Plotting by ggplot in R

Question

I have a time series data for different group components. Each group ID with its various time stamps (given as Date) has an hypo and hyper response data. I would like to plot the time series for each of this group by facet (ggplot) for both (1) Group ID and also by response i.e. (2) Hyper and Hypo response so that the picture by response is one top of another. Any help is appreciated.

A demo data set and what I have done so far is given below.

set.seed(1)
tdat <- data.frame(Group = rep(paste0("GroupID-", c("A","B")),
                              each = 100),
                   Date = rep(seq(Sys.Date(), by = "1 day", length = 100), 2),
                   Fitted = c(cumsum(rnorm(100)), cumsum(rnorm(100))),
                   Signif = rep(NA, 200))
tdat <- transform(tdat, Hyper = Fitted + 1.5, Hypo = Fitted - 1.5)
## select 1 region per Site as signif
take <- sample(10:70, 2)
take[2] <- take[2] + 100
tdat$Signif[take[1]:(take[1]+25)] <- tdat$Fitted[take[1]:(take[1]+25)]
tdat$Signif[take[2]:(take[2]+25)] <- tdat$Fitted[take[2]:(take[2]+25)]

And the data frame looks like this -

    > head(tdat)
      Group       Date     Fitted Signif     Hyper       Hypo
1 GroupID-A 2017-04-18 -0.6264538     NA 0.8735462 -2.1264538
2 GroupID-A 2017-04-19 -0.4428105     NA 1.0571895 -1.9428105
3 GroupID-A 2017-04-20 -1.2784391     NA 0.2215609 -2.7784391
4 GroupID-A 2017-04-21  0.3168417     NA 1.8168417 -1.1831583
5 GroupID-A 2017-04-22  0.6463495     NA 2.1463495 -0.8536505
6 GroupID-A 2017-04-23 -0.1741189     NA 1.3258811 -1.6741189

The time series is given by Date.

The data I have plotted is given below. However my real data has more group ID's and I really want one picture for each group ID with splitting the image for Hyper and Hypo response.

library(ggplot2)
ggplot(tdat, aes(x = Date, y = Fitted, group = Group)) +
    geom_line() +
    geom_line(mapping = aes(y = Hyper), lty = "dashed") +
    geom_line(mapping = aes(y = Hypo), lty = "dashed") +
    geom_line(mapping = aes(y = Signif), lwd = 1.3, colour = "red") +
    facet_wrap( ~ Group)

Again any help is appreciated.

Thanks

So the plot in your example is not your expected output? Did you tried facet_grid() instead? — Roman
– Roman, Commented Apr 18, 2017 at 11:10

Erdem Akkas · Accepted Answer · 2017-04-18 11:17:06Z

7

If you will reshape your data with reshape2 or tidyr or data.table and convert wide to long:

library(reshape2)
tdat2<-melt(tdat,id.vars = c("Group","Date","Signif","Fitted"))

ggplot(tdat2, aes(x = Date, y = value, group = Group)) +
geom_line() +
geom_line(mapping = aes(y = Signif), lwd = 1.3, colour = "red") +
facet_wrap( variable~ Group)

answered Apr 18, 2017 at 11:17

Erdem Akkas

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3 Comments

Roman Over a year ago

Instead of using facet_wrap I would use facet_grid(variable ~ Group). IMO it is more elegant and caleaner.

Erdem Akkas Over a year ago

I did not want to change anything but just give what OP want. OP used facet_wrap( ~ Group). Agree that facet_grid might be cleaner and theme can be improved.

Roman Over a year ago

This was no criticism. Just an additional comment.

neilfws · Accepted Answer · 2017-04-18 11:13:37Z

4

How about something like this, using geom_ribbon to show the Hyper and Hypo values:

tdat %>% 
ggplot(aes(Date, Fitted)) + 
  geom_line(lty = "dashed") + 
  geom_line(aes(y = Signif), lwd = 1.3, color = "red") +
  geom_ribbon(aes(ymin = Hypo, ymax = Hyper, group = Group), alpha = 0.2) + 
  facet_grid(Group ~ .) + 
  theme_light()

Result:

answered Apr 18, 2017 at 11:13

neilfws

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1 Comment

neilfws Over a year ago

Yes, it does better answer your question as written. As to which is the better visualization, well you be the judge :)

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