import.RInSp: Import data into a RInSp object

In RInSp: R Individual Specialization

Import data into a RInSp object

Description

The procedure reads and checks data to create an object of class RInSp.

Usage

import.RInSp(filename, col.header=FALSE, row.names = 0, info.cols= 0,
             subset.column = 0, subset.rows = NA, data.type= "integer",
             print.messages=TRUE, sep = "", dec = ".")

Arguments

filename	Name of the file or dataframe to be read.
col.header	Logical value to indicate if a header row is there. Default is FALSE.
row.names	Numeric value for column of rows' name. Default is zero for no names.
info.cols	A vector collecting columns numbers for additional information. Defaults is to have no additional information.
subset.column	A vector of columns' indices to be used as a subset. Default is to have no columns subsetting.
subset.rows	A string vector where the first element points to the column name to be used for rows subsetting, and following elements with criteria. Default is to have no rows subsetting.
data.type	Data type among "integer" or "double". From the data a proportion matrix will be produced. Default is to use integers/counts values.
print.messages	Prints messages concerning the number of rows and columns eventually deleted after subsetting because composed of all zeros. Default is TRUE.
sep	The field separator character. Values on each line of the file are separated by this character. If sep = "" (the default for read.table) the separator is ‘white space’, that is one or more spaces, tabs, newlines or carriage returns
dec	The character used in the file for decimal points.

Details

Three different types of data can be used. Integer/count values and decimal/real values are stored in the “resources” section of the output list and used to derive all meaningful information. While for proportions the “resources” section will be empty. Valid key words are: “integer”, “double”, and “proportion”. Use zero for empty cells.

The procedure will check for the presence of zero sum columns/rows for the selected dataset. A warning is printed in case of column/row deletion. It must be considered that the degree of checking on the subsetting is low.

Value

Return an list of class RInSp composed by:

resources	A matrix of the resources data.
proportions	A matrix of proportions of each resources in its row. This matrix can be imported into the software PAJEK (http://vlado.fmf.uni-lj.si/pub/networks/pajek/) to draw a weighted bipartite network connecting individuals to the various prey categories.
data.type	Data type used.
col.names	Name of the different columns of the resource data.
ind.names	Name of the individual.
info	A data frame containing additional information for the resource data.
num.prey	Number of resources/prey (i.e., columns) in the dataset after zero sum checking.
num.individuals	Number of individuals/sites (i.e., rows) in the dataset after zero sum checking.
num.zero.prey	Number of resources/prey (i.e., columns) in the dataset without zero sum checking.
num.ind.zero	Number of individuals/sites (i.e., rows) in the dataset without zero sum checking.

Author(s)

Dr. Nicola ZACCARELLI

Examples

data(Stickleback)
# Import data
GutContents <- import.RInSp(Stickleback,  row.names = 1, info.cols = c(2:13))
GutContents
# Select a single spatial sampling site (site A)
GutContents_SiteA <- import.RInSp(Stickleback, row.names = 1, info.cols = c(2:13),
subset.rows <- c("Site", "A"))

# Select a subset of prey types
GutContents_subset <- import.RInSp(Stickleback, row.names = 1, info.cols = c(2:13),
subset.column <- c(13:28, 45))

# Lump prey types into functional groups then import data
# define new columns representing lumped prey categories
attach(Stickleback)
Copepods <- Calanoid + Cyclopoid + Harpacticoid
Diptera <- Diptera.Pupae + Chironomid.larvae + Ceratopogonid.larvae + Tipulid.larvae +
Tipulidae.Adult + Diptera.Adult + Diptera.Larvae + Ceratopogonid.Adult
InsectLarvae <- Ephemeroptera + Trichoptera.larvae + Ephemeroptera.pupae +
Zygoptera.larvae + Plecoptera.larvae
Cladocera <- Bosmina + Polyphemus + Holopedium + Daphnia + Chydorus
names(Stickleback)
GutContents_lumped <- import.RInSp(Stickleback, row.names = 1, info.cols = c(2:13),
subset.column <- c(18,24,28,31,43:46))
rm(list=ls(all=TRUE))

RInSp documentation built on May 20, 2022, 9:06 a.m.