用“空”排列条形图的条形图在R中以降序排列 [英] Arranging bars of a bar plot with "null" in Descending order in R

问题描述

我想用降序条创建一个条形图，在下面的图中，由于NA出现在a1向量中的第二个点上，它在创建图时最后被推送。但是，我希望NA栏仅出现在第二个位置，请在这里帮助我，因为我希望在不修改数据的情况下实现此目的。

 < code $ library 
 
 
 $ b a1 = c（A，NA，B，C，D，F ）
 b1 = c（165,154,134,110,94,78）
 a12 = data.frame（a1，b1，stringsAsFactors = FALSE）
 pp1 < -  ggplot（a12，aes（x = reorder（a1，-b1），y = b1，text = paste（用户：
< br>，a1，< br>天数：< br>，round（b1）） ）+ 
 geom_bar（stat =identity，fill =＃3399ff）+ 
 scale_y_continuous（name =Time）+ 
 scale_x_discrete（name =Employee）
 ggplotly（pp1，tooltip =text，height = 392）
  

解决方案

在评论中，你认为硬编码一个值来取代 NA 是不好的做法。我会说，通过索引位置进行硬编码是一个坏主意，但会自动用字符串替换 NA ，如 null


在下面的例子中，我添加的唯一东西是 a12 $ a1 [is.na（a1 ）]< - null。这一行检测 a12 $ a1 中的 NA ，并用 null替换它。基于 b1 中的数字的 reorder 会稍后发生，因此这种方法并不要求您知道 NA 事前

  library（ggplot2）
 library（plotly） 
 $ b a1 = c（A，NA，B，C，D，F）
 b1 = c（165,154,134,110,94,78）
 a12 = data.frame（a1，b1，stringsAsFactors = FALSE）
 
＃将NA替换为null
 a12 $ a1 [is.na（a1）]< - null
 
 pp1 < -  ggplot（a12，aes（x = reorder（a1，-b1），y = b1，text = paste（User：
< br> ;，a1，< br>天数：< br>，round（b1））））+ 
 geom_bar（stat =identity，fill =＃3399ff）+ 
 scale_y_continuous（name =Time）+ 
 scale_x_discrete（name =Employee）
 ggplotly（pp1，tooltip =text，height = 392）
  

I want to create a bar plot with Descending bars, In the plot below, due to NA being present at 2nd spot in "a1" vector, it is pushed at the last when the plot is created. However, I want the NA bar to be present at the 2nd spot only, kindly help me here as I want to achieve this without modifying my data.

library(ggplot2)
library(plotly)

a1 = c("A",NA,"B","C","D","F")
b1 = c(165,154,134,110,94,78)
a12 = data.frame(a1,b1,stringsAsFactors = FALSE)
pp1 <<- ggplot(a12 , aes(x = reorder(a1,-b1), y = b1,text=paste("User: 
<br>",a1, "<br> Days: <br>", round(b1)))) + 
geom_bar(stat = "identity", fill = "#3399ff" ) + 
    scale_y_continuous(name = "Time") + 
    scale_x_discrete(name ="Employee") 
ggplotly(pp1, tooltip="text",height = 392)

解决方案

In the comments, you argued that hard-coded a value to replace NA is a bad practice. I would say that hard-coded by index position is a bad idea, but automatically replace NA with a character string, such as null, is a good idea.

In the following example, the only thing I added is a12$a1[is.na(a1)] <- "null". This line detects where is NA in a12$a1 and replace it with null. The reorder based on numbers in b1 will happend later, so this approach does not require you to know the index of NA beforehand

library(ggplot2)
library(plotly)

a1 = c("A",NA,"B","C","D","F")
b1 = c(165,154,134,110,94,78)
a12 = data.frame(a1,b1,stringsAsFactors = FALSE)

# Replace the NA to be "null"
a12$a1[is.na(a1)] <- "null"

pp1 <- ggplot(a12 , aes(x = reorder(a1, -b1), y = b1,text=paste("User: 
<br>",a1, "<br> Days: <br>", round(b1)))) + 
  geom_bar(stat = "identity", fill = "#3399ff" ) + 
  scale_y_continuous(name ="Time") + 
  scale_x_discrete(name ="Employee") 
ggplotly(pp1, tooltip="text",height = 392)

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