This function processes the Gradescope data before grading. Ungraded assignments (i.e. assignments with all NAs for their scores) can optionally be dropped. Eventually, this will also merge duplicated students and deal with students with no SID.
Examples
process_gs(gs = gs_demo, drop_ungraded = TRUE, verbose = TRUE)
#> Important Message
#> ℹ These are no ungraded assignments
#> # A tibble: 10 × 44
#> Names Email SID Sections `Lab 1` `Lab 1 - Max Points`
#> <chr> <chr> <dbl> <chr> <dbl> <dbl>
#> 1 Dr. Kadin Dr.Kadin@be… 3.03e9 fake-cl… 9 10
#> 2 Bartley Toy BartleyToy@… 3.03e9 fake-cl… 5 10
#> 3 Dr. Dontae Dr.Dontae@b… 3.03e9 fake-cl… 10 10
#> 4 Narcissus Considine NarcissusCo… 3.03e9 fake-cl… 10 10
#> 5 Verne Wilderman VerneWilder… 3.03e9 fake-cl… 8 10
#> 6 Toivo Witting ToivoWittin… 3.03e9 fake-cl… 9 10
#> 7 Tegan Crooks TeganCrooks… 3.03e9 fake-cl… 8 10
#> 8 Tyrus Cremin-Wisozk TyrusCremin… 3.03e9 fake-cl… 2 10
#> 9 Sydni Hansen SydniHansen… 3.03e9 fake-cl… 8 10
#> 10 Mrs. Chelsie Mrs.Chelsie… 3.03e9 fake-cl… 5 10
#> # ℹ 38 more variables: `Lab 1 - Submission Time` <chr>,
#> # `Lab 1 - Lateness (H:M:S)` <time>, `Lab 2` <dbl>,
#> # `Lab 2 - Max Points` <dbl>, `Lab 2 - Submission Time` <chr>,
#> # `Lab 2 - Lateness (H:M:S)` <time>, `Lab 3` <dbl>,
#> # `Lab 3 - Max Points` <dbl>, `Lab 3 - Submission Time` <chr>,
#> # `Lab 3 - Lateness (H:M:S)` <time>, `Lab 4` <dbl>,
#> # `Lab 4 - Max Points` <dbl>, `Lab 4 - Submission Time` <chr>, …