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Process 1 feeder data file

Source: R/data_pipeline.R
process_feeder.Rd

Reads, cleans, and filters a feeder file:

  1. Safely read the CSV / DAT file

  2. Rename columns

  3. Drop unwanted cows & transponders

  4. Keep only specified bins

  5. Subset to desired columns

Usage

process_feeder(
  file,
  col_names = NULL,
  id_col = id_col2(),
  drop_ids = NULL,
  trans_col = trans_col2(),
  drop_trans = NULL,
  bin_col = bin_col2(),
  bins = bins_feed2(),
  select_cols = NULL,
  sep = ",",
  header = FALSE
)

Arguments

file

What's the path to your data file? This should be a single string giving the path to the file.

col_names

A character vector of column names to assign when header = FALSE. This vector must match the number of columns in the raw data. If header = TRUE, the file’s existing column names are used and col_names is ignored.

id_col

What's the name of the column recording animal ID? This should be a Single string. (default: "cow").

drop_ids

Which animals do you wish to drop? This should be a vector indicating values in id_col that you wish to remove (default: NULL, so remove nothing).

trans_col

What's the name of the column recording transponder ID for each visit? This should be a single string. (default: "transponder").

drop_trans

Which transponders do you wish to delete because they are not part of your study? This should be a vector indicating values in trans_col that you wish to remove (default: NULL, so remove nothing).

bin_col

What's the name of the column recording the ID of the bin for each visit? This should be a single string. (default: "bin").

bins

Which feed bins are included in your study? This should be a numeric vector indicating bin IDs to keep (e.g. 2:4 or c(1,5)). Default is 1:30.

select_cols

Which columns in the dataframe do you wish to keep in your original data frame after cleaning? This should be a character vector indicating columns to retain in the final output. Default is NULL, so we select all columns.

sep

Field separator; passed to read.table(). Defaults to "," for comma delimited files like .csv and .DAT.

header

Logical; does your data file have a header row (i.e., column names)? Defaults to FALSE. If yor file contains column names at the top, please set this to TRUE.

Value

A cleaned feeder data frame.

Examples

# Create a toy feeder data frame
original <- data.frame(
  cow = c("A", "B", "C", "A"),
  transponder = c("X1", "X2", "X3", "X2"),
  bin = c(1, 2, 3, 2),
  value = c(10, 20, 30, 40),
  stringsAsFactors = FALSE
)
print(original)
#>   cow transponder bin value
#> 1   A          X1   1    10
#> 2   B          X2   2    20
#> 3   C          X3   3    30
#> 4   A          X2   2    40
tmp <- tempfile(fileext = ".csv")
write.csv(original, tmp, row.names = FALSE)

# Drop cow "A" and transponder "X2", keep bins 2:3, select only cow, bin, value
process_feeder(
  file = tmp,
  drop_ids = "A",
  drop_trans = "X2",
  bins = 2:3,
  select_cols = c("cow", "bin", "value"),
  header = TRUE
)
#>   cow bin value
#> 3   C   3    30
unlink(tmp)