licorice is an R package that eases the plotting of Likert-like
data. It has been heavily inspired by the likert
package from Bryer and
Speerschneider.
licorice makes use of the ggplot2 plotting engine in such a way that
interference by the licorice package in terms of theming is kept to a
minimum (the graphs diplayed belowed are themed using the ggthemr
package). When using the licorice function a ggplot2 object is
returned which can then be added upon to your liking.
For now, no CRAN version exists and you'll have to install from GitHub
using devtools.
devtools::install_github("Bart6114/licorice")
The licorice function expects a given structure of data. The example
pisatest dataset can be used as a reference.
A minimal requirement is the presence of the question, response and
count column. Additionally a group column can be added.
library(licorice)
## Warning: replacing previous import by 'tidyr::%>%' when loading 'licorice'
head(pisatest)
## question response group count
## 1 ST24Q01 Agree Canada 5623
## 2 ST24Q01 Agree Mexico 12622
## 3 ST24Q01 Agree United States 1755
## 4 ST24Q01 Disagree Canada 7938
## 5 ST24Q01 Disagree Mexico 13872
## 6 ST24Q01 Disagree United States 1705
For example the gapsample dataset is not structured as it should be.
Some simple preparations make it suited for licorice.
head(gapsample)
## StudentId question response
## 1 1 Financial Aid Agree
## 2 2 Financial Aid Strongly disagree
## 3 3 Financial Aid Agree somewhat
## 4 4 Financial Aid Strongly agree
## 5 5 Financial Aid Strongly agree
## 6 6 Financial Aid Agree
library(dplyr)
gap_fixed<-
gapsample %>%
group_by(question, response) %>%
summarise(count = n())
head(gap_fixed)
## Source: local data frame [6 x 3]
## Groups: question [1]
##
## question response count
## (fctr) (fctr) (int)
## 1 Financial Aid Strongly disagree 7
## 2 Financial Aid Disagree 3
## 3 Financial Aid Disagree somewhat 2
## 4 Financial Aid Undecided 3
## 5 Financial Aid Agree somewhat 9
## 6 Financial Aid Agree 7
Three main plots are available. First a centered plot is shown; here the
junction between two categories (which can be controlled by the
middle_pos parameter) is centered. If the factor levels of the reponse
variable are not set correctly, they can be specified using the
answer_order parameter. If a middle_pos value of e.g. 2 is given,
the results are centered at the junction between the second and third
response type.
my_order<-
c("Strongly disagree","Disagree", "Agree", "Strongly agree")
licorice(pisatest, answers_order = my_order, middle_pos = 2, type = "center", sort=T)
One can also fill the vertical space using a filled plot (also notice
the sort argument).
licorice(pisatest, answers_order = my_order, type = "fill", sort=TRUE)
We can also have a look at the count data.
licorice(pisatest, answers_order = my_order, type = "count")
You can also show plots in combination with each other using existing
functionality (the gridExtra library).
library(gridExtra)
grid.arrange(
licorice(pisatest, my_order, middle_pos = 2.5, type = "center", sort=TRUE),
licorice(pisatest, my_order, type = "count", sort=TRUE) +
theme(axis.text.y=element_blank()) +
scale_fill_discrete(""),
ncol = 2,
widths = c(3/4,1/4)
)
Groups (as the countries in the graph above) are shown automatically
when a group column is available in the data set. For example, when
using the generated gap_fixed data set (where not group column is
present), no group is shown;
levels(gap_fixed$response)
## [1] "Strongly disagree" "Disagree" "Disagree somewhat"
## [4] "Undecided" "Agree somewhat" "Agree"
## [7] "Strongly agree"
licorice(gap_fixed, middle_pos = 4, sort=TRUE) +
theme(legend.position="right")
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