. The New York Times (again) uses colour excellently: \n",
"\n",
"<img src=\"oil.jpg\" alt=\"Drawing\" style=\"width: 800px;\"/>\n",
"\n",
"And are often a good source to sample colours from, using the eyedropper tool in your faviourite application (more on this next week). A great source for choosing colours is [ColorBrewer](http://colorbrewer2.org/#type=sequential&scheme=BuGn&n=3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"---\n",
"# Task 5\n",
"---\n",
"\n",
"Use the `facet_wrap` geom to plot player age versus batting average for every team in the MLB 2017 batting data. Be sure to label each panel with the team name code."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Your answer here (feel free to add cells to complete your answer)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 10. Understand Narrative\n",
"\n",
"Perhaps the hardest thing to convey but the most important skill to have in good graphical work is to understand narrative - that is, that your graphics need to tell a story. In fact, when I write papers for my own research the first step is always to figure out the figures, then write the text around them. Having a narrative that leads people from one idea to another is grounded in our deepest ideas and cultures. It remains powerful today:\n",
"\n",
"<img src=\"minard.gif\" alt=\"Drawing\" style=\"width: 1000px;\"/>\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# What have you learned and what's next?\n",
"\n",
"The point of today's lab was to introduce Tufte's principles for graphical excellence.\n",
"\n",
"**You should at this point be comfortable:**\n",
" 1. Knowing why each of the rules is important\n",
"\n",
"Next week we will get into some final details about graphics and how to produce them.\n",
"\n",
"---\n",
"# ** A bientôt ** !"
]
}
],
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