R：平均列并有条件地排除NA数据[重复]答案

【问题标题】：R: Averaging columns and conditionally excluding NA data [duplicate]R：平均列并有条件地排除NA数据[重复]
【发布时间】：2017-06-21 19:28:34
【问题描述】：

但是，我正在尝试跨列进行平均，因为某些列缺少数据，平均结果也为 NA。有没有办法在从计算中排除任何 NA 数据的同时找到多列的平均值？

目前我使用的代码是：

### Calculate Bins ###
 {pulse<-transmute(pulse, Question, Type, Student,Bin1=(Rt1+ Rt2 + Rt3+ Rt4)/4 , Bin2= (Rt5+Rt6+Rt7+Rt8)/4 , Bin3= (Rt9+Rt10+Rt11)/3)
 }

但是，我认为这不是最好的方法。我的目标是使用 Rt1-Rt4、Rt5-Rt8 和 Rt9-Rt11 的方式创建三列。即是这样的：

 Question  Type Student  Bin1  Bin2     Bin3
1        Q   SNR  789331  4.25  4.00 4.666667
2       Q2   SNR  789331  3.75  2.50 3.000000
3       Q8   SNR  789331  4.00  2.50 3.333333
4      Q10   SNR  789331  4.00  2.75 3.333333
5      Q12   SNR  789331  3.50  3.25 3.666667

