[英]Mean of categorical variables from plyr package
My categorical variable, risk has three groups in it of: ADV, HHM and POV我的分类变量,风险包含三组:ADV、HHM 和 POV
I want get the mean these three groups for four continuous variables read.5
, read.6
, read.7
and read.8
which are reading scores of individuals over grades 5 to 8我想得到这三个组的四个连续变量read.5
、 read.6
、 read.7
和read.8
的平均值,它们是 5 到 8 年级个人的阅读分数
which is the ,2:5
of my dataset and it's an old textbook example.这是我数据集的,2:5
,它是一个旧的教科书示例。 I used the code below which is not correct apparently even though it is supposed to be correct according to the texbook example:我使用了下面的代码,尽管根据 texbook 示例它应该是正确的,但它显然是不正确的:
myrisk <- ddply(.data = MPLS[ ,2:5], .variables = .(MPLS$risk),
.fun = mean, na.rm = TRUE)
I had an error message for a piece of code earlier on of:我之前收到了一段代码的错误消息:
mymeans <- mean(MPLS[ ,2:5], na.rm = TRUE)
which when I googled it, the R software had changed and I had to find another to work out the means.当我用谷歌搜索它时,R 软件已经改变,我必须找到另一个来解决方法。
My questions are:我的问题是:
Is the ddply function which I am trying to use currently, from the plyr package been superseded in the same way that the old mean function has?我目前正在尝试使用的 ddply function 从 plyr package 是否以与旧平均值 ZC1C425268E68385D14AB5074C17A9 相同的方式被取代?
How do I get the mean of a categorical variable from the four columns?如何从四列中获取分类变量的平均值? Whether with the same function or with something different?是否使用相同的 function 或不同的东西?
Thank you谢谢
df<-data.frame(risk= rep(c("ADV","HHM","POV"),10),
read.5= rnorm(30,30),
read.4= rnorm(30,30),
read.3= rnorm(30,30),
read.2= rnorm(30,30))
> head(df)
# risk read.5 read.4 read.3 read.2
#1 ADV 30.78281 30.00721 29.80906 29.25936
#2 HHM 29.76175 29.63864 29.39256 29.40070
#3 POV 29.00964 30.48258 29.20662 28.77509
#4 ADV 29.60631 30.35032 32.00376 30.70374
#5 HHM 31.38653 30.28896 29.48756 30.32430
#6 POV 30.33102 30.40897 29.55796 30.10585
library(dplyr)
df %>% group_by(risk) %>% summarise_all(mean)
# A tibble: 3 x 5
# risk read.5 read.4 read.3 read.2
# <fct> <dbl> <dbl> <dbl> <dbl>
1 ADV 30.3 30.2 30.2 30.4
2 HHM 29.7 30.5 29.8 29.9
3 POV 29.3 30.2 29.9 30.2
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