Grouping and finding mean in R dataframe

Grouping and finding mean in R dataframe

Problem Description:

I have a table like this:

I have the Grades as a factor where grades = DP, G, H

I need to create a table that gives me the mean salary by grade for full-time males (ftMale) and part-time males (ptMale) like so:

My dataset is a lot larger than this and there would be means for part time and full time in each grade. Any help would be much appreciated!
Thanks

Solution – 1

Group by Grade and then summarize your data by getting the mean of Salary while making sure that you are subsetting to the relevant ftMale/ptMale values.

library(tidyverse)

df |>
  group_by(Grade) |>
  summarize(full_time_male = mean(Salary[genderTime == "ftMale"]),
            part_time_male = mean(Salary[genderTime == "ptMale"]))

Solution – 2

Another dplyr approach:

df %>% 
  group_by(genderTime, Grade) %>% 
  summarise(Salary = mean(Salary, na.rm=TRUE)) %>% 
  ungroup() %>% 
  pivot_wider(names_from = genderTime, values_from = Salary, values_fill = 0) %>% 
  select("Grade", "ftMale", "ptMale")

# A tibble: 3 × 3
  Grade ftMale ptMale
  <chr>  <dbl>  <dbl>
1 H          0  37250
2 G      34000      0
3 DP         0  15500

Just another (slightly different) dplyr solution

df %>% 
  filter(genderTime %in% c("ftMale", "ptMale")) %>% 
  group_by(genderTime, Grade) %>% 
  summarise(Salary = mean(Salary, na.rm=TRUE)) %>% 
  pivot_wider(names_from = genderTime, values_from = Salary, values_fill = 0)

The same using full R base:

reshape(aggregate(Salary ~ genderTime + Grade, 
                  subset = genderTime %in% c("ftMale", "ptMale"), 
                  FUN=mean, 
                  data=df), 
        direction = "wide", 
        idvar = "Grade", 
        timevar = "genderTime")