任何帮助将不胜感激！

我的数据附在下面：

> dput(pulse)
structure(list(Question = c("Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12", "Q", 
"Q2", "Q8", "Q10", "Q12", "Q", "Q2", "Q8", "Q10", "Q12"), Type = c("SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", "SNR", 
"SNR", "SNR", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", "FYS", 
"FYS", "FYS", "FYS", "FYS", "FYS", "FYS"), Student = c("789331", 
"789331", "789331", "789331", "789331", "805933", "805933", "805933", 
"805933", "805933", "826523", "826523", "826523", "826523", "826523", 
"832929", "832929", "832929", "832929", "832929", "838607", "838607", 
"838607", "838607", "838607", "841903", "841903", "841903", "841903", 
"841903", "843618", "843618", "843618", "843618", "843618", "852125", 
"852125", "852125", "852125", "852125", "876406", "876406", "876406", 
"876406", "876406", "879972", "879972", "879972", "879972", "879972", 
"885650", "885650", "885650", "885650", "885650", "888712", "888712", 
"888712", "888712", "888712", "903303", "903303", "903303", "903303", 
"903303", "796882", "796882", "796882", "796882", "796882", "827911", 
"827911", "827911", "827911", "827911", "830271", "830271", "830271", 
"830271", "830271", "831487", "831487", "831487", "831487", "831487", 
"834598", "834598", "834598", "834598", "834598", "836364", "836364", 
"836364", "836364", "836364", "839802", "839802", "839802", "839802", 
"839802", "855524", "855524", "855524", "855524", "855524", "873527", 
"873527", "873527", "873527", "873527", "885409", "885409", "885409", 
"885409", "885409", "894218", "894218", "894218", "894218", "894218", 
"928026", "928026", "928026", "928026", "928026", "932196", "932196", 
"932196", "932196", "932196", "955389", "955389", "955389", "955389", 
"955389", "956952", "956952", "956952", "956952", "956952", "957206", 
"957206", "957206", "957206", "957206", "957759", "957759", "957759", 
"957759", "957759", "959200", "959200", "959200", "959200", "959200", 
"962490", "962490", "962490", "962490", "962490", "968728", "968728", 
"968728", "968728", "968728", "969005", "969005", "969005", "969005", 
"969005", "971179", "971179", "971179", "971179", "971179", "976863", 
"976863", "976863", "976863", "976863", "981621", "981621", "981621", 
"981621", "981621", "952797", "952797", "952797", "952797", "952797", 
"965873", "965873", "965873", "965873", "965873", "967416", "967416", 
"967416", "967416", "967416", "975424", "975424", "975424", "975424", 
"975424"), Rt1 = c(4, 3, 4, 4, 3, 5, 4, 5, 5, 5, 4, 4, 4, 5, 
5, 4, 4, 4, 4, 3, 5, 5, 5, 5, 5, 2, 3, 4, 3, 4, 4, 5, 5, 4, 4, 
3, 3, 3, 4, 3, 3, 3, 4, 4, 4, 3, 4, 5, 4, 3, 4, 4, 4, 3, 5, 4, 
4, 4, 5, 5, 3, 4, 4, 4, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, 4, 5, 3, 4, 4, 4, 3, 3, 5, 4, 4, 2, 2, 3, 4, NA, NA, 
NA, NA, NA, 3, 4, 4, 4, 3, NA, NA, NA, NA, NA, 5, 4, 5, 4, 4, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, 4, 3, 3, 4, 1, 3, 
4, 5, 4, 4, 4, 5, 4, 4, NA, NA, NA, NA, NA), Rt2 = c(4, 4, 4, 
4, 3, 4, 4, 4, 4, 4, 3, 4, 4, 5, 5, 4, 4, 4, 4, 3, 5, 5, 5, 5, 
5, 4, 4, 4, 4, 5, 4, 4, 5, 5, 4, NA, NA, NA, NA, NA, 4, 4, 4, 
4, 4, 3, 4, 4, 5, 3, 4, 4, 4, 5, 5, 4, 4, 4, 4, 4, 1, 5, 5, 5, 
3, 3, 5, 5, 5, 4, 5, 4, 3, 4, 5, 4, 5, 5, 5, 4, 4, 5, 4, 5, 4, 
5, 5, 5, 5, 5, 4, 4, 4, 4, 4, 3, 4, 3, 4, 3, 5, 5, 5, 5, 5, 3, 
5, 4, 4, 3, 4, 5, 5, 5, 5, 4, 4, 4, 5, 5, 4, 5, 5, 5, 4, 4, 2, 
