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