Load raw data from disk and aggregate (using the mean function)
observations with duplicated IDs (first column). Non-numeric columns must
be excluded using the excluded_columns parameter.
load_raw(raw_data_filename, excluded_columns = NULL)Filename containing the raw data, it can be a
relative path (e.g. "my_input.csv") or an absolute path (e.g.
"/path/to/my_input.csv").
Numeric vector containing the indices of the dataset properties that are non-numeric, excluded columns.
Data frame with the pre-processed raw data.
# Toy dataset
example_data <- data.frame(ID = c(1,2,3,4,5),
P1 = c("one", "two", "three", "four", "five"),
T1 = rnorm(5),
T2 = rnorm(5))
write.csv(example_data,
file.path(tempdir(), "example_data.csv"),
row.names = FALSE)
write.csv(example_data[c(1:5, 1, 2), ],
file.path(tempdir(), "example_data_dup.csv"),
row.names = FALSE)
knitr::kable(MetaPipe::load_raw(file.path(tempdir(), "example_data.csv"),
c(1, 2)))
#>
#>
#> | ID|P1 | T1| T2|
#> |--:|:-----|----------:|----------:|
#> | 1|one | -1.1346302| 0.5904787|
#> | 2|two | 0.7645571| -1.4130700|
#> | 3|three | 0.5707101| 1.6103416|
#> | 4|four | -1.3516939| 1.8404425|
#> | 5|five | -2.0298855| 1.3682979|
knitr::kable(MetaPipe::load_raw(file.path(tempdir(), "example_data_dup.csv"),
c(1, 2)))
#>
#>
#> | ID|P1 | T1| T2|
#> |--:|:-----|----------:|----------:|
#> | 1|one | -1.1346302| 0.5904787|
#> | 2|two | 0.7645571| -1.4130700|
#> | 3|three | 0.5707101| 1.6103416|
#> | 4|four | -1.3516939| 1.8404425|
#> | 5|five | -2.0298855| 1.3682979|
# F1 Seedling Ionomics dataset
ionomics_path <- system.file("extdata",
"ionomics.csv",
package = "MetaPipe",
mustWork = TRUE)
ionomics <- MetaPipe::load_raw(ionomics_path)
knitr::kable(ionomics[1:5, 1:8])
#>
#>
#> |ID | SampleWeight| Ca44| K39| P31| Li7| B11| Na23|
#> |:-----|------------:|--------:|--------:|--------:|---------:|--------:|---------:|
#> |E_199 | 79| 32675.79| 6051.023| 2679.338| 0.1159068| 23.32975| 9.372606|
#> |E_209 | 81| 28467.95| 5642.651| 2075.403| 0.0104801| 27.31206| 8.787553|
#> |E_035 | 81| 27901.35| 7357.856| 2632.343| 0.0561879| 16.87480| 14.369062|
#> |E_197 | 79| 27855.36| 5225.275| 1761.725| 0.0104453| 25.34740| 11.009597|
#> |E_016 | 79| 27377.40| 6141.001| 2145.715| 0.0172996| 24.64500| 6.999958|