在两个以上数据框内的相同变量的嵌套列表内循环相关性测试 [英] Looping correlation tests within nested lists on same variables across more than two dataframes

问题描述

在嵌套列表中考虑以下三个数据框:

Consider these three dataframes in a nested list:

df1 <- data.frame(a = runif(10,1,10), b = runif(10,1,10), c = runif(10,1,10))

df2 <- data.frame(a = runif(10,1,10), b = runif(10,1,10), c = runif(10,1,10))

df3 <- data.frame(a = runif(10,1,10), b = runif(10,1,10), c = runif(10,1,10))
dflist1 <- list(df1,df2,df3)
dflist2 <- list(df1,df2,df3)
nest_list <- list(dflist1, dflist2)

我想对每个dflist的所有'dfs'中的列'a'相对于列'a'，'b'相对于'b'和'c'相对于'c'进行'cor.test'.我可以分别使用

I want to do a 'cor.test' between column 'a' against column 'a', 'b' against 'b' and 'c' against 'c' in all 'dfs' for each dflist. I can do it individually if assign each one to the global environment with the code below thanks to this post:

 for (i in 1:length(nest_list)) { # extract dataframes from list in to individual dfs
    for(j in 1:length(dflist1)) {

  temp_df <- Norm_red_list[[i]][[j]]}

ds <- paste (names(nest_list[i]),names(nestlist[[i]][[j]]), sep = "_")

assign(ds,temp_df)

  }
 }

combn(paste0("df", 1:3), 2, FUN = function(x) { #a ctual cor.test
      x1 <- mget(x, envir = .GlobalEnv)
     Map(function(x,y) cor.test(x,y, method = "spearman")$p.value, x1[[1]], x1[[2]])})

推荐答案

我不确定我是否完全了解您想要做什么，但是这样可以帮助您吗?

I am not sure that I understand exactly what you want to do but could something like this help you ?

    #vector of your columns name
    columns <- c("a","b","c")
    n <- length(columns)
    # correlation calculation function
    correl <- function(i,j,data) {cor.test(unlist(data[i]),unlist(data[j]), method = "spearman")$p.value}
    correlfun <- Vectorize(correl, vectorize.args=list("i","j"))
    # Make a "loop" on columns vector (u will then be each value in columns vector, "a" then "b" then "c")
    res <- sapply(columns,function(u){
        # Create another loop on frames that respect the condition names(x)==u (only the data stored in columns "a", "b" or "c")
        lapply(lapply(nest_list,function(x){sapply(x,function(x){x[which(names(x)==u)]})}),function(z)
   # on those data, use the function outer to apply correlfun function on each pair of vectors
{outer(1:n,1:n,correlfun,data=z)})},simplify = FALSE,USE.NAMES = TRUE)

这有帮助吗?不确定我的解释是否很清楚:)

Is this helping ? Not sure I'm really clear in my explanation :)

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