我有一个包含许多因素的数据框,想要创建统计表来显示每个因素的分布,包括观察值为零的因素水平。例如,这些数据:
structure(list(engag11 = structure(c(5L, 4L, 4L), .Label = c("Strongly Disagree", "Disagree", "Neither A or D", "Agree", "Strongly Agree"), class = "factor"), encor11 = structure(c(1L, 1L, 1L), .Label = c("Agree", "Neither Agree or Disagree", "Strongly Agree"), class = "factor"), know11 = structure(c(3L,
1L, 1L), .Label = c("Agree", "Neither Agree or Disagree", "Strongly Agree"), class = "factor")), .Names = c("engag11", "encor11", "know11"), row.names = c(NA, 3L), class = "data.frame")
显示 6 行,但每列仅观察到部分因子水平。当我生成表格时,我不仅想显示观察到的级别的计数,还想显示未观察到的级别的计数(例如“强烈不同意”)。像这样:
# define the factor and levels
library(dplyr);library(pander);library(forcats)
eLevels<-factor(c(1,2,3,4,5), levels=1:5, labels=c("Strongly Disagree","Disagree","Neither A or D","Agree","Strongly Agree"),ordered =TRUE )
# apply the factor to one variable
csc2$engag11<-factor(csc2$engag11,eLevels)
t1<-table(csc2$engag11)
pander(t1)
这会产生一个频率表,显示每个级别的计数,包括未报告/观察到的级别的零。
但是我有几十个变量需要转换。 Stackoverflow 上推荐的一个简单的 lapply
函数似乎不起作用,例如这个:
csc2[1:3]<-lapply(csc[1:3],eLevels)
我还为此尝试了一个简单的函数(n=列列表),但失败了:
facConv<-function(df,n)
{ df$n<-factor(c(1,2,3,4,5), levels=1:5, labels=c("Strongly
Disagree","Disagree","Neither A or D","Agree","Strongly Agree") )
return(result) }
有人可以提供解决方案吗?
最佳答案
lapply
应该可以正常工作,您只需要指定 factor()
函数即可:
csc2[1:3] <- lapply(csc2[1:3], function(x) factor(x, eLevels))
然后你可以像这样调用表:
table(csc2[1])
#Strongly Disagree Disagree Neither A or D Agree Strongly Agree
# 0 0 0 2 1
table(csc2[2])
#Strongly Disagree Disagree Neither A or D Agree Strongly Agree
# 0 0 0 3 0
关于r - 将因子水平应用于缺少因子水平的多个列,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/48196217/