使用另一个数据框在数据框中缩放变量

Question

我有一个包含以下变量的数据框

dat <- data.frame(cell.ID = 1:10, cell.name = letters[1:10], 
              groupID = rep(1:2, each = 5), 
              x1 = rnorm(10), x2 = rnorm(10), 
              x3 = rnorm(10), x4= rnorm(10), 
              x5 = rnorm(10), x6 = rnorm(10))

我存储了一个平均值和 sd 以将另一个数据帧中的 x1 标准化为 x6

norm_fin <- data.frame(variable = paste0('x',1:6), 
                   meanVar = rnorm(6),
                   SdVar = rnorm(6))

我想在将 x1 规范化为 x6 之后从 dat 创建一个新的数据帧。我做了一个循环解决方案

 varVec <- paste0('x',1:6)
 dat1 <- dat
 for(i in varVec){
  meanRef <- norm_fin$meanVar[norm_fin$variable == i]
  sdRef <- norm_fin$SdVar[norm_fin$variable == i]
  dat1[, i] <- (dat[, i] - meanRef)/sdRef
}

有没有不使用循环的其他解决方案？

Answer 1

我们可以把数据转成长格式然后left join norm_find，计算出值然后取回宽格式的数据。

library(dplyr)
library(tidyr)

dat %>%
  pivot_longer(cols = starts_with('x')) %>%
  left_join(norm_fin, by = c('name' = 'variable')) %>%
  mutate(val = (value - meanVar)/SdVar) %>%
  select(-value, -meanVar, -SdVar) %>%
  pivot_wider(names_from = name, values_from = val)

# A tibble: 10 x 9
#   cell.ID cell.name groupID     x1      x2     x3    x4     x5      x6
#     <int> <fct>       <int>  <dbl>   <dbl>  <dbl> <dbl>  <dbl>   <dbl>
# 1       1 a               1 -2.10   32.6   -0.797 0.705 -0.768  0.0217
# 2       2 b               1 -1.36   16.3    0.125 0.353 -1.76   0.144 
# 3       3 c               1  2.63   17.0   -0.751 0.933  0.394  0.150 
# 4       4 d               1 -0.690  11.6   -0.429 0.925 -6.60  -0.461 
# 5       5 e               1 -0.559  -1.01  -0.316 0.898 -4.64   0.229 
# 6       6 f               2  2.98   43.2   -1.47  0.833  0.105 -0.525 
# 7       7 g               2  0.181  18.9    1.27  0.767 -1.36   0.802 
# 8       8 h               2 -3.67  -27.6    0.528 0.467 -1.23  -0.122 
# 9       9 i               2 -2.38   22.7   -0.873 0.348 -3.77   0.0778
#10      10 j               2 -1.84    0.557  1.72  0.311 -2.01   0.0379

数据

set.seed(123)
dat <- data.frame(cell.ID = 1:10, cell.name = letters[1:10], 
                  groupID = rep(1:2, each = 5), 
                  x1 = rnorm(10), x2 = rnorm(10), 
                  x3 = rnorm(10), x4= rnorm(10), 
                  x5 = rnorm(10), x6 = rnorm(10))

norm_fin <- data.frame(variable = paste0('x',1:6), 
                       meanVar = rnorm(6),
                       SdVar = rnorm(6))

使用另一个数据框在数据框中缩放变量

scale variables in dataframe using another dataframe

r

standardized