无效因子水平，NA生成R

Sample of the data I am working with below. I already omitted all rows with a "NA" in them.

我正在处理的数据样本如下。我已经省略了所有包含“NA”的行。

gss.s[1:5,]
      abany          advfront   arrest
2      YES             Agree       NO
3      YES    Strongly agree       YES
10     YES             Agree       YES
16     YES             Agree       NO
21      NO    Strongly agree       NO

I am trying to replace the "YES" with a 1 in the abany column and "NO" with -1 in abany column. I tried using replace replace(gss.s[,1], "YES", 1) but got the error Invalid Factor Level, NA generated. I read a previous post about this same problem and couldn't figure out how to apply the solution to my problem.

我正在尝试用abany列中的1替换“是”，用abany列中的-1替换“否”。我尝试使用替换(gss)。s[，1]，“是”，1)但得到错误无效因子水平，NA生成。我之前读过一篇关于这个问题的文章，但是我不知道如何将这个解决方案应用到我的问题上。

3 个解决方案

#1

You could use ifelse() on the column, changing all values at once.

您可以在列上使用ifelse()，同时更改所有值。

gss.s$abany <- ifelse(gss.s$abany == "YES", 1, -1)
gss.s
##    abany       advfront arrest
## 2      1          Agree     NO
## 3      1 Strongly agree    YES
## 10     1          Agree    YES
## 16     1          Agree     NO
## 21    -1 Strongly agree     NO

#2

y <- data.frame ("abany"=c("YES","YES","YES","YES","NO"), 
            "advfront"=c("Agree","Strongly Agree","Agree","Agree","Strongly Agree"),
            "arrest"=c("NO","YES","YES","NO","NO"))

I would try another way: Convert factor column to character

我可以尝试另一种方法:将因子列转换为字符

y$abany <- as.character.factor (y$abany)

So now you don't have any problem to change values of the column

所以现在你没有任何问题来改变列的值。

y[y$abany=="YES", "abany"] <- 1
y[y$abany=="NO", "abany"] <- -1

#3

You can also create a vector in which you define the changes you would like to make. It is a lot quicker if you have big datasets compared to ifelse statements.

您还可以创建一个向量，在其中定义您想要进行的更改。与ifelse语句相比，如果您有大型数据集，那么速度会快得多。

translate <- c(YES=1,NO=-1)
gss.s$abany2 <- translate[as.character(gss.s$abany)] 
gss.s

#   abany       advfront arrest abany2
# 1   YES          Agree     NO      1
# 2   YES Strongly agree    YES      1
# 3   YES          Agree    YES      1
# 4   YES          Agree     NO      1
# 5    NO Strongly agree     NO     -1

You also don't have to struggle with nested ifelse functions if you have multiple changes to make:

如果要做多个更改，您也不必为嵌套的ifelse函数而烦恼:

translate2 <- c('Strongly agree'=2,Agree=1,Disagree=-1,'Strongly disagree'=-2 )
gss.s$advfront2 <- translate2[as.character(gss.s$advfront)]
gss.s

#   abany       advfront arrest abany2 advfront2
# 1   YES          Agree     NO      1         1
# 2   YES Strongly agree    YES      1         2
# 3   YES          Agree    YES      1         1
# 4   YES          Agree     NO      1         1
# 5    NO Strongly agree     NO     -1         2

#1