用ggplot2绘图:"分类y轴上的误差:提供给连续刻度的离散值"

Question

下面的绘图代码给出了 Error: Discrete value supplied to continuous scale

这段代码出了什么问题？它工作正常,直到我尝试更改比例,所以错误就在那里......我试图找出类似问题的解决方案,但不能.

这是head我的数据:

> dput(head(df))
structure(list(`10` = c(0, 0, 0, 0, 0, 0), `33.95` = c(0, 0, 
0, 0, 0, 0), `58.66` = c(0, 0, 0, 0, 0, 0), `84.42` = c(0, 0, 
0, 0, 0, 0), `110.21` = c(0, 0, 0, 0, 0, 0), `134.16` = c(0, 
0, 0, 0, 0, 0), `164.69` = c(0, 0, 0, 0, 0, 0), `199.1` = c(0, 
0, 0, 0, 0, 0), `234.35` = c(0, 0, 0, 0, 0, 0), `257.19` = c(0, 
0, 0, 0, 0, 0), `361.84` = c(0, 0, 0, 0, 0, 0), `432.74` = c(0, 
0, 0, 0, 0, 0), `506.34` = c(1, 0, 0, 0, 0, 0), `581.46` = c(0, 
0, 0, 0, 0, 0), `651.71` = c(0, 0, 0, 0, 0, 0), `732.59` = c(0, 
0, 0, 0, 0, 1), `817.56` = c(0, 0, 0, 1, 0, 0), `896.24` = c(0, 
0, 0, 0, 0, 0), `971.77` = c(0, 1, 1, 1, 0, 1), `1038.91` = c(0, 
0, 0, 0, 0, 0), MW = c(3.9, 6.4, 7.4, 8.1, 9, 9.4)), .Names = c("10", 
"33.95", "58.66", "84.42", "110.21", "134.16", "164.69", "199.1", 
"234.35", "257.19", "361.84", "432.74", "506.34", "581.46", "651.71", 
"732.59", "817.56", "896.24", "971.77", "1038.91", "MW"), row.names = c("Merc", 
"Peug", "Fera", "Fiat", "Opel", "Volv"
), class = "data.frame")

绘图代码:

## Plotting
meltDF = melt(df, id.vars = 'MW')
ggplot(meltDF[meltDF$value == 1,]) + geom_point(aes(x = MW, y = variable)) +
  scale_x_continuous(limits=c(0, 1200), breaks=c(0, 400, 800, 1200)) +
  scale_y_continuous(limits=c(0, 1200), breaks=c(0, 400, 800, 1200))

这是在添加比例之前情节的样子:

Answer 1

正如评论中所提到的,对于类型的变量,不能有连续的比例factor.你可以改变factor到numeric如下,你定义刚过meltDF变量.

meltDF$variable=as.numeric(levels(meltDF$variable))[meltDF$variable]

然后,执行ggplot命令

  ggplot(meltDF[meltDF$value == 1,]) + geom_point(aes(x = MW, y =   variable)) +
     scale_x_continuous(limits=c(0, 1200), breaks=c(0, 400, 800, 1200)) +
     scale_y_continuous(limits=c(0, 1200), breaks=c(0, 400, 800, 1200))

你会得到你的图表.

希望这可以帮助

Answer 2

就我而言，您需要将列（您认为该列是数字的，但实际上不是）转换为numeric

geom_segment(data=tmpp, 
   aes(x=start_pos, 
   y=lib.complexity, 
   xend=end_pos, 
   yend=lib.complexity)
)
# to 
geom_segment(data=tmpp, 
   aes(x=as.numeric(start_pos), 
   y=as.numeric(lib.complexity), 
   xend=as.numeric(end_pos), 
   yend=as.numeric(lib.complexity))
)

Answer 3

如果x是数字，则添加scale_x_continuous(); 如果x是字符/因素，则添加scale_x_discrete()。这可能会解决您的问题。