How to plot multiple ACF values on the one graph - r

Question

I've just started using R and would like to use look at the autocorrelation in my data using ACF. My dataframe (GL) looks something like this
GL
well year month value area
684 1994 Jan 8.53 H
684 1994 Feb 8.62 H
684 1994 Mar 8.12 H
684 1994 Apr 8.21 H
684 1995 Jan 8.53 H
684 1995 Feb 8.62 H
684 1995 Mar 8.12 H
684 1995 Apr 8.21 H
684 1996 Jan 8.53 H
684 1996 Feb 8.62 H
684 1996 Mar 8.12 H
684 1996 Apr 8.21 H
101 1994 Jan 8.53 R
101 1994 Feb 8.62 R
101 1994 Mar 8.12 R
101 1994 Apr 8.21 R
101 1995 Jan 8.53 R
101 1995 Feb 8.62 R
101 1995 Mar 8.12 R
101 1995 Apr 8.21 R
101 1996 Jan 8.53 R
101 1996 Feb 8.62 R
101 1996 Mar 8.12 R
101 1996 Apr 8.21 R
I would like to:
1. Calculate ACF for each well using lappy or some kind of loop (my actual data set has about 100 wells and three groups)
2. Plot the ACF values (as lines) for each well on one graph for each group (so in this case I would have two acf graphs H & R.
I can use split and lapply to calculate ACF for each well e.g.
split <- split(GL$value,GL$well)
test <- lapply(split,acf)
But splitting this way doesn't save the area information. If I split like this:
split1 <- split(GL,GL$well)
Then I don't know how to perform lapply on the values for each well.

Answer 1

As you split the data by well,
spl1 <- split(GL, GL$well)
the lapply would look like this.
lapply(spl1, function(x) acf(x$value))
We could make this somewhat nicer, though.
When we do the lapply by list number we get a "counter" with which we can access the list names to paste together informative titles. With par(mfrow=c(<rows>, <columns>)) we can set the arrangement of the plots.
par(mfrow=c(1, 2))
lapply(seq_along(spl1), function(x) acf(spl1[[x]]$value,
main=paste0("well ", names(spl1)[x], ", ",
"area ", unique(spl1[[x]]$area))))
Result
This will probably have to be adapted according to how your wells are divided into groups.
(As a sidenote: Better avoid overwriting function names. You use split() and give the result the same name as the function which could induce confusion, both of yourself and of R. Other popular candidates are data, df, table. We can always quickly check with ? whether the name is "free", e.g. ?df.)
Data
# result of `dput(GL)`
GL <- structure(list(well = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = c("101", "684"), class = "factor"), year = structure(c(1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 3L, 3L, 3L, 3L), .Label = c("1994", "1995", "1996"
), class = "factor"), month = structure(c(3L, 2L, 4L, 1L, 3L,
2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L,
2L, 4L, 1L), .Label = c("Apr", "Feb", "Jan", "Mar"), class = "factor"),
value = structure(c(3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L,
1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L), .Label = c("8.12",
"8.21", "8.53", "8.62"), class = "factor"), area = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("H", "R"), class = "factor")), row.names = c(NA,
-24L), class = "data.frame")

Answer 2

You can solve it with data.table:
Let's start with the data (slightly modified from yours, so there will be different values for each well):
structure(list(well = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L), .Label = c("101", "684"), class = "factor"), year = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L), .Label = c("1994", "1995", "1996"), class = "factor"), month = structure(c(3L, 2L, 4L, 1L, 3L,
2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L, 3L, 2L, 4L, 1L), .Label = c("Apr", "Feb", "Jan", "Mar"), class = "factor"),
value = c(4.65144120692275, 8.98342372477055, 17.983893298544,
15.3687085728161, 8.9577708535362, 7.47583840973675, 16.6564453896135, 11.6158618542831, 23.6109819535632, 14.1604918171652, 11.3882310683839, 20.4579487598967, 3.31275907787494, 22.109053656226, 13.598402187461, 12.3686389743816, 17.9585587936454, 17.3689122993965, 7.38424337399192, 6.93579732463695, 13.2789171519689, 21.2500206897967, 13.5766511948314, 3.58588649751619), area = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("H", "R"), class = "factor")), row.names = c(NA, -24L), class = c("data.table", "data.frame"))
Then we create a list for each well:
GL[, datos := .(list(value)) , by = well]
Each row in the datos variable will have a list with all the values corresponding to the well, so we can drop most of them and keep only the first row of each well, as it has all the information already. That is done with GL[, .SD[1,], by = well] so the result will be a two-row data table. After that, we can chain another expression that will produce and save each plot:
GL[, .SD[1,], by = well][
, {png(filename = paste0(well, "-", area, ".png"),
width = 1600,
height = 1600,
units = "px",
res = 100);
plot(a[[1]], main = paste("Well:", well,
"Area:", area, sep = " "));
dev.off()},
by = well]
Your two plots will be saved in the current directory with names like "684-H.png" and "101-R.png".
Key point here: data.table takes expressions and not just functions, so it's absolutely possible to produce the plots and save them to any given location.