[R] aggregate formula - differing results

Rui Barradas
Mon, 04 Sep 2023 11:46:00 -0000

?s 10:44 de 04/09/2023, Ivan Calandra escreveu:
> Dear useRs,
>
> I have just stumbled across a behavior in aggregate() that I cannot
> explain. Any help would be appreciated!
>
> Sample data:
> my_data <- structure(list(ID = c("FLINT-1",
"FLINT-10", "FLINT-100",
> "FLINT-101", "FLINT-102", "HORN-10",
"HORN-100", "HORN-102", "HORN-103",
> "HORN-104"), EdgeLength = c(130.75, 168.77, 142.79, 130.1,
140.41,
> 121.37, 70.52, 122.3, 71.01, 104.5), SurfaceArea = c(1736.87, 1571.83,
> 1656.46, 1247.18, 1177.47, 1169.26, 444.61, 1791.48, 461.15, 1127.2),
> Length = c(44.384, 29.831, 43.869, 48.011, 54.109, 41.742, 23.854,
> 32.075, 21.337, 35.459), Width = c(45.982, 67.303, 52.679, 26.42,
> 25.149, 33.427, 20.683, 62.783, 26.417, 35.297), PLATWIDTH = c(38.84,
> NA, 15.33, 30.37, 11.44, 14.88, 13.86, NA, NA, 26.71), PLATTHICK =
> c(8.67, NA, 7.99, 11.69, 3.3, 16.52, 4.58, NA, NA, 9.35), EPA = c(78,
> NA, 78, 54, 72, 49, 56, NA, NA, 56), THICKNESS = c(10.97, NA, 9.36, 6.4,
> 5.89, 11.05, 4.9, NA, NA, 10.08), WEIGHT = c(34.3, NA, 25.5, 18.6, 14.9,
> 29.5, 4.5, NA, NA, 23), RAWMAT = c("FLINT", "FLINT",
"FLINT", "FLINT",
> "FLINT", "HORNFELS", "HORNFELS",
"HORNFELS", "HORNFELS", "HORNFELS")),
> row.names = c(1L, 2L, 3L, 4L, 5L, 111L, 112L, 113L, 114L, 115L), class =
> "data.frame")
>
> 1) Simple aggregation with 2 variables:
> aggregate(cbind(Length, Width) ~ RAWMAT, data = my_data, FUN = mean,
> na.rm = TRUE)
>
> 2) Using the dot notation - different results:
> aggregate(. ~ RAWMAT, data = my_data[-1], FUN = mean, na.rm = TRUE)
>
> 3) Using dplyr, I get the same results as #1:
> group_by(my_data, RAWMAT) %>%
>  ? summarise(across(c("Length", "Width"), ~ mean(.x,
na.rm = TRUE)))
>
> 4) It gets weirder: using all columns in #1 give the same results as in
> #2 but different from #1 and #3
> aggregate(cbind(EdgeLength, SurfaceArea, Length, Width, PLATWIDTH,
> PLATTHICK, EPA, THICKNESS, WEIGHT) ~ RAWMAT, data = my_data, FUN = mean,
> na.rm = TRUE)
>
> So it seems it is not only due to the notation (cbind() vs. dot). Is it
> a bug? A peculiar thing in my dataset? I tend to think this could be due
> to some variables (or their names) as all notations seem to agree when I
> remove some variables (although I haven't found out which variable(s)
is
> (are) at fault), e.g.:
>
> my_data2 <- structure(list(ID = c("FLINT-1",
"FLINT-10", "FLINT-100",
> "FLINT-101", "FLINT-102", "HORN-10",
"HORN-100", "HORN-102", "HORN-103",
> "HORN-104"), EdgeLength = c(130.75, 168.77, 142.79, 130.1,
140.41,
> 121.37, 70.52, 122.3, 71.01, 104.5), SurfaceArea = c(1736.87, 1571.83,
> 1656.46, 1247.18, 1177.47, 1169.26, 444.61, 1791.48, 461.15, 1127.2),
> Length = c(44.384, 29.831, 43.869, 48.011, 54.109, 41.742, 23.854,
> 32.075, 21.337, 35.459), Width = c(45.982, 67.303, 52.679, 26.42,
> 25.149, 33.427, 20.683, 62.783, 26.417, 35.297), RAWMAT =
c("FLINT",
> "FLINT", "FLINT", "FLINT", "FLINT",
"HORNFELS", "HORNFELS", "HORNFELS",
> "HORNFELS", "HORNFELS")), row.names = c(1L, 2L, 3L, 4L,
5L, 111L, 112L,
> 113L, 114L, 115L), class = "data.frame")
>
> aggregate(cbind(EdgeLength, SurfaceArea, Length, Width) ~ RAWMAT, data =
> my_data2, FUN = mean, na.rm = TRUE)
>
> aggregate(. ~ RAWMAT, data = my_data2[-1], FUN = mean, na.rm = TRUE)
>
> group_by(my_data2, RAWMAT) %>%
>  ? summarise(across(where(is.numeric), ~ mean(.x, na.rm = TRUE)))
>
>
> Thank you in advance for any hint.
> Best wishes,
> Ivan
>
>
>
>
>  ????*LEIBNIZ-ZENTRUM*
> *F?R ARCH?OLOGIE*
>
> *Dr. Ivan CALANDRA*
> **Head of IMPALA (IMaging Platform At LeizA)
>
> *MONREPOS* Archaeological Research Centre, Schloss Monrepos
> 56567 Neuwied, Germany
>
> T: +49 2631 9772 243
> T: +49 6131 8885 543
> ivan.calandra at leiza.de
>
> leiza.de <http://www.leiza.de/>
> <http://www.leiza.de/>
> ORCID <https://orcid.org/0000-0003-3816-6359>
> ResearchGate
> <https://www.researchgate.net/profile/Ivan_Calandra>
>
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Hello,

You can define a vector of the columns of interest and subset the data
with it. Then the default na.action = na.omit will no longer remove the
rows with NA vals in at least one column and the results are the same.

However, this will not give the mean values of the other numeric
columns, just of those two.



# define a vector of columns of interest
cols <- c("Length", "Width", "RAWMAT")

# 1) Simple aggregation with 2 variables, select cols:
aggregate(cbind(Length, Width) ~ RAWMAT, data = my_data[cols], FUN =
mean, na.rm = TRUE)

# 2) Using the dot notation - if cols are selected, equal results:
aggregate(. ~ RAWMAT, data = my_data[cols], FUN = mean, na.rm = TRUE)

# 3) Using dplyr, the results are now the same results as #1 and #2:
my_data %>%
   select(all_of(cols)) %>%
   group_by(RAWMAT) %>%
   summarise(across(c("Length", "Width"), ~ mean(.x, na.rm =
TRUE)))


Hope this helps,

Rui Barradas