如何只选择在这两种测量中可用的观测？

Question

我有一个数据集，它包含时间、t1和t2的树度量。这些树是根据州、县、地块和树数来识别的。有些树木已经死亡，有些在t1和t2之间的时间间隔内生长。

State   County   Plot    Tree     Meas_yr
1       9        1       1        t1 
1       9        1       2        t1
1       9        1       3        t1
1       9        1       1        t2
1       9        1       2        t2
1       9        1       4        t2
1       9        1       5        t2    

我正试图将这些树、新生长的树木与t1和t2中的树木以及在t2中死去的树木分开。我正在尝试创建如下所示的东西。

State   County   Plot    Tree     Meas_yr  tree_survival
1       9        1       1        t1       1
1       9        1       2        t1       1
1       9        1       3        t1       0
1       9        1       1        t2       1
1       9        1       2        t2       1

我真的很感谢你的帮助。提前谢谢。

Answer 1

你可以试试这个-

library(dplyr)

df %>%
  group_by(State, County, Plot, Tree) %>%
  dplyr::filter(n() > 1 | Meas_yr == "t1") %>%
  mutate(tree_survival = as.integer(n() > 1)) %>%
  ungroup()

#   State County  Plot  Tree Meas_yr tree_survival
#  <int>  <int> <int> <int> <chr>           <int>
#1     1      9     1     1 t1                  1
#2     1      9     1     2 t1                  1
#3     1      9     1     3 t1                  0
#4     1      9     1     1 t2                  1
#5     1      9     1     2 t2                  1

这将保留"t1“年的所有行以及这两个年份中都存在的树。如果树同时存在于年份或0中，则为tree_survival分配1。

数据

df <- structure(list(State = c(1L, 1L, 1L, 1L, 1L, 1L, 1L), County = c(9L, 
9L, 9L, 9L, 9L, 9L, 9L), Plot = c(1L, 1L, 1L, 1L, 1L, 1L, 1L), 
    Tree = c(1L, 2L, 3L, 1L, 2L, 4L, 5L), Meas_yr = c("t1", "t1", 
    "t1", "t2", "t2", "t2", "t2")), class = "data.frame", row.names = c(NA, -7L))

Answer 2

library(tidyverse)

data <- tribble(
~State,   ~County,   ~Plot,    ~Tree,     ~Meas_yr,
1,       9,        1,       1,        't1', 
1,       9,        1,       2,        't1',
1,       9,        1,       3,        't1',
1,       9,        1,       1,        't2',
1,       9,        1,       2,        't2',
1,       9,        1,       4,        't2',
1,       9,        1,       5,        't2'  
)

new_df <- data %>%
    group_by(Tree) %>%
    mutate(tree_survival = n() - 1) %>%
    ungroup() %>%
    filter(!(Meas_yr == 't2' & tree_survival == 0))

## A tibble: 5 x 6
#State County  Plot  Tree Meas_yr tree_survival
#<dbl>  <dbl> <dbl> <dbl> <chr>           <dbl>
#  1     1      9     1     1 t1                  1
#2     1      9     1     2 t1                  1
#3     1      9     1     3 t1                  0
#4     1      9     1     1 t2                  1
#5     1      9     1     2 t2                  1