Purrring through - r

Question

I'm using fingertipsR to obtain public health data.
There are indicators at different geographic levels and these indicators are also grouped at profile level.
Here's some code:
library(fingertipsR)
library(fingertipscharts)
library(tidyverse)
library(ggthemes)
fingertips_stats()
inds<-indicators_unique()
profs<-profiles()
it's possible to pull unique indicators for profiles like this and then to add a column like this
smoking<-indicators_unique(ProfileID = 18,DomainID = NULL)%>%mutate(prof_id="18")
What I'd like to do is:
for each unique profile ID generate a dataframe of indicators. There are 53 unique profiles
uniqueprofs<-as_tibble(unique(profs$ProfileID))
How can I purr through this? or loop?
I am routinely stuck on these iteration type problems.
EDIT:
so. if you ctrl + click on
indicators_unique
you'll see the bit:
df <- unique(df[, c("IndicatorID", "IndicatorName")])
I copied all of the function and called it something else
function (ProfileID = NULL, DomainID = NULL, path)
{
if (missing(path))
path <- fingertips_endpoint()
#fingertips_ensure_api_available(endpoint = path)
df <- indicators(ProfileID, DomainID, path = path)
df <- unique(df[, c("IndicatorID", "IndicatorName","ProfileID")])
return(df)
}
And I now get a dataframe containing the ProfileID. If I add "DomainID" I can have that too....
Edit:
Annoyingly, I've asked a similar question and updated it with dplyr group_by and group_walk
I can do this:
inds%>%group_by(ProfileID)%>%group_walk(~ write.csv(.x, paste0(.y$ProfileID, ".csv")))
How do I group_walk and write the dataframes/tibbles to the environment rather than writing them a drive and then loading them in?

Answer 1

Start with some minimal initial code
library(fingertipsR)
library(tidyverse)
profs<-profiles()
indictators_unique is already vectorized so rather than loading the ProfileIDs into a tibble, put them in a list and then you can do a simple
unique_profs <- list(unique(profs$ProfileID))
indicators_unique(ProfileID = unique_profs, DomainID = NULL)
The issue is adding your desired prof_id column. I'm not familiar with these packages. Is there any dataframe that links ProfileID to either IndicatorID or IndicatorName that you can do a join on?