2, 4, 4, 5, 5, 5, 5, 5, 3, 4, 4, 5, 5, 5, 5, 3, 5, 4, 5, 4, 4, 
5, 4, 5, 2, 3, 4, 3, 4, 3, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 3, 4, 
3, 5, 5, 5, 5, 4, 5, 5, 5, 3, 4, 4, 5, 5, 5, 5, NA, NA, NA, NA, 
NA, NA, 4, 5, 5, 5, NA, NA, NA, NA, NA, 4, 4, 4, 4, 4), Rt3 = c(4, 
4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 4, 4, 5, 5, 4, 4, 4, 4, 3, 5, 5, 
5, 5, 5, 4, 5, 4, 4, 4, 5, 4, 5, 5, 4, 4, 4, 4, 4, 3, 4, 3, 4, 
5, 5, 3, 4, 4, 4, 4, 3, 4, 4, 4, 5, NA, NA, NA, NA, NA, 3, 5, 
5, 5, 5, 3, 4, 5, 5, 3, 4, 3, 3, 4, 4, 4, 5, 5, 5, 5, 4, 5, 4, 
4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 1, 3, 1, 4, 1, 4, 5, 5, 5, 
4, 4, 4, 4, 4, 3, 4, 5, 5, 5, 4, 4, 5, 5, 4, 4, 5, 5, 5, 4, 5, 
NA, NA, NA, NA, NA, 4, 4, 5, 5, 5, NA, NA, NA, NA, NA, 5, 4, 
4, 4, 3, 5, 4, 4, 5, 4, NA, NA, NA, NA, NA, 5, 4, 3, 5, 4, 3, 
4, 4, 4, 3, 5, 5, 4, 4, 5, 5, 4, 4, 5, 4, NA, 5, 5, 5, 5, 5, 
4, 4, 5, 5, NA, NA, NA, NA, NA, 5, 5, 5, 5, 5, 5, 5, 4, 3, 4, 
3, 4, 3, 3, 4), Rt4 = c(5, 4, 4, 4, 4, 4, 4, 3, 4, 3, 4, 4, 4, 
5, 5, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, NA, NA, NA, NA, NA, 5, 4, 
4, 4, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, NA, NA, NA, NA, NA, 4, 
4, 4, 3, 5, 4, 4, 4, 4, 5, 3, 4, 4, 4, 5, 3, 4, 5, 5, 3, NA, 
NA, NA, NA, NA, 5, 5, 5, 5, 5, 5, 5, 4, 4, 5, 4, 4, 4, 4, 4, 
4, 4, 4, 4, 4, 1, 1, 2, 3, 2, 4, 5, 5, 5, 4, 4, 4, 4, 4, 5, 4, 
5, 5, 5, 5, 5, 5, 4, 4, 5, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
5, 4, 4, 5, 4, NA, NA, NA, NA, NA, 4, 4, 5, 4, 4, 4, 3, 3, 4, 
3, 5, 4, 4, 4, 5, NA, NA, NA, NA, NA, 5, 4, 3, 3, 4, NA, NA, 
NA, NA, NA, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA), Rt5 = c(3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 4, 
5, 4, 5, 5, 2, 4, 4, 4, 4, 5, 5, 5, 5, 5, 4, 4, 4, 3, 3, 5, 4, 
4, 4, 5, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 3, 4, 4, 4, 5, 
4, 4, 4, 4, 5, 4, 5, NA, NA, NA, NA, NA, 3, 2, 4, 4, 1, 3, 2, 
3, 5, 4, 5, 5, 5, 5, 5, 4, 5, 4, 5, 4, 4, 4, 4, 4, 5, 3, 4, 3, 
4, 4, 5, 4, 3, 4, 5, 4, 4, 5, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 4, 
4, 5, 5, 5, 5, 5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 4, 
3, 3, 5, 5, NA, NA, NA, NA, NA, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 
4, 2, 2, 4, 4, 5, 4, 4, 4, 4, 3, 3, 4, 4, 3, NA, NA, NA, NA, 
NA, 5, 5, 4, 4, 4, NA, NA, NA, NA, NA, 5, 5, 5, 5, 5, 5, 4, 4, 
4, 5, 4, 4, 4, 4, 4, 4, 4, 5, 4, 4, NA, NA, NA, NA, NA), Rt6 = c(4, 
2, 2, 1, 3, 4, 3, 3, 3, 3, 4, 5, 5, 4, 5, NA, NA, NA, NA, NA, 
5, 4, 4, 4, 5, NA, NA, NA, NA, NA, 5, 4, 4, 4, 5, 3, 3, 4, 4, 
4, 4, 3, 2, 1, 2, 4, 4, 4, 5, 4, 4, 5, 4, 3, 4, 4, 5, 5, 4, 4, 
3, 4, 4, 3, 3, 5, 3, 2, 3, 5, 4, 3, 3, 4, 3, 5, 4, 4, 4, 5, NA, 
NA, NA, NA, NA, 4, 4, 4, 4, 4, 3, 4, 3, 3, 3, 2, 2, 3, 2, 2, 
4, 4, 5, 4, 5, NA, NA, NA, NA, NA, 4, 5, 5, 4, 4, 5, 5, 5, 5, 
5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
3, 2, 4, 3, 4, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 3, 3, 3, 2, 4, 4, 
5, 4, 5, 5, 3, 3, 3, 3, 3, NA, NA, NA, NA, NA, NA, 5, 4, 4, 4, 
NA, NA, NA, NA, NA, 5, 3, 4, 4, 5, 4, 3, 4, 4, 3, 4, 4, 4, 3, 
4, 4, 4, 5, 4, 5, NA, NA, NA, NA, NA), Rt7 = c(5, 2, 2, 3, 3, 
4, 3, 3, 3, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, 4, 
4, 4, 4, 4, 4, 3, 4, 5, 5, 4, 4, 4, 5, 3, 4, 3, 4, 4, 4, 3, 2, 
2, 3, 4, 4, 4, 4, 4, 5, 5, 4, 4, 4, 5, 4, 5, 4, 5, 3, 4, 4, 4, 
4, 4, 3, 1, 1, 5, NA, NA, NA, NA, NA, 5, 5, 4, 5, 5, 4, 5, 4, 
