Recently, ggplot2 2.2.0 was released. Among other news, stacking bar plot was improved. Here is a short demonstration.
Load libraries
library(tidyverse)
library(htmlTable)
… and load data:
data <- read.csv("https://osf.io/meyhp/?action=download")
DOI for this piece of data is 10.17605/OSF.IO/4KGZH.
The data consists of results of a survey on extraversion and associated behavior.
Say, we would like to visualize the responsed to the extraversion items (there are 10 of them).
So, let’s see. First, compute summary of the responses.
data %>%
select(i01:i10) %>%
gather %>%
dplyr::count(key, value) %>%
ungroup -> data2
htmlTable(head(data2))
| key | value | n | |
|---|---|---|---|
| 1 | i01 | 1 | 7 |
| 2 | i01 | 2 | 39 |
| 3 | i01 | 3 | 230 |
| 4 | i01 | 4 | 223 |
| 5 | i01 | 2 | |
| 6 | i02 | 1 | 176 |
Ok, so now let’s plot.
ggplot(data2) +
geom_col(aes(x = key, fill = value, y = n))
Note that geom_col is short-hand vor geom_bar(stat = "identity").
Of interest, “negative” stacking is now possible.
data %>%
select(i01:i10) %>%
gather %>%
na.omit %>%
count(key, value) %>%
ungroup %>%
group_by(key) %>%
mutate(rel_n = round(n - mean(n), 2)) %>%
ungroup -> data3
htmlTable(head(data3))
| key | value | n | rel_n | |
|---|---|---|---|---|
| 1 | i01 | 1 | 7 | -117.75 |
| 2 | i01 | 2 | 39 | -85.75 |
| 3 | i01 | 3 | 230 | 105.25 |
| 4 | i01 | 4 | 223 | 98.25 |
| 5 | i02 | 1 | 176 | 51.5 |
| 6 | i02 | 2 | 224 | 99.5 |
ggplot(data3) +
geom_col(aes(x = key, fill = value, y = rel_n))
Hm, at it comes to the color, we need to change to discrete colors. It appears that the color scheme is not able (out of the box) to adapt to this “negative stacking”.
So:
ggplot(data3) +
geom_col(aes(x = key, fill = factor(value), y = rel_n))
sessionInfo()
## R version 3.3.2 (2016-10-31)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: macOS Sierra 10.12.1
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] purrr_0.2.2.9000 readr_1.0.0 tibble_1.2 tidyverse_1.0.0
## [5] knitr_1.15 htmlTable_1.7 ggplot2_2.2.0 tidyr_0.6.0
## [9] dplyr_0.5.0
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.7 magrittr_1.5 munsell_0.4.3
## [4] colorspace_1.3-0 R6_2.2.0 highr_0.6
## [7] stringr_1.1.0 plyr_1.8.4 tools_3.3.2
## [10] grid_3.3.2 gtable_0.2.0 DBI_0.5-1
## [13] htmltools_0.3.5 yaml_2.1.13 lazyeval_0.2.0.9000
## [16] assertthat_0.1 digest_0.6.10 rprojroot_1.1
## [19] rsconnect_0.5 evaluate_0.10 rmarkdown_1.1.9016
## [22] labeling_0.3 stringi_1.1.2 scales_0.4.1
## [25] backports_1.0.4