R code (Rstats) calculating unemployment rate based off columns in long form data

Question

I am trying to calculate the unemployment rate based of the data below and add it as new rows to the data table. I want to divide unemployed by labourforce based off the date and add each datapoint as a row.

Essentially, I am trying to go from this

date	series_1	value
2021-01-01	labourforce	13793
2021-02-01	labourforce	13812
2021-03-01	labourforce	13856
2021-01-01	unemployed	875
2021-02-01	unemployed	805
2021-03-01	unemployed	778

to this

date	series_1	value
2021-01-01	labourforce	13793
2021-02-01	labourforce	13812
2021-03-01	labourforce	13856
2021-01-01	unemployed	875
2021-02-01	unemployed	805
2021-03-01	unemployed	778
2021-01-01	unemploymentrate	6.3
2021-02-01	unemploymentrate	5.8
2021-03-01	unemploymentrate	5.6

Here is my code so far. I know the last line is wrong? Any suggestions or ideas are welcome!

longdata %>% 
  group_by(date) %>%
  summarise(series_1 = 'unemploymentrate',
  value = series_1$unemployed/series_1$labourforce))

Answer 1

Fro each day, you can get the ratio of 'unemployed' by 'labourforce' and add it as new rows to your original dataset.

library(dplyr)

df %>% 
  group_by(date) %>%
  summarise(value = value[series_1 == 'unemployed']/value[series_1 == 'labourforce'] * 100, 
            series_1 = 'unemploymentrate') %>%
  bind_rows(df) %>%
  arrange(series_1)

#   date          value series_1        
#  <chr>         <dbl> <chr>           
#1 2021-01-01 13793    labourforce     
#2 2021-02-01 13812    labourforce     
#3 2021-03-01 13856    labourforce     
#4 2021-01-01   875    unemployed      
#5 2021-02-01   805    unemployed      
#6 2021-03-01   778    unemployed      
#7 2021-01-01     6.34 unemploymentrate
#8 2021-02-01     5.83 unemploymentrate
#9 2021-03-01     5.61 unemploymentrate