(R) 计算月份之间的差距

Question

我有一个类似于下面示例的数据集。 MonthYear 变量仅描述 UniqueID 的第一次出现。 Count1 列计算 UniqueID 的出现次数。 Count2 列计算每个 UniqueID 的出现总数。 MonthCount 变量只是根据月份分配一个数字。我从 2018 年 10 月开始收集此信息，因此该值将获得 1，然后 2018 年 11 月将获得 2，依此类推。

注意：2019 年 7 月和 2019 年 10 月均无可用数据，因此 2019 年 8 月的值为 10，2019 年 11 月的值为 12。

UniqueID Region City MonthYear Count1 Count2 MonthCount
ABC123   West   AAA  OCT-18    1      4      1
ABC123   West   AAA  NOV-18    2      4      2
ABC123   West   AAA  DEC-18    3      4      3 
ABC123   West   AAA  JAN-19    4      4      4
DEF456   East   BBB  DEC-18    1      3      3 
DEF456   East   BBB  JAN-19    2      3      4
DEF456   East   BBB  MAR-19    3      3      6
GHI789   East   CCC  JAN-19    1      4      4
GHI789   East   CCC  FEB-19    2      4      5
GHI789   East   CCC  APR-19    3      4      7
GHI789   East   CCC  JUN-19    4      4      9
JKL012   South  DDD  AUG-19    1      4      10 
JKL012   South  DDD  SEP-19    2      4      11
JKL012   South  DDD  NOV-19    3      4      12
JKL012   South  DDD  DEC-19    4      4      13 

我想要做的是计算每个 UniqueID 每月跳过的总次数（JUL19 和 OCT19 除外）。我将有一个如下所示的数据集：

UniqueID Region City MonthYear Count1 Count2 MonthCount Skipped
ABC123   West   AAA  OCT-18    1      4      1          0      
ABC123   West   AAA  NOV-18    2      4      2          0
ABC123   West   AAA  DEC-18    3      4      3          0
ABC123   West   AAA  JAN-19    4      4      4          0
DEF456   East   BBB  DEC-18    1      3      3          1
DEF456   East   BBB  JAN-19    2      3      4          1
DEF456   East   BBB  MAR-19    3      3      6          1 
GHI789   East   CCC  JAN-19    1      4      4          2
GHI789   East   CCC  FEB-19    2      4      5          2
GHI789   East   CCC  APR-19    3      4      7          2
GHI789   East   CCC  JUN-19    4      4      9          2
JKL012   South  DDD  AUG-19    1      4      10         0 
JKL012   South  DDD  SEP-19    2      4      11         0
JKL012   South  DDD  NOV-19    3      4      12         0
JKL012   South  DDD  DEC-19    4      4      13         0

任何帮助将不胜感激！我不知道从哪里开始。谢谢！

Answer 1

通过'UniqueID'分组后，可以得到'MonthCount'的diff，检查是否有大于1的值即相邻月份的差异大于1，sum逻辑上的@987654323 @

df1 %>% 
   group_by(UniqueID) %>%
   mutate(Skipped = sum(diff(MonthCount) > 1))
# A tibble: 15 x 8
# Groups:   UniqueID [4]
#   UniqueID Region City  MonthYear Count1 Count2 MonthCount Skipped
#   <chr>    <chr>  <chr> <chr>      <int>  <int>      <int>   <int>
# 1 ABC123   West   AAA   OCT-18         1      4          1       0
# 2 ABC123   West   AAA   NOV-18         2      4          2       0
# 3 ABC123   West   AAA   DEC-18         3      4          3       0
# 4 ABC123   West   AAA   JAN-19         4      4          4       0
# 5 DEF456   East   BBB   DEC-18         1      3          3       1
# 6 DEF456   East   BBB   JAN-19         2      3          4       1
# 7 DEF456   East   BBB   MAR-19         3      3          6       1
# 8 GHI789   East   CCC   JAN-19         1      4          4       2
# 9 GHI789   East   CCC   FEB-19         2      4          5       2
#10 GHI789   East   CCC   APR-19         3      4          7       2
#11 GHI789   East   CCC   JUN-19         4      4          9       2
#12 JKL012   South  DDD   AUG-19         1      4         10       0
#13 JKL012   South  DDD   SEP-19         2      4         11       0
#14 JKL012   South  DDD   NOV-19         3      4         12       0
#15 JKL012   South  DDD   DEC-19         4      4         13       0

数据

df1 <- structure(list(UniqueID = c("ABC123", "ABC123", "ABC123", "ABC123", 
"DEF456", "DEF456", "DEF456", "GHI789", "GHI789", "GHI789", "GHI789", 
"JKL012", "JKL012", "JKL012", "JKL012"), Region = c("West", "West", 
"West", "West", "East", "East", "East", "East", "East", "East", 
"East", "South", "South", "South", "South"), City = c("AAA", 
"AAA", "AAA", "AAA", "BBB", "BBB", "BBB", "CCC", "CCC", "CCC", 
"CCC", "DDD", "DDD", "DDD", "DDD"), MonthYear = c("OCT-18", "NOV-18", 
"DEC-18", "JAN-19", "DEC-18", "JAN-19", "MAR-19", "JAN-19", "FEB-19", 
"APR-19", "JUN-19", "AUG-19", "SEP-19", "NOV-19", "DEC-19"), 
    Count1 = c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 1L, 2L, 3L, 4L, 1L, 
    2L, 3L, 4L), Count2 = c(4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L), MonthCount = c(1L, 2L, 3L, 4L, 3L, 
    4L, 6L, 4L, 5L, 7L, 9L, 10L, 11L, 12L, 13L)), class = "data.frame",
    row.names = c(NA, 
-15L))