创建具有多行均值的新数据框

Question

我有一个由三列组成的数据帧: ID、试验和差异度量(diff_DT)。我有19个参与者，每个人都完成了30次试验。下面是我的数据帧的样子：

    ID     Trial     diff_DT
    01      005       37,5
    01      006       40,5
    01      007       16,5
    ...     ...       ...
    02      005       16,5 
    ...     ...       ...
    02      016       27,9

30个试验中始终有6个属于一个区块:区块1:试验5-10，区块2:试验16-21，区块3:试验26-31，区块4:试验36-41，区块5:试验46-51 (注:试验数量> 30，因为参与者总共完成了更多试验)

现在，我需要每个块的每个参与者的变量diff_DT的平均值，结果是每个参与者的五个平均值。我不知道该怎么做才好。谢谢你的建议！

Answer 1

您可以为块/试验创建单独的关键数据帧或矩阵，将其合并到原始表中，然后运行聚合以获得平均分数。

 ID <- c(rep(1, 3), 2, 2)
 Trial <- c(5, 6, 7, 5, 16)
 diff_DT <- c(37.5, 40.5, 16.5, 16.5, 27.9)
 Trial.key <- c(5:10, 16:21, 26:31, 36:41, 46:51)
 block <- rep(1:5, each = 6)

 df <- data.frame(ID, Trial, diff_DT)
 blocks <- data.frame(Trial.key, block)

 df.blocks <- merge(df, blocks, by.x = "Trial", by.y = "Trial.key", all.x = TRUE,
                    all.y = FALSE)
 df.blocks
#  Trial ID diff_DT block
#     5  1    37.5     1
#     5  2    16.5     1
#     6  1    40.5     1
#     7  1    16.5     1
#    16  2    27.9     2

 df.agg <- with(df.blocks, aggregate(diff_DT, by = list(ID, Trial), 
                                     FUN = "mean"))
 names(df.agg) <- c("ID", "Trial", "mean.diff_DT")
 df.agg
#  ID Trial mean.diff_DT
#  1     5         37.5
#  2     5         16.5
#  1     6         40.5
#  1     7         16.5
#  2    16         27.9

Answer 2

看看这对你有没有帮助。

bd <- data.frame(ID = rep(1:6, each = 30),
             Trial = c(sample(c(5:10,16:21,26:31,36:41,46:51), 30), 
                       sample(c(5:10,16:21,26:31,36:41,46:51), 30),
                       sample(c(5:10,16:21,26:31,36:41,46:51), 30), 
                       sample(c(5:10,16:21,26:31,36:41,46:51), 30),
                       sample(c(5:10,16:21,26:31,36:41,46:51), 30), 
                       sample(c(5:10,16:21,26:31,36:41,46:51), 30)),
             diff_DT = rnorm(n = 180, mean = 30, sd = 2))

library(dplyr)
bd <- bd %>% 
  mutate(block = ifelse(Trial <= 10, 1, 
                    ifelse(Trial <= 21, 2, 
                           ifelse(Trial <= 31, 3,
                                  ifelse(Trial <= 41, 4, 5)))))
bd %>% 
group_by(ID, block) %>% 
summarise(Mean = mean(diff_DT))

Answer 3

如果只想使用基数R，一种方法是在数据帧中创建一个列block，然后对每个块中的每个参与者应用mean函数。如果试验是数字的(考虑到您的试验是001,002，情况可能不是这样)，您可以

df$block = ifelse(df$trial>=5 & df$trial <=10, 1, 
              ifelse(df$trial>=16 & df$trial <=21,2,
              ifelse(df$trial>=26 & df$trial <=31,3,
              ifelse(df$trial>=36 & df$trial <=41,4,
              ifelse(df$trial>=46 & df$trial <=51,5,0))))
           )

如果试验不是数字(例如，字符或因子)，则应首先使用

df$trial = as.numeric(as.character(df$trial))

然后你只需要

aggregate(df$trial, by=list(df$block,df$id), mean)