I am trying to use the group= option in geom_boxplot and it works for one grouping function, but not for the another. First plot runs, 2nd and 3rd plots (really same, called differently) both fail to produce 2-month boxplots for pre 2017 and one-month boxplots for 2017, as the grouper intends. For grouper function ggplot declares Warning message: position_dodge requires non-overlapping x intervals " but X value is same across graphs. Clearly related to my groupdates function, but groups appear to be constructed properly. Suggestions welcome. With thanks.
library(tidyverse)
library(lubridate)
# I want two month groups before 2017, and one-month groups in 2017
groupdates <- function(date) {
month_candidate <-case_when(
year(date) < 2017 ~ paste0(year(date), "-", (floor(((0:11)/12)*6)*2)+1),
TRUE ~ paste0(year(date), "_", month(date))
)
month_candidate2 <-case_when(
(str_length(month_candidate)==6) ~ paste0(str_sub(month_candidate,1,5), "0", str_sub(month_candidate,6)),
TRUE ~ month_candidate
)
return(month_candidate2)
}
generate_fake_date_time <- function(N, st="2015/01/02", et="2017/02/28") {
st <- as.POSIXct(as.Date(st))
et <- as.POSIXct(as.Date(et))
dt <- as.numeric(difftime(et,st,unit="sec"))
ev <- sort(runif(N, 0, dt))
rt <- st + ev
}
n=5000
set.seed(250)
test <-as.data.frame(generate_fake_date_time(n))
colnames(test) <- "posixctdate"
test$ranvalue <- month(test$posixctdate)+runif(length(test), 0,1)
test$grouped_time <-groupdates(test$posixctdate)
table(test$grouped_time)
ggplot(test)+geom_boxplot(aes(x=posixctdate, y=ranvalue, group=paste0(year(posixctdate), "_", month(posixctdate))))
#ggplot(test)+geom_violin(aes(x=posixctdate, y=ranvalue, group=junk))
ggplot(test)+geom_boxplot(aes(x=posixctdate, y=ranvalue, group=grouped_time))
ggplot(test)+geom_boxplot(aes(x=posixctdate, y=ranvalue, group=groupdates(posixctdate)))
sessionInfo()
If I correctly understood your problem, you should think about modifying your groupdates
function.
I only modified the 3rd line using :
ceiling
instead of floor
month(date)
instead of 0:11
Resulting in :
groupdates <- function(date) {
month_candidate <-case_when(
year(date) < 2017 ~ paste0(year(date), "-", (ceiling(((month(date))/12)*6)*2)+1),
TRUE ~ paste0(year(date), "_", month(date))
)
month_candidate2 <-case_when(
(str_length(month_candidate)==6) ~ paste0(str_sub(month_candidate,1,5), "0", str_sub(month_candidate,6)),
TRUE ~ month_candidate
)
return(month_candidate2)
}
I also modified the computation of ranvalue
to have a better distribution, I bet you wanted to use nrow
instead of length
:
test$ranvalue <- month(test$posixctdate) + runif(nrow(test), 0, 1)
test$grouped_time <-groupdates(test$posixctdate)
table(test$grouped_time)
And the output (no changes) :
ggplot(test)+geom_boxplot(aes(x=posixctdate, y=ranvalue, group=grouped_time))
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