I have a dataset that I am playing with and learning about in R. I am attempting to accomplish a visualization where there are multiple models of a particular item with several sub categories of data for each item that I need to display. Each model has the same subcategories of data, I.E. Model A has Spec1, Spec2, Spec3, Spec4, and Spec5. I want to list out ModelA, ModelB, ModelC, and show their respective data values above each model. I have pivoted the table of data from one row listing the model and each subcategory, to each row displaying a different sub cateory of data, where you may see the model several times. I am not sure if that is how I need to wrangle the data to begin with, but I found a tutorial showing a similar visualization that worked for them, but it didnt work for me. I am somewhat stuck, and I am looking for advice on how to accomplish this quickly and effectively, as I am new to R. I am not sure I am asking the right questions or attempting to wrangle correctly in the first place. Thanks for any advice

我有一个数据集，我正在R中操作和学习。我正在尝试完成一个可视化，其中有一个特定项目的多个模型，每个项目都有几个子类别的数据，我需要显示。每个模型都具有相同的数据子类别，即模型A具有spec1、spec2、spec3、spec4和spec5。我想列出ModelA、ModelB、ModelC，并在每个模型上显示它们各自的数据值。我已经将数据表从列出模型和每个子类别的一行，旋转到每一行显示不同的数据子目录，在那里您可能会多次看到模型。我不确定一开始我是否需要这样处理数据，但我找到了一个教程，它展示了一个类似的可视化方法，对他们有效，但对我不起作用。我有些手足无措，我正在寻求关于如何快速有效地完成这项工作的建议，因为我刚接触R。我不确定我问的问题是正确的，还是试图在一开始就正确地争论。谢谢你的建议

I tried the following code

我尝试了以下代码

barchart <- ggplot()
barchart <- barchart +
  geom_col(
    ata = dataset,
    aes(x = dataCategories, y = dataNumbers, ),
    position = "dodge"
  )
barchart

I also tried this

我也试过这个

barchart <- ggplot()
barchart <- barchart +
  geom_col(
    main.cat = c("productName"),
    second.cat = c("subcat1", "subcat2", "subcat3", "supcat4", "subcat5"),
    value = c("dataNumbers")
  )

Something like this? Note that the test data is in the long format.

像这样的吗？请注意，测试数据是长格式的。

suppressPackageStartupMessages({
  library(ggplot2)
  library(dplyr)
})

df1 %>%
  mutate(
    productName = factor(productName, levels = productName %>% unique()),
    subcat = sub("[[:alpha:]]+", "", subcat)
  ) %>%
  group_by(productName) %>%
  mutate(Group = interaction(subcat, productName, sep = "&")) %>% 
  ggplot(aes(Group, dataNumbers, group = subcat)) +
  geom_col(position = position_dodge(), fill = "steelblue") +
  labs(x = "Model", y = "Data Numbers") +
  guides(x = ggh4x::guide_axis_nested(delim = "&")) +
  theme_bw()

^{Created on 2023-09-10 with reprex v2.0.2}

创建于2023-09-10，Reprex v2.0.2

Test data

set.seed(2023)
Model <- sprintf("Model%s", LETTERS[1:3])
subcat <- sprintf("Spec%d", 1:5)
df1 <- expand.grid(subcat, Model)[2:1]
names(df1) <- c("productName", "subcat")
df1$dataNumbers <- sample(10:20, nrow(df1), TRUE)
df1
#>    productName subcat dataNumbers
#> 1       ModelA  Spec1          14
#> 2       ModelA  Spec2          18
#> 3       ModelA  Spec3          17
#> 4       ModelA  Spec4          12
#> 5       ModelA  Spec5          19
#> 6       ModelB  Spec1          11
#> 7       ModelB  Spec2          10
#> 8       ModelB  Spec3          10
#> 9       ModelB  Spec4          10
#> 10      ModelB  Spec5          10
#> 11      ModelC  Spec1          14
#> 12      ModelC  Spec2          17
#> 13      ModelC  Spec3          11
#> 14      ModelC  Spec4          12
#> 15      ModelC  Spec5          13

^{Created on 2023-09-10 with reprex v2.0.2}

创建于2023-09-10，Reprex v2.0.2