Read in plantCV csv output in wide or long format

Usage

read.pcv(
  filepath,
  mode = NULL,
  traitCol = "trait",
  labelCol = "label",
  valueCol = "value",
  reader = NULL,
  filters = NULL,
  awk = NULL,
  ...
)

Arguments

filepath: Path to csv file of plantCV output.
mode: NULL (the default) or one of "wide" or "long", partial string matching is supported. This controls whether data is returned in long or wide format. If left NULL then the output format will be the same as the input format.
traitCol: Column with phenotype names, defaults to "trait". This should generally not need to be changed from the default. This, labelCol, and valueCol are used to determine if data are in long format in their raw state (the csv file itself).
labelCol: Column with phenotype labels (units), defaults to "label". This should generally not need to be changed from the default. This is used with traitCol when mode="wide" to identify unique traits since some may be ambiguous (ellipseCenter.x vs ellipseCenter.y, bins of histograms, etc)
valueCol: Column with phenotype values, defaults to "value". This should generally not need to be changed from the default.
reader: The function to use to read in data, defaults to NULL in which case data.table::fread is used if filters are in place and read.csv is used otherwise. Note that if you use read.csv with filters in place then you will need to specify header=FALSE so that the piped output from awk is read correctly. If fread is too slow for your needs then vroom::vroom() may be useful.
filters: If a very large pcv output file is read then it may be desireable to subset it before reading it into R, either for ease of use or because of RAM limitations. The filter argument works with "COLUMN in VALUES" syntax. This can either be a character vector or a list of character vectors. In these vectors there needs to be a column name, one of " in ", " is ", or " = " to match the string exactly, or "contains" to match with awk style regex, then a set of comma delimited values to filter that column for (see examples). Note that this and awk both use awk through pipe(). This functionality will not work on a windows system.
awk: As an alternative to filters a direct call to awk can be supplied here, in which case that call will be used through pipe().
...: Other arguments passed to the reader function. In the case of 'fread' there are several defaults provided already which can be overwritten with these extra arguments.

Value

Returns a data.frame in wide or long format.

Details

In plantCV version 4 the single value traits are returned in wide format from json2csv and the multi value traits are returned in long format. Briefly plantCV data was returned as one long table which sparked the emphasis in this function on reading data quickly and parsing it outside of R. With the current plantCV output these options are largely unnecessary. When data is read in using read.pcv the traitCol, valueCol, and labelCol arguments are checked to determine if the data is in long format. This is done to keep compatibility with interim versions of plantcv output where all outputs were in a single long format file.

With the current implementation and plantcv output you can read wide or long format files into wide or long format in R. Keep in mind that the 'mode' argument controls the format that will be returned in R, not the format that the data saved as in your csv file.

Examples

# \donttest{
tryCatch(
  {
    mv <- paste0(
      "https://media.githubusercontent.com/media/joshqsumner/",
      "pcvrTestData/main/pcv4-multi-value-traits.csv"
    )
    sv <- paste0(
      "https://raw.githubusercontent.com/joshqsumner/",
      "pcvrTestData/main/pcv4-single-value-traits.csv"
    )

    w2w <- read.pcv(sv, mode = "wide", reader = "fread")
    dim(w2w)

    w2l <- read.pcv(sv, mode = "long", reader = "fread")
    dim(w2l)

    l2w <- read.pcv(mv, mode = "wide", reader = "fread")
    dim(l2w)

    l2l <- read.pcv(mv, mode = "long", reader = "fread")
    dim(l2l)
  },
  error = function(e) {
    message(e)
  }
)
#> [1] 513720     21
# }