1 Load packages
library(tidyverse) # data wrangling
library(vistime) # time line2 Motivation
For project planing, a visualization of some time line is often useful. If it’s not the dates but rather the steps of a process, a graph of steps is more appropriate. However, if the sequence of steps is simple and rather linear, and the dates are the important piece of information to be transmitted, a kind of timeline graph is warranted.
Here’s one go: We’re going to make use of Sandra Raabe’s nice R package vistime.
3 Sample data
timeline_data <- data.frame(
event = c("Anmeldung", "Vergabe", "Schreiben", "Thesismodul", "Beginn Semester 1", "Ende Semester 1", "Beginn Semester 2", "Ende Semester 2"),
start = c("2023-03-15", "2023-05-22", "2023-10-04", "2023-10-04", "2023-03-15", "2023-06-30", "2023-10-04", "2024-01-14"),
end = c("2023-05-21", "2023-06-30", "2024-01-14", "2024-01-14", "2023-03-15", "2023-06-30", "2023-10-04", "2024-01-14"),
group = c("Semester 1", "Semester 1", "Semester 2", "Semester 2", "Semester 1", "Semester 1", "Semester 2", "Semester 2")
)4 Visualization
gg_vistime(timeline_data, optimize_y = TRUE) +
labs(title = "Thesis schreiben im Studiengang AWM",
subtitle = "ENTWURF") 
5 Debrief
6 Reproducibility
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