subtract value from previous row by group

In R, let's say I have this data frame:

Data
id		date		value
2380	10/30/12	21.01
2380	10/31/12	22.04
2380	11/1/12		22.65
2380	11/2/12		23.11
20100	10/30/12	35.21
20100	10/31/12	37.07
20100	11/1/12		38.17
20100	11/2/12		38.97
20103	10/30/12	57.98
20103	10/31/12	60.83 

And I want to subtract the previous value from the current value, by group ID date, to create this:

id		date		value	diff
2380	10/30/12	21.01	0
2380	10/31/12	22.04	1.03
2380	11/1/12		22.65	0.61
2380	11/2/12		23.11	0.46
20100	10/30/12	35.21	0
20100	10/31/12	37.07	1.86
20100	11/1/12		38.17	1.1
20100	11/2/12		38.97	0.8
20103	10/30/12	57.98	0
20103	10/31/12	60.83	2.85

With dplyr:

library(dplyr)

data %>%
    group_by(id) %>%
    arrange(date) %>%
    mutate(diff = value - lag(value, default = first(value)))

For clarity you can arrange by date and grouping column (as per comment by lawyer)

data %>%
    group_by(id) %>%
    arrange(date, .by_group = TRUE) %>%
    mutate(diff = value - lag(value, default = first(value)))

or lag with order_by:

data %>%
    group_by(id) %>%
    mutate(diff = value - lag(value, default = first(value), order_by = date))

With data.table:

library(data.table)

dt <- as.data.table(data)
setkey(dt, id, date)
dt[, diff := value - shift(value, fill = first(value)), by = id]

You can do this with the ave function:

data$diff <- ave(data$value, data$id, FUN=function(x) c(0, diff(x)))
data
#       id                date value diff
# 1   2380 2012-10-30 00:15:51 21.01 0.00
# 2   2380 2012-10-31 00:31:03 22.04 1.03
# 3   2380 2012-11-01 00:16:02 22.65 0.61
# 4   2380 2012-11-02 00:15:32 23.11 0.46
# 5  20100 2012-10-30 00:15:38 35.21 0.00
# 6  20100 2012-10-31 00:15:48 37.07 1.86
# 7  20100 2012-11-01 00:15:49 38.17 1.10
# 8  20100 2012-11-02 00:15:19 38.97 0.80
# 9  20103 2012-10-30 10:27:34 57.98 0.00
# 10 20103 2012-10-31 12:24:42 60.83 2.85

The first argument is the data to be operated on, the second argument is the group, and the last argument is the function to be applied to the data from each group.

Awesome answers! Just wanted to add that if you want to make your data consecutively to work with the code above you can do that with order, e.g.:

data <- data[with{data, order(id, date)), ]
data$diff <- ave(data$value, data$id, FUN=function(x) c(0, diff(x)))

See: https://stackoverflow.com/questions/67383811/calculate-difference-between-values-in-rows-by-two-grouping-variables