Functions for conversion from long to wide format and vice versa.
long2wide.Rdlong2wide casts data from long to wide format.
w2lDensity casts density data from wide to long format.
w2lTrait casts trait data from wide to long format.
wide2long casts data from wide to long format.
l2wDensity casts density data from long to wide format.
l2wTrait casts trait data from long to wide format.
Usage
wide2long(wide, d.column = 1, w.names = NULL,
absences = FALSE)
w2lDensity(wide, d.column = 1, taxon.names = NULL,
absences = FALSE)
w2lTrait(wide, t.column = 1, trait.names = NULL,
absences = FALSE)
long2wide(row, column, value, averageOver = NULL,
taxonomy = NULL, subset)
l2wDensity(descriptor, taxon, value, averageOver = NULL,
taxonomy = NULL, subset)
l2wTrait(trait, taxon, value, averageOver = NULL,
taxonomy = NULL, subset)Arguments
- wide
data, in *WIDE* format. For density data, this is a data.frame or matrix with (descriptor x taxon) information (for density data), and The first column usually contains the descriptor name. For trait data this is a data.frame with (taxon x trait) information, and the first column generally contains the names of the taxa. It is also allowed to have the descriptors as row.names of the data.frame -this requires setting
d.column=0.- row
vector or data.frame that contains the data that will be used to label the rows in wide format. This can consist of multiple colums.
- column
vector with the data that will be used to label the columns in wide format.
- descriptor
name(s) of the descriptor, i.e. *where* the data were taken, e.g. station names. Either a vector, a list, a data.frame or matrix (and with multiple columns). It can be of type numerical, character, or a factor. When a data.frame or a list the "names" will be used in the output; when a vector, the argument name will be used in the output.
- taxon
gives the taxonomic name(s) (e.g. species). Should be of the same length as (the number of rows of)
descriptor. Can be a list (or data.frame with one column), or a vector. When a data.frame or a list the "name" of the column will be used in the output; when a vector, the argument name will be used.- value
vector or list that contains the *values* of the data, usually density. Should be of the same length as (the number of rows of)
descriptorandtaxon. For functiongetDensity,valuecan also be a multi-column data.frame or matrix.- averageOver
vector with *replicates* over which averages need to be taken. Should be of the same length as (the number of rows of)
descriptor.- subset
logical expression indicating elements to keep: missing values are taken as FALSE. If NULL, or absent, then all elements are used. Note that the subset is taken *after* the number of samples to average per descriptor is calculated, so this will also work for selecting certain taxa that may not be present in all replicates over which should be averaged.
- taxonomy
taxonomic information; first column will be matched with
taxon, regardless of its name.- d.column
position(s) or name(s) of the column(s) that holds the descriptors of the (density) data set, and that should be removed for any calculations. The default is to have the first column holding the descriptors. If
NULL, or0, then there is no separate column with names, so therow.namesof the dataset are used as descriptor names.- t.column
position(s) or name(s) of the column(s) that holds the taxon names of the (trait) data set, and that should be removed for any calculations. The default is to have the first column holding the taxa. If
NULL, or0, then there is no separate column with names, so therow.namesof the dataset are used as taxon names.- trait
(taxon x trait) data or (descriptor x trait) data, in WIDE format. Traits can be fuzzy coded. In the default setting, the first column contains the name of the taxon, and
t.column=1. It is also allowed to have the taxa asrow.namesof the data.frame - sett.column=0.- w.names, taxon.names, trait.names
names of the items constituting the columns in the wide dataset. If not given, the columnames (minus d.column) will be used. Input this as a data.frame if you want to set the names of the columns in the long format.
- absences
if
TRUEthe long format will contains 0's for absences
See also
MWTL for the data sets
mapBtrait for simple plotting functions
getDensity for functions working on density data
getSummary for estimating summaries from density data
getTraitDensity for functions combining density and traits
getDbIndex for extracting bioturbation and bioirrigation indices
extendTrait for functions working with traits
Details
About long2wide and wide2long:
There are two ways in which density data can be inputted:
descriptor, taxon, value, replicates, ... are vectors with density data in *LONG* format: (where, which, replicates (averageOver), value); all these vectors should be of equal length (or NULL).
wide has the density data in *WIDE* format, i.e. as a matrix with the descriptor (and perhaps replicates) in the first column, the taxon as the column names (excluding the first column), and the content of the data is the density.
