library(groupedHyperframe)15 groupedData
The examples in Chapter 15 require that the
searchpath contains the followingnamespaces,
Function nlme::groupedData() (Pinheiro, Bates, and R Core Team 2025, v3.1.168) creates a grouped data frame, i.e., an R object of S3 class 'groupedData'. Package groupedHyperframe implements the following S3 method dispatches to the class 'groupedData' (Listing 15.1, Table 15.1),
S3 method dispatches groupedHyperframe::*.groupedData
Code
methods2kable(class = 'groupedData', package = 'groupedHyperframe', all.names = TRUE)S3 method dispatches groupedHyperframe::*.groupedData (v0.3.0.20251020)
| visible | from | generic | isS4 | |
|---|---|---|---|---|
as.groupedHyperframe.groupedData |
TRUE | groupedHyperframe | groupedHyperframe::as.groupedHyperframe |
FALSE |
15.1 Create groupedHyperframe
The S3 generic function as.groupedHyperframe() are introduced in Section 12.1. The S3 method dispatch as.groupedHyperframe.groupedData() converts a groupedData into a groupedHyperframe (Chapter 16) using its grouping structure.
Listing 15.2 converts the grouped data frame Remifentanil from package nlme (Pinheiro, Bates, and R Core Team 2025, v3.1.168) into a groupedHyperframe.
Data: Remifentanil
nlme::Remifentanil |>
head(n = 3L)
# Grouped Data: conc ~ Time | Subject
# ID Subject Time conc Rate Amt Age Sex Ht Wt BSA LBM
# 1 1 1 0.0 NA 71.99 107.9850 30.58 Male 171 72 1.8393 56.5075
# 2 1 1 1.5 9.51 71.99 35.9950 30.58 Male 171 72 1.8393 56.5075
# 3 1 1 2.0 11.50 71.99 37.4348 30.58 Male 171 72 1.8393 56.5075as.groupedHyperframe.groupedData() on Remifentanil
Remifentanil_g = nlme::Remifentanil |>
as.groupedHyperframe()Example: a grouped hyper data frame Remifentanil_g
Remifentanil_g
# Grouped Hyperframe: ~Subject
# <environment: 0x31352eab8>
#
# 65 Subject
#
# Preview of first 10 (or less) rows:
#
# Time conc Rate Amt ID Subject Age Sex Ht Wt BSA LBM
# 1 (numeric) (numeric) (numeric) (numeric) 30 30 21 Female 165 55.9 1.6095 42.8260
# 2 (numeric) (numeric) (numeric) (numeric) 21 21 24 Female 161 58.6 1.6131 43.0953
# 3 (numeric) (numeric) (numeric) (numeric) 25 25 32 Female 157 45.9 1.4278 36.4631
# 4 (numeric) (numeric) (numeric) (numeric) 23 23 23 Female 163 50.0 1.5215 39.5740
# 5 (numeric) (numeric) (numeric) (numeric) 29 29 25 Female 163 54.5 1.5782 41.7695
# 6 (numeric) (numeric) (numeric) (numeric) 28 28 30 Female 178 79.1 1.9708 55.4106
# 7 (numeric) (numeric) (numeric) (numeric) 32 32 54 Female 167 45.0 1.4806 37.4038
# 8 (numeric) (numeric) (numeric) (numeric) 64 64 55 Female 168 74.8 1.8455 50.6969
# 9 (numeric) (numeric) (numeric) (numeric) 22 22 33 Female 163 70.5 1.7607 47.7487
# 10 (numeric) (numeric) (numeric) (numeric) 45 45 72 Female 165 54.4 1.5910 42.1204Listing 15.3 converts the grouped data frame bdf from package nlme (Pinheiro, Bates, and R Core Team 2025, v3.1.168) into a groupedHyperframe.
