---
title: "Making charts"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{charts}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---






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## `reschola` and charts

This document assumes two things:

- charts are made in ggplot2
- you have a fair understanding of ggplot2, so this is not a guide to using that package.

It also does not reiterate the principles of data visualisation, though it does point to some resources in that vein.

## The reschola theme

##### Global theme setting {.bs-callout .bs-callout-blue}

You can set the theme for your whole Rmarkdown document (or session, for that matter) by putting `theme_set(theme_schola())`. Then you don't need to add it to your plots. As `theme_schola()` has parameters which you are likely to need, this seems impractical and anyway could be confusing.

### Basic usage of `theme_schola()`

`reschola` contains the `theme_schola()` theme, which has

- sensible defaults so you are not forever changing the same parameters
- some aesthetic choices custom for Schola Emppirica
- good default fonts

The examples below serve as (a) guide to the parameters of the theme, (b) test, and (c) showcase.

> Resolution and sizes can be off on this page. The templates contained in this package are optimised to produce great looking and properly sized charts in Word documents.

First, let's see the default plot, no theme


```r
p <- ggplot(mpg) +
 geom_bar(aes(y = class)) +
 labs(title = "Lots of cars", subtitle = "Count of numbers")
p
```

<img src="charts-no-theme-1.png" title="plot of chunk no-theme" alt="plot of chunk no-theme" width="100%" />

Now let's see what `theme_schola()` defaults do


```r
p +
 theme_schola("x") # only setting the first parameter to get the right gridlines
```

<img src="charts-schola-default-1.png" title="plot of chunk schola-default" alt="plot of chunk schola-default" width="100%" />

in combination with `flush_axis`


```r
p +
 theme_schola("x") +
 scale_x_continuous(expand = flush_axis)
```

<img src="charts-flush-1.png" title="plot of chunk flush" alt="plot of chunk flush" width="100%" />

Scatterplot


```r
ggplot(mpg) +
 geom_point(aes(cty, hwy)) +
 theme_schola("scatter") +
 labs(title = "Lots of cars", subtitle = "Point by point")
```

<img src="charts-scatter-1.png" title="plot of chunk scatter" alt="plot of chunk scatter" width="100%" />

Smaller text, flush plot alignment


```r
ggplot(mpg) +
 geom_point(aes(cty, hwy), alpha = .2) +
 theme_schola("scatter", base_size = 9, margin_side = 0) +
 labs(title = "Lots of cars", subtitle = "Point by point")
```

<img src="charts-scatter-flush-1.png" title="plot of chunk scatter-flush" alt="plot of chunk scatter-flush" width="100%" />

If you are adding a caption in your Rmarkdown chunk, you may also want `margin_bottom = 0` to cut the bottom margin in the plot and move the caption closer to the plot.

#### Override defaults changed inside `theme_schola()`


```r
ggplot(mpg) +
 geom_point(aes(cty, hwy), alpha = .2) +
 theme_schola("scatter", base_size = 12, margin_side = 0) +
 labs(title = "Lots of cars", subtitle = "Point by point") +
 theme(panel.background = element_rect(fill = "lightpink"))
```

<img src="charts-scatter-defaultschanged-1.png" title="plot of chunk scatter-defaultschanged" alt="plot of chunk scatter-defaultschanged" width="100%" />

#### Small mutliples


```r
p +
 theme_schola("x", multiplot = T) +
 scale_x_continuous(expand = flush_axis) +
 facet_wrap(~ manufacturer, nrow = 2)
```

<img src="charts-multiples-1.png" title="plot of chunk multiples" alt="plot of chunk multiples" width="100%" />

Same without aesthetic adjustment for `facet_wrap()`


```r
p +
 theme_schola("x", multiplot = F) +
 scale_x_continuous(expand = flush_axis) +
 facet_wrap(~ manufacturer, nrow = 2)
```

<img src="charts-multiples-nomultiplot-1.png" title="plot of chunk multiples-nomultiplot" alt="plot of chunk multiples-nomultiplot" width="100%" />

Small mutliples scatter


```r
ggplot(mpg) +
 geom_point(aes(cty, hwy), alpha = .2) +
 theme_schola("scatter", multiplot = T) +
 labs(title = "Lots of cars", subtitle = "Point by point") +
 facet_wrap(~ class, nrow = 2)
```

