cf_files %>% iso_get_problems_summary() %>% rmarkdown::paged_table()

cf_files %>% iso_get_problems() %>% rmarkdown::paged_table()

# select + rename specific file info columns
cf_files2 <- cf_files %>%
  iso_select_file_info(
    ID = `Identifier 1`, ID = `Name`, Analysis, `Peak Center`, `H3 Factor`,
    `Date & Time` = file_datetime,
    # recode to the same name in different files
    `Sample Weight` = `Identifier 2`, `Sample Weight` = `EA Sample Weight`,
    file_specific = TRUE
  )
#> Info: selecting/renaming the following file info:
#>  - for 4 file(s): 'file_id', 'Name'->'ID', 'file_datetime'->'Date & Time', 'EA Sample Weight'->'Sample Weight'
#>  - for 2 file(s): 'file_id', 'Identifier 1'->'ID', 'Analysis', 'Peak Center', 'H3 Factor', 'file_datetime'->'Date & Time', 'Identifier 2'->'Sample Weight'

# fetch all file info
cf_files2 %>% iso_get_file_info() %>% rmarkdown::paged_table()
#> Info: aggregating file info from 6 data file(s)

# find files that have 'acetanilide' in the new ID field
cf_files2 %>% iso_filter_files(grepl("acetanilide", ID)) %>%
  iso_get_file_info() %>%
  rmarkdown::paged_table()
#> Info: applying file filter, keeping 1 of 6 files
#> Info: aggregating file info from 1 data file(s)

# find files that were run since 2015
cf_files2 %>%
  iso_filter_files(`Date & Time` > "2015-01-01") %>%
  iso_get_file_info() %>%
  rmarkdown::paged_table()
#> Info: applying file filter, keeping 1 of 6 files
#> Info: aggregating file info from 1 data file(s)

cf_files3 <-
  cf_files2 %>%
  iso_mutate_file_info(
    # update existing column
    ID = paste("ID:", ID),
    # introduce new column
    `Run since 2015?` = `Date & Time` > "2015-01-01",
    # parse weight as a number and turn into a column with units
    `Sample Weight` = `Sample Weight` %>% parse_number() %>% iso_with_units("mg")
  )
#> Info: mutating file info for 6 data file(s)

cf_files3 %>%
  iso_get_file_info() %>%
  iso_make_units_explicit() %>%
  rmarkdown::paged_table()
#> Info: aggregating file info from 6 data file(s)

# this kind of information data frame is frequently read in from a csv or xlsx file
new_info <-
  dplyr::bind_rows(
    # new information based on new vs. old samples
    dplyr::tribble(
      ~file_id, ~`Run since 2015?`,  ~process,  ~info,
       NA,       TRUE,                "yes",     "new runs",
       NA,       FALSE,               "yes",     "old runs"
    ),
    # new information for a single specific file
    dplyr::tribble(
      ~file_id,        ~process,  ~note,
       "6617_IAEA600",  "no",      "did not inject properly"
    )
  )
new_info %>% rmarkdown::paged_table()

# adding it to the isofiles
cf_files3 %>%
  iso_add_file_info(new_info, by1 = "Run since 2015?", by2 = "file_id") %>%
  iso_get_file_info(select = !!names(new_info)) %>%
  rmarkdown::paged_table()
#> Info: adding new file information ('process', 'info', 'note') to 6 data file(s), joining by 'Run since 2015?' then 'file_id'...
#>  - 'Run since 2015?' join: 2/2 new info rows matched 6/6 data files - 1 of these was/were also matched by subsequent joins which took precedence
#>  - 'file_id' join: 1/1 new info rows matched 1/6 data files
#> Info: aggregating file info from 6 data file(s), selecting info columns 'file_id', 'Run since 2015?', 'process', 'info', 'note'

# use parsing and extraction in iso_mutate_file_info
cf_files2 %>%
  iso_mutate_file_info(
    # change type of Peak Center to logical
    `Peak Center` = parse_logical(`Peak Center`),
    # retrieve first word of file_id
    file_id_1st = extract_word(file_id),
    # retrieve second word of ID column
    file_id_2nd = extract_word(file_id, 2),
    # retrieve file extension from the file_id using regular expression
    name = extract_substring(ID, "(\\w+)-?(.*)?", capture_bracket = 1)
  ) %>%
  iso_get_file_info(select = c(matches("file_id"), ID, name, `Peak Center`)) %>%
  rmarkdown::paged_table()
#> Info: mutating file info for 6 data file(s)
#> Info: aggregating file info from 6 data file(s), selecting info columns 'c(matches("file_id"), ID, name, `Peak Center`)'

# use parsing in iso_filter_file_info
cf_files2 %>%
  iso_filter_files(parse_number(`H3 Factor`) > 2) %>%
  iso_get_file_info() %>%
  rmarkdown::paged_table()
#> Info: applying file filter, keeping 1 of 6 files
#> Info: aggregating file info from 1 data file(s)

# use iso_parse_file_info for simplified parsing of column data types
cf_files2 %>%
  iso_parse_file_info(
    integer = Analysis,
    number = `H3 Factor`,
    logical = `Peak Center`
  ) %>%
  iso_get_file_info() %>%
  rmarkdown::paged_table()
#> Info: parsing 3 file info columns for 6 data file(s):
#>  - to integer: 'Analysis'
#>  - to logical: 'Peak Center'
#>  - to number: 'H3 Factor'
#> Info: aggregating file info from 6 data file(s)

# entire vendor data table
cf_files %>% iso_get_vendor_data_table() %>% rmarkdown::paged_table()
#> Info: aggregating vendor data table from 6 data file(s)

# get specific parts and add some file information
cf_files %>%
  iso_get_vendor_data_table(
    # select peak number, ret. time, overall intensity and all H delta columns
    select = c(Nr., Rt, area = `rIntensity All`, matches("^d \\d+H")),
    # include the Analysis number fron the file info and rename it to 'run'
    include_file_info = c(run = Analysis)
  ) %>%
  rmarkdown::paged_table()
#> Info: aggregating vendor data table from 6 data file(s), including file info 'c(run = Analysis)'

# the data table also provides units if included in the original data file
# which can be made explicit using the function iso_make_units_explicit()
cf_files %>%
  iso_get_vendor_data_table(
    # select peak number, ret. time, overall intensity and all H delta columns
    select = c(Nr., Rt, area = `rIntensity All`, matches("^d \\d+H")),
    # include the Analysis number fron the file info and rename it to 'run'
    include_file_info = c(run = Analysis)
  ) %>%
  # make column units explicit
  iso_make_units_explicit() %>%
  rmarkdown::paged_table()
#> Info: aggregating vendor data table from 6 data file(s), including file info 'c(run = Analysis)'