Wb to df cleanup

[JanMarvin]

This cuts the time wasted doing ... nothing. Oh this did cost me almost a day, tweaking back and forth 😄 (I hate optimizing my own code). Though I assume there are a few other places where we simply select something and try to get away with it. (Edit: With other places I mean functions I wrote and with we I mean me ofc 🙈 )

Unit: milliseconds
                                                   expr       min        lq      mean    median        uq       max neval
             wb_old <- openxlsx::loadWorkbook(xlsxFile) 119.04867 122.62752 129.43213 125.08641 128.56099 204.89869    25
                 wb_new <- openxlsx2::wb_load(xlsxFile)  82.15260  83.24123  86.36275  85.13675  86.59532  96.14397    25
    x_old <- openxlsx::read.xlsx(wb_old, sheet = sheet)  11.82465  12.44604  17.24027  12.83931  13.56616  98.14137    25
   x_new <- openxlsx2::read_xlsx(wb_new, sheet = sheet)  39.38849  40.06065  43.35709  40.54560  46.85837  55.08895    25
         openxlsx::saveWorkbook(wb_old, xlsx_old, TRUE) 330.11265 338.87480 364.67391 344.69655 353.43451 536.59185    25
             openxlsx2::wb_save(wb_new, xlsx_new, TRUE) 230.22640 235.91002 249.66324 239.08765 244.97935 336.63808    25
  x_old <- openxlsx::read.xlsx(xlsxFile, sheet = sheet)  78.24407  79.80921  81.53757  80.54667  81.48225  98.49348    25
 x_new <- openxlsx2::read_xlsx(xlsxFile, sheet = sheet)  92.46984  95.17568  99.36759  96.93220 102.30894 111.38240    25

[JanMarvin]

table() is slow, but not slow enough to be replaced.

[JanMarvin]

in the table there might not be a column "b", therefore enforce this check with isTRUE