I am doing an exploratory data analysis for data that is collected at the daily level over many years. The relevant time period is about 18 – 20 months from the same date each year. What I would like to do is visually inspect these 18 month periods one on top of the other. I can do this as below by adding data for each geom_point() call. I would like to avoid calling that one time for each period
min ex:
library(tidyverse)
minex <- data.frame(dts = seq((mdy('01/01/2010')), mdy('11/10/2013'), by = 'days'))
minex$day <- as.numeric(minex$dts - min(minex$dts))
minex$MMDD <- paste0(month(minex$dts), "-", day(minex$dts))
minex$v1 <- 20 + minex$day^0.4 -cos(2*pi*minex$day/365) + rnorm(nrow(minex), 0, 0.3)
ggplot(filter(minex, dts %in% seq((mdy('11/10/2013') - (365 + 180)), mdy('11/10/2013'), by =
'days')), aes(day, v1)) +
geom_point() +
geom_point(data = filter(minex, dts %in% seq((mdy('11/10/2012') - (365 + 180)),
mdy('11/10/2012'), by = 'days')), aes(day+365, v1), color = 'red')
>Solution :
Since you have overlapping spans of time, I think we can lapply over your end dates, mutate the data a little, then use normal ggplot2 aesthetics to color them.
spans <- bind_rows(lapply(mdy("11/10/2010", "11/10/2011", "11/10/2012", "11/10/2013"), function(end) {
filter(minex, between(dts, end - (365 + 180), end)) %>%
mutate(day = day - min(day), end = end)
}))
ggplot(spans, aes(day, v1)) +
geom_point(aes(color = factor(end)))
You can see the range of each with a quick summary:
spans %>%
group_by(end) %>%
summarize(startdate = min(dts), enddate = max(dts))
# # A tibble: 4 x 3
# end startdate enddate
# <date> <date> <date>
# 1 2010-11-10 2010-01-01 2010-11-10
# 2 2011-11-10 2010-05-14 2011-11-10
# 3 2012-11-10 2011-05-15 2012-11-10
# 4 2013-11-10 2012-05-14 2013-11-10