带有for循环的数据摘要

我试图使用包

Rmisc

中的

summarySE

函数为工作簿中的每一列生成数据摘要。工作表中的第一列是分组变量，我想循环其他列。 我正在使用以下代码：

library(Rmisc)
for(i in 2:ncol(file)){
    sum<-summarySE(file, measurevar = file[,i], groupvars = file[1])
}

我知道

文件[1]

是一个

列表

，应该是一个

向量

，但是使用

取消列表会导致更多问题。有什么想法吗

数据：

我们需要一个
data.frame
来应用
summarySE
。使用
lappy
，循环列序列，将“文件”子集，指定
measurevar
和
groupvars
（基于列索引）

或者如果我们使用OP的方法

lst <- vector("list", ncol(file)-1)
for(i in 2:ncol(file)){
   lst[[i]] <- summarySE(file, measurevar = i, groupvars = 1)
}

lst


在OP的代码中，
measurevar
和
groupvars
采用列的值，而不是列名

structure(list(Treatment = c("SKELE", "SKELE", "SKELE", "SKELE", 
"SKELE", "SKELE", "SKELE", "SKELE", "SKELE", "SKELE", "SKELE", 
"SKELE", "TISSUE", "TISSUE", "TISSUE", "TISSUE", "TISSUE", "TISSUE", 
"TISSUE", "TISSUE", "TISSUE", "TISSUE", "TISSUE", "TISSUE"), 
`% lipid in skeleton` = c(21.8706902567934, 31.1736436075643, 
62.2246234617322, 86.6248675033794, 46.5607971373041, 34.7532319115317, 
32.7686161366371, 6.73685660233744, 33.7111477556584, 48.8970450055359, 
54.3687328279357, 48.9086732773318, 78.1293097432066, 68.8263563924357, 
37.7753765382678, 13.3751324966206, 53.4392028626959, 65.2467680884683, 
67.2313838633629, 93.2631433976626, 66.2888522443416, 51.1029549944641, 
45.6312671720643, 51.0913267226682), `% ash in skeleton` = c(97.370981485225, 
98.6169174273543, 99.2417548180554, 99.1330769035889, 98.5523872323069, 
98.0077944962001, 97.7848485294277, 98.0738823145836, 98.1567971208113, 
98.8047064451889, 97.1790753033603, 98.7503991978965, 2.62901851477497, 
1.38308257264571, 0.75824518194458, 0.866923096411125, 1.44761276769314, 
1.99220550379987, 2.2151514705723, 1.92611768541643, 1.84320287918869, 
1.19529355481109, 2.82092469663973, 1.24960080210352), `% tissue in skeleton` = c(55.2224357342865, 
70.022864703591, 77.5880978578982, 83.1168129092154, 67.3012504898307, 
62.1455896726595, 64.2488985210074, 67.3089347382539, 59.9276126303114, 
70.5681668501146, 67.717146912379, 68.8185249866557, 44.7775642657135, 
29.977135296409, 22.4119021421018, 16.8831870907846, 32.6987495101694, 
37.8544103273405, 35.7511014789926, 32.6910652617461, 40.0723873696886, 
29.4318331498854, 32.2828530876211, 31.1814750133443)), class = "data.frame", row.names = c(NA, 
-24L), .Names = c("Treatment", "% lipid in skeleton", "% ash in skeleton", 
"% tissue in skeleton"))

lapply(2:ncol(file), function(j) summarySE(file[c(1, j)], measurevar = 2, groupvars = 1))
#[[1]]
#  Treatment  N        2       sd       se       ci
#1     SKELE 12 42.38324 20.53836 5.928913 13.04945
#2    TISSUE 12 57.61676 20.53836 5.928913 13.04945

#[[2]]
#  Treatment  N         2        sd        se        ci
#1     SKELE 12 98.306052 0.6567242 0.1895799 0.4172626
#2    TISSUE 12  1.693948 0.6567242 0.1895799 0.4172626

#[[3]]
#  Treatment  N        2       sd       se       ci
#1     SKELE 12 67.83219 7.442443 2.148448 4.728703
#2    TISSUE 12 32.16781 7.442443 2.148448 4.728703

lst <- vector("list", ncol(file)-1)
for(i in 2:ncol(file)){
   lst[[i]] <- summarySE(file, measurevar = i, groupvars = 1)
}

lst

for(i in 2:ncol(file)){
 lst[[i]] <- summarySE(file, measurevar = names(file)[i], groupvars = names(file)[1])
 }