https://github.com/clauswilke/multiscales

Multivariate scales for ggplot2
https://github.com/clauswilke/multiscales

Last synced: 17 days ago
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Multivariate scales for ggplot2

• Host: GitHub
• URL: https://github.com/clauswilke/multiscales
• Owner: clauswilke
• License: other
• Created: 2018-06-22T18:24:37.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2022-01-05T18:40:53.000Z (almost 3 years ago)
• Last Synced: 2024-10-14T17:28:58.489Z (about 1 month ago)
• Language: R
• Homepage:
• Size: 5.49 MB
• Stars: 100
• Watchers: 6
• Forks: 2
• Open Issues: 4
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

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README

        
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  dpi = 300

)

```

# multiscales

Multivariate scales for ggplot2, written by Claus O. Wilke

## Installation

This package can be installed from github. It requires the development version of the colorspace package. It also requires ggplot2 3.0.0, which was released on July 3, 2018.

```

install.packages("colorspace", repos = "http://R-Forge.R-project.org")

devtools::install_github("clauswilke/multiscales")

```

This is an experimental package. Use at your own risk. API is not stable. No user support provided.

## Examples

Visualizing the lead/lag of Clinton vs. Trump in the 2016 presidential election jointly with the uncertainty of the lead/lag estimates. This visualization shows that for many states the outcome was difficult to predict. (Example taken from Correll et al., [Value-Suppressing Uncertainty Palettes](https://idl.cs.washington.edu/files/2018-UncertaintyPalettes-CHI.pdf), CHI 2018.)

```{r message = FALSE}

library(ggplot2)

library(multiscales)

colors <- scales::colour_ramp(

  colors = c(red = "#AC202F", purple = "#740280", blue = "#2265A3")

)((0:7)/7)

ggplot(US_polling) + 

  geom_sf(aes(fill = zip(Clinton_lead, moe_normalized)), color = "gray30", size = 0.2) + 

  coord_sf(datum = NA) +

  bivariate_scale("fill",

    pal_vsup(values = colors, max_desat = 0.8, pow_desat = 0.2, max_light = 0.7, pow_light = 1),

    name = c("Clinton lead", "uncertainty"),

    limits = list(c(-40, 40), c(0, 1)),

    breaks = list(c(-40, -20, 0, 20, 40), c(0, 0.25, 0.50, 0.75, 1.)),

    labels = list(waiver(), scales::percent),

    guide = "colourfan"

  ) +

  theme_void() +

  theme(

    legend.key.size = grid::unit(0.8, "cm"),

    legend.title.align = 0.5,

    plot.margin = margin(5.5, 20, 5.5, 5.5)

  )

```

For comparison, the same plot with a univariate color scale. Not it appears that in every state we know who is in the lead.

```{r message = FALSE}

ggplot(US_polling) + 

  geom_sf(aes(fill = Clinton_lead), color = "gray30", size = 0.2) + 

  coord_sf(datum = NA) +

  scale_fill_gradient2(

    low = "#AC202F", mid = "#740280", high = "#2265A3",

    name = c("Clinton lead", "uncertainty"),

    limits = c(-40, 40),

    breaks = c(-40, -20, 0, 20, 40),

    guide = guide_colorbar(

      direction = "horizontal",

      label.position = "bottom",

      title.position = "top",

      barwidth = grid::unit(4.0, "cm")

    )

  ) +

  theme_void() +

  theme(

    legend.title.align = 0.5,

    legend.key.size = grid::unit(0.8, "cm"),

    plot.margin = margin(5.5, 20, 5.5, 5.5)

  )

```