Transition plot in R-change in time visualization
Transition Plot in R, when we have quantitative data for change in time, visualization is straight forward but in the case of a categorical variable, it’s not as easy.
In this article, we are going to describe transition plots for categorical variables.
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Approach 1:-
You can use plotmat function from the diagram package.
If you are not installed, let’s install the package.
install.packages("diagram")
library(diagram)
plotmat(transition_matrix[1:3,1:3])
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Approach 2:-
Let’s load the package transition plot function from Gmisc package.
library(Gmisc) library(grid)
Let’s create a matrix for visualization,
no_boxes <- 3 transition_matrix <- matrix(NA, nrow = no_boxes, ncol = no_boxes) transition_matrix[1, ] <- 200 * c(.5, .25, .25) transition_matrix[2, ] <- 540 * c(.75, .10, .15) transition_matrix[3, ] <- 340 * c(0, .2, .80) transition_matrix
[,1] [,2] [,3] [1,] 100 50 50 [2,] 405 54 81 [3,] 0 68 272
Let’s load the transition plot function and fill the box names
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Transition plot in R
transitionPlot(transition_matrix,
box_txt = c("First", "Second", "Third"),
type_of_arrow = "simple",
min_lwd = unit(1, "mm"),
max_lwd = unit(6, "mm"),
overlap_add_width = unit(1, "mm"))
Based on a transition plot function, visualizing time change is quick and provide more intuitive understanding. The lines indicates the transition from one particular group/level into the next.
library(RColorBrewer)
output_perc <-
function(txt, n) sprintf("%s\n[%.0f%%]", txt, n)
box_txt <-
cbind(mapply(output_perc,
txt = c("First", "Second", "Third"),
n = prop.table(rowSums(transition_matrix))*100),
mapply(output_perc,
txt = c("First", "Second", "Third"),
n = prop.table(colSums(transition_matrix))*100))
transitionPlot(transition_matrix,
box_label = c("Before", "After"),
box_txt = box_txt,
cex = 1.2,
type_of_arrow = "simple")
You can add title while using main, box labels based on box_label, and customizing box text can using box_txt. The box_txt vector assumes the same text or label for both left and right boxes.
Conclusion
The function transition plot is from Gmisc-package and it’s very handy when we need categorical time change visualization. The original idea was for transitionPlot is to show the before and after impact.
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