Import data
# excel file
data <- read_excel("../00_data/Salaries.xlsx")
data
## # A tibble: 397 × 6
## rank discipline yrs.since.phd yrs.service sex salary
## <chr> <chr> <dbl> <dbl> <chr> <dbl>
## 1 Prof B 19 18 Male 139750
## 2 Prof B 20 16 Male 173200
## 3 AsstProf B 4 3 Male 79750
## 4 Prof B 45 39 Male 115000
## 5 Prof B 40 41 Male 141500
## 6 AssocProf B 6 6 Male 97000
## 7 Prof B 30 23 Male 175000
## 8 Prof B 45 45 Male 147765
## 9 Prof B 21 20 Male 119250
## 10 Prof B 18 18 Female 129000
## # ℹ 387 more rows
Apply the following dplyr verbs to your data
Filter rows
filter(data, rank == "Prof")
## # A tibble: 266 × 6
## rank discipline yrs.since.phd yrs.service sex salary
## <chr> <chr> <dbl> <dbl> <chr> <dbl>
## 1 Prof B 19 18 Male 139750
## 2 Prof B 20 16 Male 173200
## 3 Prof B 45 39 Male 115000
## 4 Prof B 40 41 Male 141500
## 5 Prof B 30 23 Male 175000
## 6 Prof B 45 45 Male 147765
## 7 Prof B 21 20 Male 119250
## 8 Prof B 18 18 Female 129000
## 9 Prof B 20 18 Male 104800
## 10 Prof B 12 3 Male 117150
## # ℹ 256 more rows
Arrange rows
arrange(data, yrs.since.phd)
## # A tibble: 397 × 6
## rank discipline yrs.since.phd yrs.service sex salary
## <chr> <chr> <dbl> <dbl> <chr> <dbl>
## 1 AsstProf B 1 1 Male 77700
## 2 AsstProf B 1 1 Male 70768
## 3 AsstProf B 1 0 Male 88000
## 4 AsstProf B 1 0 Male 88795
## 5 AsstProf B 2 0 Male 78000
## 6 AsstProf B 2 2 Male 88400
## 7 AsstProf A 2 0 Female 72500
## 8 AsstProf B 2 2 Male 89516
## 9 AsstProf A 2 0 Male 85000
## 10 AsstProf B 3 2 Male 75243
## # ℹ 387 more rows
Select columns
Add columns
Summarize by groups