Thanks for the tutorial it was very helpful.
I think it is this right?
rcommunity <- tibble::tribble(
~Ative_Inactive, ~STATUS, ~Gender_Recode, ~Employee_ID, ~Nationality, ~Gender, ~Date_Birth, ~Age_Entrie, ~Age_Employee, ~Length_Time_Year, ~Length_Time_Month, ~Admission_Date, ~Admisson_Year, ~Dismissal_Date, ~Year_Demisson, ~Job, ~Tier, ~Rank, ~Business, ~Client, ~Costumer, ~ID_BUM, ~BUM, ~ID_Manager, ~Manager, ~Manager_Recode, ~`Rate/_Hour`, ~Annual_Gross_Salary,
0L, "ACTIVE", 1L, 3L, "PT", "Male", "29/04/1980", 29L, 40L, 11L, 1L, "04/01/2010", 2010L, NA, NA, "eefv", "edf", "defg", "Consulting", "nbm", "ktb", 917L, "Carol", "Colle", "Colleague_1", "Colleague", "36,00 €", "39 657,34 €",
0L, "ACTIVE", 1L, 17L, "PT", "Male", "18/04/1976", 34L, 44L, 10L, 7L, "05/07/2010", 2010L, NA, NA, "efef", "wdvf", "defe", "Consulting", "dth", "nbv", 189L, "Rick", "Colle", "Colleague_2", "Ashley", "32,50 €", "33 637,53 €"
)
head(rcommunity)
#> # A tibble: 2 x 28
#> Ative_Inactive STATUS Gender_Recode Employee_ID Nationality Gender Date_Birth
#> <int> <chr> <int> <int> <chr> <chr> <chr>
#> 1 0 ACTIVE 1 3 PT Male 29/04/1980
#> 2 0 ACTIVE 1 17 PT Male 18/04/1976
#> # ... with 21 more variables: Age_Entrie <int>, Age_Employee <int>,
#> # Length_Time_Year <int>, Length_Time_Month <int>, Admission_Date <chr>,
#> # Admisson_Year <int>, Dismissal_Date <lgl>, Year_Demisson <lgl>, Job <chr>,
#> # Tier <chr>, Rank <chr>, Business <chr>, Client <chr>, Costumer <chr>,
#> # ID_BUM <int>, BUM <chr>, ID_Manager <chr>, Manager <chr>,
#> # Manager_Recode <chr>, `Rate/_Hour` <chr>, Annual_Gross_Salary <chr>