Data: bdf
nlme::bdf |>
head(n = 3L)
# Grouped Data: langPOST ~ IQ.verb | schoolNR
# <environment: 0x1275389d0>
# schoolNR pupilNR IQ.verb IQ.perf sex Minority repeatgr aritPRET classNR aritPOST langPRET langPOST ses denomina
# 1 1 17001 15.0 12.33333 0 N 0 14 180 24 36 46 23 1
# 2 1 17002 14.5 10.00000 0 Y 0 12 180 19 36 45 10 1
# 3 1 17003 9.5 11.00000 0 N 0 10 180 24 33 33 15 1
# schoolSES satiprin natitest meetings currmeet mixedgra percmino aritdiff homework classsiz groupsiz IQ.ver.cen
# 1 11 3.42857 0 1.7 1.83333 0 60 12 2.33333 29 29 3.165938
# 2 11 3.42857 0 1.7 1.83333 0 60 12 2.33333 29 29 2.665938
# 3 11 3.42857 0 1.7 1.83333 0 60 12 2.33333 29 29 -2.334062
# avg.IQ.ver.cen grpSiz.cen
# 1 -1.514062 5.899432
# 2 -1.514062 5.899432
# 3 -1.514062 5.899432as.groupedHyperframe.groupedData() on bdf
bdf_g = nlme::bdf |>
as.groupedHyperframe()Example: a grouped hyper data frame bdf_g
bdf_g
# Grouped Hyperframe: ~schoolNR
# <environment: 0x125827318>
#
# 131 schoolNR
#
# Preview of first 10 (or less) rows:
#
# pupilNR IQ.verb IQ.perf sex Minority repeatgr aritPRET classNR aritPOST langPRET langPOST ses
# 1 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 2 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 3 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 4 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 5 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 6 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 7 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 8 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 9 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# 10 (factor) (numeric) (numeric) (factor) (factor) (ordered) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric)
# mixedgra percmino homework classsiz groupsiz IQ.ver.cen grpSiz.cen schoolNR denomina schoolSES satiprin natitest
# 1 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 47 3 11 2.85714 0
# 2 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 103 3 12 3.00000 1
# 3 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 2 1 11 3.00000 0
# 4 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 123 2 20 3.14286 1
# 5 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 10 1 15 3.00000 0
# 6 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 258 3 14 2.71429 0
# 7 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 27 1 17 3.28571 0
# 8 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 12 1 20 3.14286 0
# 9 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 109 1 15 3.28571 0
# 10 (factor) (numeric) (numeric) (numeric) (numeric) (numeric) (numeric) 192 3 19 3.57143 1
# meetings currmeet aritdiff avg.IQ.ver.cen
# 1 2.11111 1.83333 13 -3.5215621
# 2 2.10000 2.16667 17 -5.0840621
# 3 1.60000 1.66667 27 -2.8340621
# 4 2.10000 2.00000 27 -2.0840621
# 5 2.60000 2.66667 27 -1.3340621
# 6 2.00000 2.00000 13 -1.1912049
# 7 1.10000 1.00000 9 -0.4054907
# 8 2.70000 2.66667 17 -2.4007288
# 9 1.60000 1.33333 17 -1.0090621
# 10 3.20000 3.16667 16 -1.0840621Converting a groupedData (or data.frame) with substantial amount of duplicated information into a groupedHyperframe not necessarily(!!) reduces the memory allocation, because the hyperframe object carries additional auxiliary information. And even when it does reduce the memory allocation, a groupedHyperframe would not reduce much the saved file.size compared to a data.frame, if xz compression is used for both.
Advanced: Reducing memory allocation
unclass(object.size(Remifentanil_g) / object.size(nlme::Remifentanil))
# [1] 0.3094831
f = replicate(n = 2L, expr = tempfile(fileext = '.rds'))
Remifentanil_g |> saveRDS(file = f[1L], compress = 'xz')
nlme::Remifentanil |> saveRDS(file = f[2L], compress = 'xz')
file.size(f[1L]) / file.size(f[2L])
# [1] 1.221687Advanced: Not reducing memory allocation
unclass(object.size(bdf_g) / object.size(nlme::bdf))
# [1] 25.78725