按组计算连续行中的值之间的差异

Question

这是我的df(data.frame):

group value
1     10
1     20
1     25
2     5
2     10
2     15 

我需要按组计算连续行中值之间的差异.

所以,我需要一个结果.

group value diff
1     10    NA # because there is a no previous value
1     20    10 # value[2] - value[1]
1     25    5  # value[3] value[2]
2     5     NA # because group is changed
2     10    5  # value[5] - value[4]
2     15    5  # value[6] - value[5]

虽然,我可以通过使用来处理这个问题ddply,但需要花费太多时间.这是因为我的团队中有很多团体df.(我的超过1,000,000个团体df)

有没有其他有效的方法来处理这个问题？

Answer 1

该软件包data.table可以使用该shift功能相当快速地完成此操作.

require(data.table)
df <- data.table(group = rep(c(1, 2), each = 3), value = c(10,20,25,5,10,15))
#setDT(df) #if df is already a data frame

df[ , diff := value - shift(value), by = group]    
#   group value diff
#1:     1    10   NA
#2:     1    20   10
#3:     1    25    5
#4:     2     5   NA
#5:     2    10    5
#6:     2    15    5
setDF(df) #if you want to convert back to old data.frame syntax

或者使用中的lag功能dplyr

df %>%
    group_by(group) %>%
    mutate(Diff = value - lag(value))
#   group value  Diff
#   <int> <int> <int>
# 1     1    10    NA
# 2     1    20    10
# 3     1    25     5
# 4     2     5    NA
# 5     2    10     5
# 6     2    15     5

有关前期data.table::shift和前期的替代方案dplyr::lag,请参阅编辑.

Answer 2

您可以使用基本功能,ave()此

df <- data.frame(group=rep(c(1,2),each=3),value=c(10,20,25,5,10,15))
df$diff <- ave(df$value, factor(df$group), FUN=function(x) c(NA,diff(x)))

返回

  group value diff
1     1    10   NA
2     1    20   10
3     1    25    5
4     2     5   NA
5     2    10    5
6     2    15    5