4, 4, 4, 4, 4, 4, 4, 3, 4, 3, 4, 4, 3, 3, 3, 3, 3, 5, 5, 5, 5, 
4, 4, 4, 4, 4, 5, 4, 5, 5, 3, 4, 5, 5, 5, 5, 5, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, 3, 5, 5, 4, 5, 5, 5, 3, 4, 5, 4, 4, 4, 
4, 4, 4, 3, 3, 3, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
1, 1, 1, 1, 1, 5, 4, 4, 4, 5, 5, 4, 4, 4, 4, 4, 3, 3, 4, 4, 5, 
3, 4, 3, 4, 4, 4, 4, 4, 4, 3, 1, 1, 1, 1, 5, 5, 5, 4, 4, 3, 2, 
2, 3, 4), Rt8 = c(4, 3, 3, 3, 3, 4, 3, 3, 3, 3, 5, 5, 5, 4, 4, 
NA, NA, NA, NA, NA, 5, 4, 4, 5, 4, 3, 4, 3, 3, 4, 5, 4, 4, 3, 
5, 4, 4, 4, 4, 4, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4, 5, 4, 4, 3, 5, 
4, 4, 4, 3, 4, 3, 4, 4, 3, 4, 1, 1, 1, 1, 3, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, 5, 5, 4, 4, 5, NA, NA, NA, NA, NA, 3, 
4, 3, 4, 4, 4, 4, 4, 4, 5, 4, 4, 4, 4, 4, 4, 5, 4, 4, 5, 5, 5, 
4, 3, 5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, 3, 5, 5, 5, 5, 4, 4, 4, 5, 4, 5, 5, 4, 4, 3, 4, 3, 3, 
3, 3, 4, 4, 4, 4, 4, 4, 4, 2, 4, 4, 3, 3, 3, 3, 3, 5, 5, 4, 4, 
5, 5, 5, 4, 5, 5, 4, 3, 3, 4, 4, 5, 5, 5, 3, 3, 5, 4, 4, 4, 4, 
3, 2, 2, 2, 2, 5, 5, 5, 5, 5, NA, NA, NA, NA, NA), Rt9 = c(4, 
3, 3, 3, 3, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, 4, 3, 4, 4, 4, 4, 4, 4, 4, 5, 4, 3, 3, 4, 4, NA, NA, 
NA, NA, NA, 3, 3, 3, 2, 4, 4, 4, 4, 4, 4, 5, 4, 4, 3, 3, 5, 4, 
4, 4, 4, 3, 4, 4, 4, 4, 3, 1, 1, 1, 5, NA, NA, NA, NA, NA, 5, 
5, 5, 5, 5, 5, 5, 5, 4, 5, NA, NA, NA, NA, NA, 3, 4, 3, 3, 4, 
3, 3, 3, 2, 3, 5, 5, 5, 5, 5, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, 4, 5, 5, 4, 4, NA, NA, NA, NA, NA, 5, 4, 3, 4, 4, 4, 3, 3, 
3, 2, NA, NA, NA, NA, NA, 1, 1, 1, 1, 1, 2, 3, 4, 4, 2, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, 4, 1, 1, 1, 1, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA), Rt10 = c(5, 3, 3, 3, 4, NA, NA, NA, NA, 
NA, 5, 4, 4, 4, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 5, 4, 4, 3, 4, 4, 3, 3, 3, 4, 4, 3, 2, 3, 4, 
4, 4, 4, 4, 4, 5, 5, 4, 3, 3, 5, 4, 4, 3, 4, 3, 4, 4, 4, 3, 3, 
1, 1, 1, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, 5, 4, 
3, 5, 4, 4, 4, 4, 4, 3, 4, 3, 3, 4, 1, 1, 2, 2, 3, 4, 5, 4, 4, 
4, 4, 4, 4, 3, 4, 4, 4, 4, 2, 5, 4, 4, 4, 3, 5, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, 4, 4, 4, 4, 4, 
4, 3, 4, 4, 4, 4, 5, 4, 4, 4, 4, 4, 4, 5, 4, 2, 2, 4, 4, 1, 1, 
3, 1, 2, 5, 5, 4, 4, 5, NA, NA, NA, NA, NA, 4, 5, 3, 4, 4, 5, 
5, 5, 5, 5, 4, 4, 4, 4, 4, 5, 3, 3, 2, 4, NA, NA, NA, NA, NA, 
3, 4, 3, 4, 4), Rt11 = c(5, 3, 4, 4, 4, 4, 3, 3, 3, 3, 4, 4, 
4, 4, 5, NA, NA, NA, NA, NA, 4, 4, 3, 3, 4, 3, 5, 5, 5, 5, 5, 
4, 4, 4, 5, 3, 5, 5, 5, 5, 4, 4, 4, 4, 5, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, 5, 5, 5, 4, 4, 4, 5, 5, 4, 5, 5, 3, 4, 5, 
4, NA, NA, NA, NA, NA, 5, 5, 5, 5, 5, 5, 5, 4, 4, 5, 4, 4, 4, 
4, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 4, 4, 5, 4, 5, 4, 4, 
5, 4, 4, 4, 3, 3, 5, 5, 5, 5, 5, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 5, 4, 4, 
4, 5, 5, 4, 5, 5, 4, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
1, 1, 1, 2, 3, 5, 5, 4, 4, 5, 5, 5, 5, 5, 5, NA, NA, NA, NA, 
NA, 5, 5, 5, 5, 5, 4, 4, 4, 4, 4, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA)), .Names = c("Question", "Type", 
"Student", "Rt1", "Rt2", "Rt3", "Rt4", "Rt5", "Rt6", "Rt7", "Rt8", 
"Rt9", "Rt10", "Rt11"), row.names = c(NA, -205L), class = c("tbl_df", 
"tbl", "data.frame"))

