Applying a function using elements within a list take 2 - r

Question

I attempted this question yesterday(Applying a function using elements within a list) but my reprex produced the wrong data structure and unfortunately the suggestions didn't work for my actual dataset.
I have what is hopefully a simple functional programming question. I have a list of locations with average temperature and amplitude for each day (180 days in my actual dataset). I want to iterate through these locations and create a sine curve of 24 points using a custom made function taking the average temperature and amplitude from each day within a list. Below is my new reprex.
library(tibble)
library(REdaS)##degrees to radians
library(tidyverse)
sinefunc<- function(Amplitude,Average){
hour<- seq(0,23,1)
temperature<-vector("double",length = 24)
for(i in seq_along(hour)){
temperature[i]<- (Amplitude*sin(deg2rad(180*(hour[i]/24)))+Average)+Amplitude*sin(deg2rad(180*hour[i]/12))
}
temperature
}
data<- tibble(Location = c(rep("London",6),rep("Glasgow",6),rep("Dublin",6)),
Day= rep(seq(1,6,1),3),
Average = runif(18,0,20),
Amplitude = runif(18,0,15))%>%
nest_by(Location)
Using Purrr and map_dfr I get the error Error in .x$Average : $ operator is invalid for atomic vectors
df<-data %>%
map_dfr(~sinefunc(.x$Average, .x$Amplitude))
Using lapply I get the error Error in x[, "Amplitude"] : incorrect number of dimensions
data <- lapply(data, function(x){
sinefunc(Amplitude = x[,"Amplitude"], Average = x[,"Average"])
})
My goal is to have 24 hourly data points for each day and location.
Any further help would be much appreciated.
Stuart

Answer 1

Maybe you look for this? You get a dataframe back with 24 datapoints for each day and location, e.g. London-Day1, Dublin-Day1 etc.
library(dplyr)
library(purrr)
data<- tibble(Location = c(rep("London",6),rep("Glasgow",6),rep("Dublin",6)),
Day= rep(seq(1,6,1),3),
Average = runif(18,0,20),
Amplitude = runif(18,0,15))
# get group name
group_name <- data %>%
group_by(Location, Day) %>%
group_keys() %>%
mutate(group_name = stringr::str_c(Location,"_",Day)) %>%
pull(group_name)
data %>%
# split into lists
group_split(Location, Day) %>%
# get list name
setNames(group_name) %>%
# apply your function and get a dataframe back
map_dfr(~sinefunc(.x$Average, .x$Amplitude))