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tidyplate
Start by loading tidyplate:
Import multiple csv files into separate tibbles:
file <- system.file("extdata",
"example_12_well.xlsx",
package = "tidyplate")
csv_files <- list.files(path = file,
pattern = "*.csv",
full.names = TRUE)
names <- tools::file_path_sans_ext(basename(csv_files))
# Loop through the filenames and assign data
for(i in seq_along(csv_files)) {
assign(names[i], tidy_plate(csv_files[i]))
}
Import multiple csv files as a list of tibbles:
# Initialize an empty list to store tibbles for each file
tb_csv_list <- list()
# Loop through the filenames and assign data
for(i in seq_along(csv_files)) {
tb_csv_list[[i]] <- tidy_plate(csv_files[i])
}
For multiple excel sheets in the same excel file:
# as individual tibbles
xl_file <- system.file("extdata",
"multisheet_example.xlsx",
package = "tidyplate")
sheets <- readxl::excel_sheets(xl_file)
for (sheet in sheets) {
tb <- tidy_plate(xl_file, sheet = sheet)
name <- paste0("tb_", sheet)
assign(name, tb)
}
#> Plate type: 6-well
#> Plate type: 12-well
#> Plate type: 12-well
# as elements of a list
# Initialize an empty list to store tibbles for each sheet
tb_xl_list <- list()
for (sheet in sheets) {
tb_xl_list[[sheet]] <- tidy_plate(xl_file, sheet = sheet)
}
#> Plate type: 6-well
#> Plate type: 12-well
#> Plate type: 12-well
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.