【问题讨论】：

请添加您正在使用的任何软件包的名称。 transmute 不是基本 R 函数。
见?mean。您需要 na.rm=T 对于示例中的列 Rt1：mean(pulse$Rt1, na.rm=T)
@SRivero 谢谢！这有帮助，但我试图对每个学生的列进行平均（即我想要 Rt1、RT2 和 Rt3 的平均值）。有没有办法做到这一点？
是的，rowMeans
Bin1 = rowMeans(pulse[,4:7], na.rm = TRUE); Bin2 = rowMeans(pulse[,8:11], na.rm = TRUE); Bin3 = rowMeans(pulse[,12:14], na.rm = TRUE)

标签： r

【解决方案1】：

生成行的平均值：

dataframe <- pulse[(number_of_rows_you_are_interested_in),]   
rowMeans(dataframe, na.rm = TRUE)

【讨论】：

谢谢！但是有没有办法应用它，以便平均列 Rt1-Rt4、Rt5-Rt8 和 Rt9-Rt11 以创建三个新的平均列？我是一个完整的 R 初学者，因此可能需要额外的解释，我将不胜感激！ :)
@Bailey 如果您想平均来自不同列的行并将结果保存在新列中，请使用来自dplyr 包的mutate。 pulse %>% mutate(new_column1 = mean(c(Rt1:Rt4)), new_column2 = mean(c(Rt5:Rt8)), new_column3 = mean(c(Rt9:Rt11))) 使用列号而不是列名。
你甚至不需要 dplyr。请点击此链接stackoverflow.com/questions/9490485/…

【解决方案2】：

Rt1[!is.na(Rt1)]

以上代码通过排除 Rt1 中的所有 NA 条目返回缩减的数据帧

您可以在列中使用此表达式

【讨论】：

【解决方案3】：

我发现 complete.cases() 对于只为您提供没有 NA 的行特别有用

pulse <- pulse[complete.cases(pulse), ]

然后你应该能够计算这个数据帧

另外，不必手动计算平均值，而是遵循 link 的示例（这与您开始的问题非常相似）

【讨论】：