差异数据框列的每个子集

Question

我有一个包含 ID、年份和月份的数据框。我需要按年和月分组并从该组中获取唯一 ID。我想将唯一ID与上年、月组进行比较，增加了多少个ID，减去了多少个。

有点像在黑暗中拍摄，但我尝试了以下方法，但不起作用：

connections <- df %>%
  group_by(year, month) %>%
  arrange(year, month) %>%
  diff_data(unique(as.vector(~ID)), lag(unique(as.vector(~ID))))

示例数据

df <- data.frame(ID=c("A1", "A2", "A3", "A1", "A2","A4", "A1", "A4", "A5"),
year= c(2010, 2010, 2010, 2011, 2011, 2011, 2012, 2012, 2012), 
month= c(1, 2, 3, 1, 2, 3, 1, 2, 3))

Desired Output

Answer 1

首先会在月份和年份执行 aggregate。在这种方法中，将列出每个月添加和删除的所有 ID，并获取 length 来计算每个月添加和删除的数量。

library(tidyverse)

df %>%
  aggregate(ID ~ year + month, ., unique, drop = FALSE) %>%
  group_by(month) %>%
  arrange(year) %>%
  mutate(addedID = mapply(setdiff, ID, lag(ID), SIMPLIFY = FALSE),
         num_addedID = lapply(addedID, length),
         deletedID = mapply(setdiff, lag(ID), ID, SIMPLIFY = FALSE),
         num_deletedID = lapply(deletedID, function(x) length(na.omit(x)))) %>%
  ungroup() %>%
  arrange(month, year) %>%
  as.data.frame()

输出

  year month ID addedID num_addedID deletedID num_deletedID
1 2010     1 A1      A1           1        NA             0
2 2011     1 A1                   0                       0
3 2012     1 A1                   0                       0
4 2010     2 A3      A3           1        NA             0
5 2011     2 A2      A2           1        A3             1
6 2012     2 A4      A4           1        A2             1
7 2010     3 A3      A3           1        NA             0
8 2011     3 A4      A4           1        A3             1
9 2012     3 A5      A5           1        A4             1

数据

df <- data.frame(ID=c("A1", "A3", "A3", "A1", "A2","A4", "A1", "A4", "A5"),
                 year= c(2010, 2010, 2010, 2011, 2011, 2011, 2012, 2012, 2012), 
                 month= c(1, 2, 3, 1, 2, 3, 1, 2, 3))

差异数据框列的每个子集

Diff on each subset of a data frame column

diff

r

subset