R：平均化してNAデータを条件付きで除外します

-2

しかし、列の中にはデータが欠落しているために平均化しようとしています。計算からNAデータを除外して多数の列の平均を見つける方法はありますか？R：平均化してNAデータを条件付きで除外します

私がこれまで使用してきたコードは次のとおりです。

### 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) 
}

しかし、私はこれが最善のway.Myのゴールだとは思わないRt1を-RT4、RT5の手段を3つの列を持つことです-Rt8およびRt9-Rt11である。つまり、次のようなものです：

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

助けていただければ幸いです。

> 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"))

出典

2017-06-21 Bailey

使用しているパッケージの名前を追加してください。 'transmute'は基底R関数ではありません。 – lmo

'？mean'を参照してください。 'na.rm = T'が必要ですあなたの例の列Rt1については、' mean（pulse $ Rt1、na.rm = T） ' –

@SRivero ありがとう！これは役に立ちますが、各学生の平均的な列（つまり、私はRt1、RT2、Rt3の平均値が必要です）を平均化しようとしています。それを行う方法はありますか？ – Bailey

行の平均生成する：

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

出典

2017-06-21 19:36:26 Piotr

ありがとう！しかし、これを適用して列Rt1〜Rt4、Rt5〜Rt8、Rt9〜Rt11を平均して3つの新しい平均列を作成する方法がありますか？私は完全なRの初心者ですので、追加の説明が必要になるかもしれないし、間違いなく感謝します！ :) – Bailey

@Bailey異なる列の行を平均化し、新しい列に結果を保存する場合は、 'dplyr'パッケージから' mutate'を使用します。 new_column2 =平均（c（Rt5：Rt8））、new_column3 =平均（c（Rt9：Rt11））） '列％の代わりに列番号を使用する名前。 – Piotr

あなたはdplyrも必要ありません。このリンクに従ってくださいhttps://stackoverflow.com/questions/9490485/how-can-i-get-the-average-mean-of-selected-columns – sweetmusicality

Rt1[!is.na(Rt1)]

上記のコードは

Rt1を内のすべてのNAエントリを除外することによって縮小データフレームを返す

私のデータを以下に取り付けられています。

この式は、列全体で使用できます

私はあなたに何のNA

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

、その後、あなたの代わりに手動ですることの、また、このデータフレームの上に

を計算することができるはずがない行を与えるに特に有用であることがcomplete.cases()を見つけた

出典

2017-06-21 19:37:07

平均を計算すると、linkの例に従います（これはあなたの質問に似ています）

出典

2017-06-21 19:52:08 sweetmusicality

R：平均化してNAデータを条件付きで除外します

答えて

関連する問題