<img src="charts-multiples-scatter-1.png" title="plot of chunk multiples-scatter" alt="plot of chunk multiples-scatter" width="100%" />

Small mutliples grid


```r
p +
 theme_schola("x", multiplot = T) +
 scale_x_continuous(expand = flush_axis) +
 facet_grid(cyl ~ drv)
```

<img src="charts-multiples-grid-1.png" title="plot of chunk multiples-grid" alt="plot of chunk multiples-grid" width="100%" />

Small mutliples scatter grid


```r
ggplot(mpg) +
 geom_point(aes(cty, hwy), alpha = .2) +
 theme_schola("scatter", multiplot = T) +
 labs(title = "Lots of cars", subtitle = "Point by point") +
 facet_grid(cyl ~ class)
```

<img src="charts-multiples-scatter-grid-1.png" title="plot of chunk multiples-scatter-grid" alt="plot of chunk multiples-scatter-grid" width="100%" />

Same but without multiplot parameter


```r
ggplot(mpg) +
 geom_point(aes(cty, hwy), alpha = .2) +
 theme_schola("scatter", multiplot = F) +
 labs(title = "Lots of cars", subtitle = "Point by point") +
 facet_grid(cyl ~ class)
```

<img src="charts-multiples-scatter-grid-nomultiplot-1.png" title="plot of chunk multiples-scatter-grid-nomultiplot" alt="plot of chunk multiples-scatter-grid-nomultiplot" width="100%" />


## Building a diverging Likert plot

[To be completed once the function is in place]

## Using colour scales

[To be completed once the scales are in place]

## Using custom numeric scales

The chartb below illustrates the custom scales


```r
ggplot(mpg, aes(hwy * 100, cty/max(cty))) +
  geom_point(aes(colour = cty/max(cty), size = hwy*100)) +
  theme_schola() +
  scale_y_percent_cz() +
  scale_x_number_cz() +
  scale_color_binned(labels = label_percent_cz()) +
  scale_size_binned(labels = label_number_cz())
```

<img src="charts-scales-1.png" title="plot of chunk scales" alt="plot of chunk scales" width="100%" />
The percent formatter and number formatter also handle the decimal mark correctly. The parameters which you would normally find inside the `scales::format_*()` functions are accessible directly in the `scale_[xy]_continuous()` functions.


```r
ggplot(mpg, aes(hwy / 100, cty/max(cty)/100)) +
  geom_point(aes(colour = cty/max(cty), size = hwy*100)) +
  theme_schola() +
  scale_y_percent_cz(accuracy = .1) +
  scale_x_number_cz(accuracy = .1) +
  scale_color_binned(labels = label_percent_cz(accuracy = .1)) +
  scale_size_binned(labels = label_number_cz(accuracy = 0.1))
```

<img src="charts-scales-decimal-1.png" title="plot of chunk scales-decimal" alt="plot of chunk scales-decimal" width="100%" />

An English-locale version would look like this, using functions in `scales` or reexported from `hrbrthemes`:


```r
ggplot(mpg, aes(hwy * 100, cty/max(cty))) +
  geom_point(aes(colour = cty/max(cty), size = hwy*100)) +
  theme_schola() +
  scale_y_percent(accuracy = .1) +
  scale_x_comma(accuracy = .1) +
  scale_color_binned(labels = scales::label_percent(accuracy = .1)) +
  scale_size_binned(labels = scales::label_number(accuracy = .1))
```

<img src="charts-scales-en-1.png" title="plot of chunk scales-en" alt="plot of chunk scales-en" width="100%" />

## Sizing images

The `schola_[word|pdf]` formats have opinionated sizing defaults to ensure that resolution, size and font size in the bitmap (PNG) image are in line with the rest of the document.
This is particularly tricky in the context of Word documents, hence the baked in defaults. For this reason, the steps to change images sizes are a bit special - see below.

