使用历史数据 [前期] 创建新变量

Question

我想创建两个考虑先前历史记录的列[t-1] 以创建新列来指定当前期间重复或执行的新活动和旧活动的数量[数据见下文structure]。例如第 5 行，算法应该将 'think' 的新事件与之前的 [read, write] 事件进行比较，因为 t-1 中没有之前的 'think'，它被列为 1 [for new] 期间 3 [第 5 行] 没有使用旧事件，因此它是 0。

event<- c('read', 'write', 'read', 'write', 'think', 'read', 'think', 'read')
person<- c('arun', 'arun','arun','arun','arun','john','john', 'john')
time <-  c(1, 1,2,2,3,1,2,3)
df<- data.frame(event, person,time)

    event person time  new  old

    read   arun    1    .    .
    write  arun    1    .    .
    read   arun    2    0    2
    write  arun    2    0    2
    think  arun    3    1    0
    read   john    1    .    .
    think  john    2    1    0
    read   john    3    1    0

关于如何实现这一点有什么建议吗？

Answer 1

event<- c('read', 'write', 'read', 'write', 'think', 'read', 'think', 'read')
person<- c('arun', 'arun','arun','arun','arun','john','john', 'john')
time <-  c(1, 1,2,2,3,1,2,3)
df<- data.frame(event, person,time)

library(tidyverse, warn.conflicts = FALSE)

df %>% 
  group_by(person, time) %>%
  summarise(new = list(event), .groups = 'drop') %>%
  group_by(person) %>%
  mutate(old = map2_int(new, lag(new), ~ sum(.x %in% .y)),
         new = map_int(new, length) - old) %>%
  mutate(across(new:old, ~ifelse(time == 1, NA, .))) %>%
  left_join( df, ., by = c('person', 'time'))

#>   event person time new old
#> 1  read   arun    1  NA  NA
#> 2 write   arun    1  NA  NA
#> 3  read   arun    2   0   2
#> 4 write   arun    2   0   2
#> 5 think   arun    3   1   0
#> 6  read   john    1  NA  NA
#> 7 think   john    2   1   0
#> 8  read   john    3   1   0

^{由 reprex package (v2.0.0)}

创建于 2021-07-21

使用历史数据 [前期] 创建新变量

using historical data [prior period] to create new variable

r

dplyr

tidyr