Interpolate based on multiple conditions in r - r

Question

Beginner r user here. I have a dataset of yearly employment numbers for different industry classifications and different subregions. For some observations, the number of employees is null. I would like to fill these values through linear interpolation (using na.approx or some other method). However, I only want to interpolate within the same industry classification and subregion.
For example, I have this:
subregion <- c("East Bay", "East Bay", "East Bay", "East Bay", "East Bay", "South Bay")
industry <-c("A","A","A","A","A","B" )
year <- c(2013, 2014, 2015, 2016, 2017, 2002)
emp <- c(50, NA, NA, 80,NA, 300)
data <- data.frame(cbind(subregion,industry,year, emp))
subregion industry year emp
1 East Bay A 2013 50
2 East Bay A 2014 <NA>
3 East Bay A 2015 <NA>
4 East Bay A 2016 80
5 East Bay A 2017 <NA>
6 South Bay B 2002 300
I need to generate this table, skipping interpolating the fifth observation because subregion and industry do not match the previous observation.
subregion industry year emp
1 East Bay A 2013 50
2 East Bay A 2014 60
3 East Bay A 2015 70
4 East Bay A 2016 80
5 East Bay A 2017 <NA>
6 South Bay B 2002 300
Articles like this have been helpful, but I cannot figure out how to adapt the solution to match the requirement that two columns be the same for interpolation to occur, instead of one. Any help would be appreciated.

Answer 1

We could do a group by na.approx (from zoo)
library(tidyverse)
data %>%
group_by(subregion, industry) %>%
mutate(emp = zoo::na.approx(emp, na.rm = FALSE))
# A tibble: 6 x 4
# Groups: subregion, industry [2]
# subregion industry year emp
# <fct> <fct> <dbl> <dbl>
#1 East Bay A 2013 50
#2 East Bay A 2014 60
#3 East Bay A 2015 70
#4 East Bay A 2016 80
#5 East Bay A 2017 NA
#6 South Bay B 2002 300
data
data <- data.frame(subregion,industry,year, emp)