从ggplot中消除NAs [英] Eliminating NAs from a ggplot

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本文介绍了从ggplot中消除NAs的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

这里非常基本的问题在于我刚刚开始使用R,但我试图在ggplot2中创建一个因子计数的条形图,并在绘图时获取14个代表我实际水平的小彩色闪烁,然后显示一个巨大的灰色最后代表样本中的5000个新生样本(这是一个仅适用于样本约5%的问题的调查数据)。我试过以下代码无济于事:

  ggplot(data = MyData,aes(x = the_variable,fill = the_variable ,na.rm = TRUE))+ 
geom_bar(stat =bin)

此处添加的na.rm参数没有明显的效果。



同时

  ggplot(data = na.omit(MyData),aes(x = the_variable,fill = the_variable,na.rm = TRUE))+ 
geom_bar(stat =bin)

给我


错误:美学必须是长度为1或与数据长度相同的长度


与添加 na相同.omit()添加到the_variable,或MyData和the_variable。

所有我想要做的就是从我的图表中消除巨大的NA栏,有人可以帮我做这个吗?

ggplot2 中使用子集函数。试试这个

  library(ggplot2)

data(iris)
iris $ Sepal.Length [5:10]< - NA#为这个例子创建了一些NA

ggplot(data = subset(iris,!is.na(Sepal.Length)),aes(x = Sepal.Length))+
geom_bar(stat =bin)


Very basic question here as I'm just starting to use R, but I'm trying to create a bar plot of factor counts in ggplot2 and when plotting, get 14 little colored blips representing my actual levels and then a massive grey bar at the end representing the 5000-ish NAs in the sample (it's survey data from a question that only applies to about 5% of the sample). I've tried the following code to no avail:

ggplot(data = MyData,aes(x= the_variable, fill=the_variable, na.rm = TRUE)) + 
   geom_bar(stat="bin") 

The addition of the na.rm argument here has no apparent effect.

meanwhile

ggplot(data = na.omit(MyData),aes(x= the_variable, fill=the_variable, na.rm = TRUE)) + 
   geom_bar(stat="bin") 

gives me

"Error: Aesthetics must either be length one, or the same length as the data"

as does affixing the na.omit() to the_variable, or both MyData and the_variable.

All I want to do is eliminate the giant NA bar from my graph, can someone please help me do this?

解决方案

You can use the function subset inside ggplot2. Try this

library(ggplot2)

data("iris")
iris$Sepal.Length[5:10] <- NA # create some NAs for this example

ggplot(data=subset(iris, !is.na(Sepal.Length)), aes(x=Sepal.Length)) + 
geom_bar(stat="bin")

这篇关于从ggplot中消除NAs的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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