r - 如何收集然后变异一个新列然后再次传播到宽格式

Question

使用 tidyr/dplyr，我有一些因子列，我想对其进行 Z 评分，然后对平均 Z 评分进行变异，同时保留原始数据以供引用。

我想避免在 tidyr/dplyr 中使用 for 循环，因此我正在收集数据并在单个列上执行计算(Z 分数)。但是，我正在努力恢复宽格式。

这是一个 MWE:

library(dplyr)
library(tidyr)

# Original Data
dfData <- data.frame(
  Name = c("Steve","Jwan","Ashley"),
  A = c(10,20,12),
  B = c(0.2,0.3,0.5)
) %>% tbl_df() 

# Gather to Z-score
dfLong <- dfData %>% gather("Factor","Value",A:B) %>% 
  mutate(FactorZ = paste0("Z_",Factor)) %>% 
  group_by(Factor) %>% 
  mutate(ValueZ = (Value - mean(Value,na.rm = TRUE))/sd(Value,na.rm = TRUE))

# Now go wide to do some mutations (eg Z)Avg = (Z_A + Z_B)/2)

# This does not work
dfWide <- dfLong %>% 
  spread(Factor,Value) %>%
  spread(FactorZ,ValueZ)%>% 
  mutate(Z_Avg = (Z_A+Z_B)/2)


# This is the desired result
dfDesired <- dfData %>% mutate(Z_A = (A - mean(A,na.rm = TRUE))/sd(A,na.rm = TRUE)) %>% mutate(Z_B = (B - mean(B,na.rm = TRUE))/sd(B,na.rm = TRUE)) %>% 
                    mutate(Z_Avg = (Z_A+Z_B)/2)

感谢您的帮助/输入!

Answer 1

另一种使用dplyr(版本 0.5.0)的方法

library(dplyr)

dfData  %>% 
   mutate_each(funs(Z = scale(.)), -Name) %>% 
   mutate(Z_Avg = (A_Z+B_Z)/2)