我有三个不同的data.frame对象。这些data.frame对象称为Experiment1，Experiment2，Experiment3 ... Experiment {n}（其中n是NumberTubes除以NumberParameters）。
Experiment1：
Name Statistic NoCells
1 CD4 subset 41.2 11935
2 CD4 subset/CD39 subset 30.6 3656
3 CD4 subset/CD69 subset 4.93 588
4 CD4 subset/CD73 subset 49.8 5946
5 CD4 subset/CD103 subset 2.62 313
6 CD4 subset/integrin B7 subset 4.37 521
7 CD8a subset 33.5 9697
8 CD8a subset/CD39 subset 54.3 5270
9 CD8a subset/CD69 subset 5.48 531
10 CD8a subset/CD73 subset 73.7 7148
11 CD8a subset/CD103 subset 4.06 394
Experiment2：
Name Statistic NoCells
1 CD4 subset 31.1 11935
2 CD4 subset/CD39 subset 24.6 3656
3 CD4 subset/CD69 subset 9.91 588
4 CD4 subset/CD73 subset 45.1 5946
5 CD4 subset/CD103 subset 2.61 313
6 CD4 subset/integrin B7 subset 4.34 521
7 CD8a subset 33.2 9697
8 CD8a subset/CD39 subset 84.3 5270
9 CD8a subset/CD69 subset 2.48 531
10 CD8a subset/CD73 subset 70.7 7148
11 CD8a subset/CD103 subset 4.01 394
现在我想从每个data.frame对象合并表中的。$ Statistic列。每个表的列数应由NumberRepeats变量定义。
例如，假设NumberRepeats = 3：
tab_1 <- cbind(Experiment1, Experiment2$Statistic, Experiment3$Statistic)
tab_2 <- cbind(Experiment4, Experiment5$Statistic, Experiment6$Statistic)
....
tab_x <- cbind(Experimentn-2, Experimentn-1$Statistic, Experimentn$Statistic)
另一个例子，假设NumberRepeats = 4：
tab_1 <- cbind(Experiment1, Experiment2$Statistic, Experiment3$Statistic, Experiment4$Statistic)
tab_2 <- cbind(Experiment5, Experiment6$Statistic, Experiment7$Statistic, Experiment8$Statistic)
....
tab_x <- cbind(Experimentn-3, Experimentn-2$Statistic, Experimentn-1$Statistic, Experimentn$Statistic)
如何实现这一目标？该脚本应该提供与上述cbind相同的输出，但是基于NumberRepeats和n（NumberTubes除以NumberParameters）的值自动生成。
ExperimentalDesign：
parameter repeat1 repeat2 repeat3
1 but 10.0 4.0 3.00
2 hip 4.0 3.0 2.00
3 H2S 0.2 0.1 0.05
4 pro 4.0 3.0 1.00
5 ace 5.0 4.0 3.00
来自循环的所需table_1：
name exp1 exp2 exp3 parameter
1 CD4 subset 41.2 31.1 ... but
2 CD4 subset/CD39 subset 30.6 24.6 ... but
答案 0 :(得分：1)
使用此功能，您可以将不同数据框对象的列合并到一个表中。您可以通过NumberRepeats变量控制列数。存储在列表中的所有表都具有相同数量的数据列，如
除了最后一个表格之外的NumberRepeats变量...顺便说一句，构建这样的结构很有趣我不确定这是否是分析数据的好方法。
# created test data
for(i in 1:17){
Name <- letters[1:7]
Statistic <- round(rnorm(7), 3)
assign(paste0("Experiment",i), data.frame(Name, Statistic))
}
# set some parameters
NumberRepeats <- 5
Experiment_n <- 17
skipTube <- c(3,7,11)
＃let go
out <- list()
list_index <- 1
counter <- 1
while(counter < Experiment_n) {
tab <- NULL
nam <- NULL
while((is.null(tab) || ncol(tab) < NumberRepeats) & Experiment_n >= counter){
if(!any(counter == skipTube)){
tab <- cbind(tab, get(paste0("Experiment", counter))$Statistic)
# tab <- as.data.frame(tab)
nam <- c(nam,paste0("Experiment", counter))
}
counter <- counter + 1
}
colnames(tab) <- nam
rownames(tab) <- as.matrix(Experiment1$Name)
out[[list_index]] <- tab
assign(paste0('table_', list_index), tab)
list_index <- list_index + 1
}
out
# get a idea for the results
p_dat <- sapply(out, function(x) rowMeans(x))
barplot(t(p_dat), beside=T)
答案 1 :(得分：1)
# created test data
for(i in 1:17){
Name <- letters[1:7]
Statistic <- round(rnorm(7), 3)
assign(paste0("Experiment",i), data.frame(Name, Statistic))
}
# create the other data
dat2 <- c(10.0, 4.0, 3.00,
4.0, 3.0, 2.00,
0.2, 0.1, 0.05,
4.0, 3.0, 1.00,
5.0, 4.0, 3.00)
dat2 <- matrix(dat2, byrow=T, ncol=3 )
colnames(dat2) <- c('conc1', 'conc2', 'conc3')
rownames(dat2) <- c('but', 'hip', 'H2S', 'pro', 'ace')
# set some parameters
NumberRepeats <- 3
Experiment_n <- 17
skipTube <- c(3,7,11)
# lets go
out <- list()
list_index <- 1
counter <- 1
while(counter < Experiment_n) {
tab <- NULL
nam <- NULL
while((is.null(tab) || ncol(tab) < NumberRepeats) & Experiment_n >= counter){
if(!any(counter == skipTube)){
tab <- cbind(tab, get(paste0("Experiment", counter))$Statistic)
tab <- as.data.frame(tab)
nam <- c(nam,paste0("repeat", counter))
}
counter <- counter + 1
}
nam[1:3] <- dat2[list_index,]
colnames(tab) <- nam
rownames(tab) <- as.matrix(Experiment1$Name)
parameter <- rownames(dat2)[list_index]
tab <- cbind(tab, parameter)
out[[list_index]] <- tab
assign(paste0('table_', list_index), tab)
list_index <- list_index + 1
}
table_1
table_2
table_3
p_dat <- sapply(out, function(x) rowMeans(x))
barplot(t(p_dat), beside=T)
答案 2 :(得分：0)
你可以使用循环来做到这一点。
library(tidyverse)
library(data.table)
# make a list from all Experiment tables
df_list <- lapply(ls(pattern = 'Experiment'), get)
tables_index <- seq_len(length(ls(pattern = 'Experiment')))
# set NumberRepeats value
NumberRepeats <- 1
# create index for cbind function
subset_index <- rep(seq_len(length(ls(pattern = 'Experiment'))/NumberRepeats), each = NumberRepeats, length.out = length(ls(pattern = 'Experiment')))
# loops for binding needed columns
experiment_list = list()
for (i in (1:(length(ls(pattern = 'Experiment'))/NumberRepeats))) {
indices <- tables_index[subset_index == i]
experiment_df <- data.frame(df_list[indices[1]])
for (j in indices[-1]) {
experiment_df <- cbind(experiment_df, df_list[[j]]['wt'])
}
experiment_list[[i]] <- experiment_df
}
# show result
experiment_list
对我来说，使用和聚合类似列的最佳方法是将一个data.frame中的所有表联合起来，然后按不同的参数进行分组。