产生多重相关性”；“热图”；对于许多变量，使用for循环

我有一个包含127个变量的数据集：

cols <- c("Important", paste("var", 1:126, sep = ""))

。。。我看不懂，因为变量太多了。我试过不同的数字，有30多个变量难以辨认。所以我做了：

ggcorrplot(transac_shadow_cor[1:30, 1:30], lab = TRUE,
           outline.col = "white", ggtheme = ggplot2::theme_gray)
ggcorrplot(transac_shadow_cor[31:60, 31:60], lab = TRUE,
           outline.col = "white", ggtheme = ggplot2::theme_gray)

以此类推，生成5张清晰的热图。（1:30，31:60，61:90，91:120，121:127）

请求：我想为循环构建一个

for

来构建这些热图，但我不知道如何将所有变量的子集设置为30。如果再加上它，我可以在每个热图上都有第一个变量“重要”，那将是多么神奇，因为。。这很重要，但如果我不这么做也没什么大不了的

---

我没有连接到

ggcorrplot

，它只是我正在使用的一个。

这将是一个起点：

transac_shadow_cor
Size <- 30
Init <- 0
Iteration <- floor(dim(transac_shadow_cor)[1] / Size) #You have some remaining 
variables 
End <- Size

for (i in 1:Iteration){
  ggcorrplot(transac_shadow_cor[c(Init+1):End, c(Init+1):End], lab = TRUE,
         outline.col = "white", ggtheme = ggplot2::theme_gray)
  Inti <-  Init + Size
  End <- End + Size
}

transac\u shadow\u cor
尺寸回答我自己的问题，酷。
@奥兰多·萨博加尔差点就成功了。以下是我根据他的建议编写的代码：

Size <- 30
Init <- 0
Iteration <- floor(dim(transac_shadow_cor)[1] / Size) #You have some remaining 
End <- Size
heatmaps <- c()                   # this strores heatmaps for latter printing

for (i in 1:Iteration) {

  # Store each heatmap
  heatmaps[[i]] <- ggcorrplot(transac_shadow_cor[c(Init+1):End, c(Init+1):End], lab = TRUE,
                              outline.col = "white", ggtheme = ggplot2::theme_gray)

  # now print it
  plot(heatmaps[[i]])
  Init <-  Init + Size           # he had a typo here
  End <- End + Size
}

大小非常接近！，但有了你的回答，我自己设法找到了解决办法。谢谢
transac_shadow_cor
Size <- 30
Init <- 0
Iteration <- floor(dim(transac_shadow_cor)[1] / Size) #You have some remaining 
variables 
End <- Size

for (i in 1:Iteration){
  ggcorrplot(transac_shadow_cor[c(Init+1):End, c(Init+1):End], lab = TRUE,
         outline.col = "white", ggtheme = ggplot2::theme_gray)
  Inti <-  Init + Size
  End <- End + Size
}

Size <- 30
Init <- 0
Iteration <- floor(dim(transac_shadow_cor)[1] / Size) #You have some remaining 
End <- Size
heatmaps <- c()                   # this strores heatmaps for latter printing

for (i in 1:Iteration) {

  # Store each heatmap
  heatmaps[[i]] <- ggcorrplot(transac_shadow_cor[c(Init+1):End, c(Init+1):End], lab = TRUE,
                              outline.col = "white", ggtheme = ggplot2::theme_gray)

  # now print it
  plot(heatmaps[[i]])
  Init <-  Init + Size           # he had a typo here
  End <- End + Size
}

Size <- 30
Init <- 0
Iteration <- floor(dim(cormat)[1] / Size) #You have some remaining 
End <- Size
heatmaps <- c()                           # this strores heatmaps for latter printing
range <- c(1, seq(from = 2, to = End))    # the range of variables to appear on the heatmap

for (i in 1:Iteration) {

  # Store each heatmap
  heatmaps[[i]] <- ggcorrplot(cormat[range, range], lab = TRUE,
                              outline.col = "white", ggtheme = ggplot2::theme_gray)

  # now print it
  plot(heatmaps[[i]])

  # move the chains of the loop
  Init <-  Init + Size                         # he had a typo here
  End <- End + Size
  range <- c(1, seq(from = Init+1, to = End))  # increase range
}