Put Correlation Output of Function into Data Frame - r

Question

I am performing a lot of correlations of a populations over time. I have split them up accordingly and have put them through a function with lapply. I want to put the output of each correlation into a data frame (i.e.: each row will be the info for one correlation, with the columns: correlation's name, p-value, t statistic, df, CIs, and corcoeff).
I have two issues:
I don't know how to extract the name of the correlation made in the split
I can get my function to run the correlation on the split (600+ Correlations), but I can't get it to print it into the data frame. To clarify: When I run the function without the loop, it does all 600 Correlations for each group. However, when I add the loop, it produces NULL for all the groups in the split.
Here is what I have thus far:
> head(Birds) #Shortened for this Post
Location Species Year Longitude Latitude Section Total Percent Family
1 Chiswell A Kittiwake 1976 -149.5847 59.59559 Central 310 16.78397 Gull
BigSplit<-split(Birds,list(Birds$Family, Birds$Location,
Birds$Section,Birds$Species), drop=T) #A list of Dataframes
#Make empty data frame
resultcor <- data.frame(Name = character(),
tvalue = character(),
degreeF = character(),
pvalue = character(),
CIs = character(),
corcoeff = character(),stringsAsFactors = F)
WorkFunc <- function(dataset) {
data.name = substitute(dataset) #Use "dataset" as substitute for actual dataset name
#Correlation between Year and population Percent
try({
correlation <- cor.test(dataset$Year, dataset$Percent, method = "pearson")
}, silent = TRUE)
for (i in 1:nrow(resultcor)) {
resultcor$Name[i] <- ??? #These ??? are not in the code, just highlighting Issue 1
resultcor$tvalue[i] <- correlation$dataset$statistic
resultcor$degreeF[i] <- correlation$dataset$parameter
resultcor$pvalue[i] <- correlation$dataset$p.value
resultcor$CIs[i] <- correlation$dataset$conf.int
resultcor$corcoeff[i] <- correlation$dataset$estimate
}
}
lapply(BigSplit, WorkFunc)
Any help would be appreciated, Thanks!

Answer 1

Consider using Map (variant to mapply) where you pass both the elements and names of BigSplit. Using Map will output a list of dataframes that you can then row bind at end with do.call(). Below assumes BigSplit is a named list.
WorkFunc <- function(dataset, dataname) {
# Correlation between Year and population Percent
tryCatch({
correlation <- cor.test(dataset$Year, dataset$Percent, method = "pearson")
CIs <- correlation$conf.int
return(data.frame(
Name = dataname,
tvalue = correlation$statistic,
degreeF = correlation$parameter,
pvalue = correlation$p.value,
CI_lower = ifelse(is.null(CIs), NA, CIs[[1]]),
CI_higher = ifelse(is.null(CIs), NA, CIs[[2]]),
corcoeff = correlation$estimate
)
)
}, error = function(e)
return(data.frame(
Name = character(0),
tvalue = numeric(0),
degreeF = numeric(0),
pvalue = numeric(0),
CI_lower = numeric(0),
CI_higher = numeric(0),
corcoeff = numeric(0)
)
)
)
}
# BUILD CORRELATION DATAFRAMES INTO LIST
cor_df_list <- Map(WorkFunc, BigSplit, names(BigSplit))
cor_df_list <- mapply(WorkFunc, BigSplit, names(BigSplit), SIMPLIFY=FALSE) # EQUIVALENT
# ROW BIND ALL DATAFRAMES TO FINAL LARGE DATAFRAME
finaldf <- do.call(rbind, cor_df_list)