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Published
20 hours ago •
ATFutures
ATFutures
Basic visualisation
E.g. using an approach like calendarPlot() from the openair pkg that produces plots like this:
There are +s and -s of using ggplot2 to consider. Not sure if there are good ways of doing it in base R package graphics. One for the backburner in any case.
Also food for thought (source):
# install.packages("vistime")
library(vistime)
library(tidyverse)
library(lubridate)
# ?vistime
# d = read_csv("potential-projects/ofo/gantt.csv")
d = read.csv(stringsAsFactors = FALSE,text = "event,start,duration,group
compile datasets,0,2,descriptive analysis
baseline data,1,2,descriptive analysis
time of day,1,2,descriptive analysis
demographics,1,2,descriptive analysis
areas,1,1,visualisation
routes,1.5,1,visualisation
route networks,2,2,visualisation
comparison with census data,3,2,data analysis
comparison with university data,3,2,data analysis
comparison with PCT data,4,2,data analysis
demand,4,1.5,policy analysis
cycle network gaps,5,3,policy analysis
projecting growth,6,3,policy analysis
return zones,7,3,policy analysis
BikeHub-Ofo interaction,7,2,policy analysis
write-up and comparison with other projects,4,6,write-up")
start_date = as_date(lubridate::ymd("2018-05-01", tz = "GMT"))
d$start = start_date + d$start * 7
d$end = d$start + d$duration * 7
vistime(d, linewidth = 20)
Reasonable. Or even a separate package like icalviz to keep things modular.