TLDR: I had to find a way to join two tibbles such that the rows corresponded with each other correctly. In a stroke of genius, I realised I could give each row a unique ID to use as an organising variable when joining the tibbles together.
You can see my excitement in the code annotations below.
```{r (i deleted the other bracket so that the document could knit without me having to read all the relevant data sets)
Study2_HouseholdSummary3 <- Study2_HouseholdSummary2 %>% pivot_longer(cols = c(mean_emp, mean_physdist), names_to = “category_mean”, values_to = “means”) %>% mutate(ID = 1:16) #https://statisticsglobe.com/assign-unique-id-for-each-group-in-r
Study2_HouseholdSummary4 <- Study2_HouseholdSummary2 %>% pivot_longer(cols = c(sd_emp, sd_physdist), names_to = “category_sd”, values_to = “sd”) %>% mutate(ID = 1:16)
Study2_HouseholdJoin <- Study2_HouseholdSummary4 %>% left_join(Study2_HouseholdSummary3, by = “ID”)
print(Study2_HouseholdJoin) #omg it works ok lets see if i can make it into a graph
```