Here is what the defaults are:

- width is full-page, i.e. 15.98 cm (so the image is sized exactly to fit inside margings without any resizing which would degrade quality)
- resolution at 300 DPI and pixel size to result in sharp image with exactly same font size as document
- height is width divided by the golden ratio, i.e. default height is 9.92 cm

Here is how to manipulate image sizes without messing up anything else, in Word:

- to change the **height**, set the `fig.asp` chunk option to more or less than 0.62
- to change the **width**, set chunk options `fig.width` and `out.width` to the same size in centimeters, e.g. for half-width you would do `fig.width=7.98/2.54, out.width="7.98cm"` (because `fig.width` is set in inches).
Note the quotes around the `out.width` value - this is a special thing for pandoc to ensure the sizing is reflected in the layout of the Word document. The height in this case will be 7.98 * 0.62 cm (see above)
- so to change **both width and height**, set the `fig.asp` param as per above.

For **HTML** output, you can use e.g. `out.width="50%"`.

For **PDF** output, you can just set `fig.width` in inches and the height using `fig.asp` as above, as long as you use the `pdf` or `cairo_pdf` device (using the `dev` option in the chunk or at per-document level.)
Note that the font handling might be a bit tricky for PDF depending on your system.

Image sizing works quite differently between output formats (HTML, PDF, Word).
For that reason it is probably the one thing that will look odd or break if you try to render a document written in a reschola template into HTML or PDF without fiddling with sizing, graphic devices or font handling.

## Making fonts work

The `schola_theme()` is set to use the Ubuntu and Ubuntu Condensed font families by default.
These may not be present on your system.
You can install them with `reschola::install_reschola_fonts()` and by running `reschola::register_reschola_fonts()` (only needed on Windows if you use Windows bitmap devices -- which are default).
On package load, these will be registered with R.
If the fonts do not show up in your charts, run `extrafont::loadfonts()` (once per session).
You can also set the option `reschola.loadfonts` to have `reschola` register these fonts with the PDF/PostScript ecosystem upon package load. (The fonts may or may not work out of the box when you render into PDF depending on your system -- if not, first try using the `cairo_pdf` device and/or running `extrafont::embed_fonts()` on the whole resulting PDF document.)

## Using fonts

If you end up using different fonts, it is good to choose something that (a) has fixed-width figures in the default set of characters, and (b) has sensible widths or a narrow-width member of the type family (usually called "Condensed", "Narrow" or some such.)

The `hrbrthemes` package has a good range of fonts, some of which tick these criteria. Arial Narrow is narrow and has fixed-width figures.
IBM Plex Sans, Titillium Sans and Econ Sans all have fixed width figures but not all have Narrow companions.

Public Sans does not have fixed-width figures.

See the [hrbrthemes vignette](https://cran.r-project.org/web/packages/hrbrthemes/vignettes/why_hrbrthemes.html#kern-what) for an explanation of why these criteria matter

## Tricks of the trade for ggplot2

- `theme_void()` for visuals that don't need any gridlines, axes, etc., such as schematic maps
- aes(..., group = 1) for making all data points in a `geom_line()` into one line
- `key_glyph` parameter to geoms to pick a specific shape for the legend key
- `geom_sf_label` for intelligently labelling spatial features plotted through `geom_sf()`
- `labs(colour = NULL)` for switching off the colour legend, `labs(x = NULL)` to turn off colour label -  quicker than `theme(axis.label.x = element_blank())` and `guides(colour = "none")`

## Resources on good practice

Kieran Healy. [Data Visualisation: a practical introduction](http://socviz.co). With R code.

Claus Wilke.    [Fundamentals of Data Visualisation](https://serialmentor.com/dataviz/) No R code, very strong on principles.

Beyond that and in the world of paper books, anything by Alberto Cairo is solid.

## Handy (or just cool) ggplot2 extensions

### Crucial

- `patchwork` for combining multiple plots into one in a simple, intuitive way, while merging legends and aligning everyhing as needed
- `ggraph` in combination with `tidygraph` for network data
- `ggcorr` for correlation matrices
- `GGally` with a set of utilities, incl. `GGally::ggpairs()`
- `sjPlot` also provides useful visual forms, most usefully the visual and tabular summaries of model results

### Useful

- `ggtext` for formatting pretty much any text in a ggplot using Markdown/HTML
- `ggiraph` for basic web interactivity
- `ggforce` for cool annotation
- `ggrepel` for handling overlapping labels
- `gghighlight` for highlighting individual points/series
- `ggmosaic` for mosaic plots
- `ggalluvial` for Sankey diagrams
- `waffle` for waffle (square pie) charts incl Isotype-style charts using icons

### Fun

- `ggchiclet` for rounded bars
