在ggplot2

Question

我对for loop中的ggplot2感到困惑。

我正在尝试通过ggplot2中的for循环向每个绘图标题添加Species和categ名称以及文件名。不知何故，循环似乎只有一个物种名称标题。

library(dplyr)
data_iris <- iris%>%
  mutate(categ=ifelse(Petal.Width<0.4,"A",ifelse(Petal.Width>=0.4&Petal.Width<=1.0, "B","C")))

> head(data_iris)
  Sepal.Length Sepal.Width Petal.Length Petal.Width Species categ
1          5.1         3.5          1.4         0.2  setosa     A
2          4.9         3.0          1.4         0.2  setosa     A
3          4.7         3.2          1.3         0.2  setosa     A
4          4.6         3.1          1.5         0.2  setosa     A
5          5.0         3.6          1.4         0.2  setosa     A
6          5.4         3.9          1.7         0.4  setosa     B

PLOT PART

for (i in unique(data_iris$Species)) {

for (j in unique(data_iris$categ)) {

  p = ggplot(data_iris[data_iris$categ==j,], aes(x=Sepal.Length, y=Sepal.Width)) +
    geom_point(size=3, aes(colour=categ))+

    labs(title=paste( i,j, "species_categ",sep="_")) #this part is not working!!!

  plot_list[[j]] = p
}
}  

# Save plots to tiff. Makes a separate file for each plot.


library(ggplot2)

for (i in unique(data_iris$Species)) {

for (j in unique(data_iris$categ)) {
  file_name = paste(i,j, "iris_plot_", ".tiff", sep="_")
  tiff(file_name)
  print(plot_list[[j]])
  dev.off()
}
}

ant输出是这样的（我没有添加所有的图和名称。但是你会在工作目录中看到它们）

所以，正如我们可以看到问题在这里，我无法为每个情节获得正确的Species名称。我无法得到它？为什么会这样？

Answer 1

试试这个。 你的索引是错误的。我可能会首先以不同的方式存储图表 - 可能在列表列表中。

ind <- 1 # initialise the index for storing

for (i in unique(data_iris$Species)) {
  for (j in unique(data_iris$categ)) {

    p <- ggplot(data_iris[data_iris$categ==j,], aes(x=Sepal.Length, y=Sepal.Width)) +
      geom_point(size=3, aes(colour=categ))+

      labs(title=paste( i,j, "species_categ",sep="_")) 

    plot_list[[ind]] <- p  # stor the plot
    ind <- ind + 1         # increment   
  }
}  

ind <- 1
for (i in unique(data_iris$Species)) {
  for (j in unique(data_iris$categ)) {

    file_name = paste(i,j, "iris_plot_", ".tiff", sep="_")
    tiff(file_name)
    print(plot_list[[ind]]) # use the same index to retrieve the plot
    ind <- ind + 1
    dev.off()
  }
}

setosa_A_iris_plot__

setosa_B_iris_plot__

Answer 2

purrr::map, walk & iwalk框架中使用tidyverse的解决方案

library(tidyverse)

data_iris <- iris%>%
  as_tibble() %>% 
  mutate(categ = ifelse(Petal.Width < 0.4, "A",
                        ifelse(Petal.Width >= 0.4 & Petal.Width <= 1.0, "B", "C")))
data_iris

#> # A tibble: 150 x 6
#>    Sepal.Length Sepal.Width Petal.Length Petal.Width Species categ
#>           <dbl>       <dbl>        <dbl>       <dbl> <fct>   <chr>
#>  1          5.1         3.5          1.4         0.2 setosa  A    
#>  2          4.9         3            1.4         0.2 setosa  A    
#>  3          4.7         3.2          1.3         0.2 setosa  A    
#>  4          4.6         3.1          1.5         0.2 setosa  A    
#>  5          5           3.6          1.4         0.2 setosa  A    
#>  6          5.4         3.9          1.7         0.4 setosa  B    
#>  7          4.6         3.4          1.4         0.3 setosa  A    
#>  8          5           3.4          1.5         0.2 setosa  A    
#>  9          4.4         2.9          1.4         0.2 setosa  A    
#> 10          4.9         3.1          1.5         0.1 setosa  A    
#> # ... with 140 more rows

# Split based on species and categories
# Remove lists having 0 row
data_iris %>% 
  split(list(.$Species, .$categ)) %>% 
  discard(function(x) nrow(x) == 0) -> df_split

# For all species and categories
plots <- map(df_split,  
             ~ ggplot(.x, aes(x = Sepal.Length, y = Sepal.Width)) +
               geom_point(size = 3, aes(colour = categ))+
               theme_bw(base_size = 16) +
               labs(title = paste0("Species: ", .x$Species, " | Category: ", .x$categ)))

# Check the 1st plot
plots[[1]]

# Display all plots using purrr::walk
walk(plots, print) 

# Save all plots using purrr::iwalk
iwalk(plots,  
     ~ ggsave(plot = .x,
              filename = paste0("./img/", .y, ".tiff"))
     )

由reprex package（v0.2.0）创建于2018-05-16。

Answer 3

我想通过添加Species_categ列并在循环中运行它似乎不太复杂。

data_iris <- iris%>%
  mutate(categ=ifelse(Petal.Width<0.4,"A",ifelse(Petal.Width>=0.4&Petal.Width<=1.0, "B","C")))%>%
  unite(Species_categ,Species,categ,remove=F) #added this line

plot_list = list()

for (i in unique(data_iris$Species_categ)) {

  p = ggplot(data_iris[data_iris$Species_categ==i,], aes(x=Sepal.Length, y=Sepal.Width)) +
    geom_point(size=3, aes(colour=categ))+

    labs(title=paste( i, "species_categ",sep="_"))

  plot_list[[i]] = p
}


    # Save plots to tiff. Makes a separate file for each plot.
    for (i in unique(data_iris$Species_categ)) {

      file_name = paste(i, "iris_plot_2", ".tiff", sep="_")
      tiff(file_name)
      print(plot_list[[i]])
      dev.off()
    }