Examples
## ====================================================
## Long to wide format
## ====================================================
##-----------------------------------------------------
## A small dataset with replicates
##-----------------------------------------------------
# 2 stations, 2 replicates for st.a, one replicate for st.b
Bdata.rep <- data.frame(
station = c("st.a","st.a","st.a","st.b","st.b","st.b"),
replicate = c( 1, 1, 2, 1, 1, 1),
species = c("sp.1","sp.2","sp.1","sp.3","sp.4","sp.5"),
density = c( 1, 2, 3, 3, 1, 3)
)
Bdata.rep
#> station replicate species density
#> 1 st.a 1 sp.1 1
#> 2 st.a 1 sp.2 2
#> 3 st.a 2 sp.1 3
#> 4 st.b 1 sp.3 3
#> 5 st.b 1 sp.4 1
#> 6 st.b 1 sp.5 3
##-----------------------------------------------------
## Go to wide format, average of replicates
##-----------------------------------------------------
with (Bdata.rep,
l2wDensity(value = density,
descriptor = station,
taxon = species,
averageOver = replicate))
#> descriptor sp.1 sp.2 sp.3 sp.4 sp.5
#> 1 st.a 2 1 0 0 0
#> 2 st.b 0 0 3 1 3
##-----------------------------------------------------
## Go to wide format, keep replicates
##-----------------------------------------------------
with (Bdata.rep,
l2wDensity(value = density,
descriptor = cbind(station, replicate),
taxon = species))
#> station replicate sp.1 sp.2 sp.3 sp.4 sp.5
#> 1 st.a 1 1 2 0 0 0
#> 2 st.b 1 0 0 3 1 3
#> 3 st.a 2 3 0 0 0 0
##-----------------------------------------------------
## Go to wide format, ADD replicates
##-----------------------------------------------------
with (Bdata.rep,
l2wDensity(value = density,
descriptor = station,
taxon = species))
#> descriptor sp.1 sp.2 sp.3 sp.4 sp.5
#> 1 st.a 4 2 0 0 0
#> 2 st.b 0 0 3 1 3
## ====================================================
## A small dataset without replicates
## ====================================================
Bdata <- data.frame(
station = c("st.a","st.a","st.b","st.b","st.b","st.c"),
species = c("sp.1","sp.2","sp.1","sp.3","sp.4","sp.5"),
density = c(1, 2, 3, 3, 1, 3)
)
##-----------------------------------------------------
## From long to wide format
##-----------------------------------------------------
Bwide <- with (Bdata,
l2wDensity (value = density,
descriptor = station,
taxon = species))
Bwide
#> descriptor sp.1 sp.2 sp.3 sp.4 sp.5
#> 1 st.a 1 2 0 0 0
#> 2 st.b 3 0 3 1 0
#> 3 st.c 0 0 0 0 3
## ====================================================
## Small dataset: taxonomy
## ====================================================
Btaxonomy <- data.frame(
species = c("sp.1","sp.2","sp.3","sp.4","sp.5","sp.6"),
genus = c( "g.1", "g.2", "g.2", "g.2", "g.3", "g.4"),
family = c( "f.1", "f.1", "f.1", "f.1", "f.2", "f.3"),
order = c( "o.1", "o.1", "o.1", "o.1", "o.2", "o.2"),
class = c( "c.1", "c.1", "c.1", "c.1", "c.1", "c.1")
)
##-----------------------------------------------------
## density on higher taxonomic level
##-----------------------------------------------------
# add genus, family... to the density data
Bdata.ext <- merge(Bdata, Btaxonomy)
head(Bdata.ext)
#> species station density genus family order class
#> 1 sp.1 st.a 1 g.1 f.1 o.1 c.1
#> 2 sp.1 st.b 3 g.1 f.1 o.1 c.1
#> 3 sp.2 st.a 2 g.2 f.1 o.1 c.1
#> 4 sp.3 st.b 3 g.2 f.1 o.1 c.1
#> 5 sp.4 st.b 1 g.2 f.1 o.1 c.1
#> 6 sp.5 st.c 3 g.3 f.2 o.2 c.1
# estimate (summed) density on genus level
Bwide.genus <- with (Bdata.ext,
l2wDensity(descriptor = station,
taxon = genus,
value = density)
)
Bwide.genus
#> descriptor g.1 g.2 g.3
#> 1 st.a 1 2 0
#> 2 st.b 3 4 0
#> 3 st.c 0 0 3
##-----------------------------------------------------
## select part of the data
##-----------------------------------------------------
# return species density for g.2 only
with (Bdata.ext,
l2wDensity(value = density,
descriptor = station,
taxon = species,
subset = genus=="g.2")
)
#> descriptor sp.2 sp.3 sp.4
#> 1 st.a 2 0 0
#> 2 st.b 0 3 1
# create summed values for g.2 only
with (Bdata.ext,
l2wDensity(value = density,
descriptor = station,
taxon = genus,
subset = genus=="g.2")
)
#> descriptor g.2
#> 1 st.a 2
#> 2 st.b 4
## ====================================================
## From wide to long format
## ====================================================
Bwide <- data.frame(station=c("Sta", "Stb", "Stc"),
sp1 =c( 1, 3, 0),
sp2 =c( 2, 0, 0),
sp3 =c( 0, 0, 3))
# this long format includes the 0 densities
wide2long (wide = Bwide, absences=TRUE)
#> station name value
#> 1 Sta sp1 1
#> 2 Stb sp1 3
#> 3 Stc sp1 0
#> 4 Sta sp2 2
#> 5 Stb sp2 0
#> 6 Stc sp2 0
#> 7 Sta sp3 0
#> 8 Stb sp3 0
#> 9 Stc sp3 3
# this labels the species column appropriately
wide2long (wide = Bwide, w.name=data.frame(species=colnames(Bwide)[-1]))
#> station species value
#> 1 Sta sp1 1
#> 2 Stb sp1 3
#> 3 Sta sp2 2
#> 4 Stc sp3 3