How to Matching conditions in R Dataframe - r

Question

I am having dataframe which looks like:
Count_ID Stats Date
123 A 10-01-2017
123 A 12-01-2017
123 B 15-01-2017
456 B 18-01-2017
456 C 17-01-2017
789 A 20-01-2017
486 A 25-01-2017
486 A 28-01-2017
I want to add a Status & Count column in Dataframe which give me below mention status.
Match oldest Count_ID as per date having Stats as "A" compare if any Count_ID with same value (i.e 123) is having date > than that Previous same Count_ID having Stats as "A", than show it "False" in status column.
If there are multiple Count_ID with same value (i.e 123) than check Stats "A" than match any same Count_ID with Stats other than "A" or "A" are having date > than of those having Stats "A", than show status as "False"
If there are multiple same Count_ID (i.e 123) having Stats as "A" with date difference <30 days (w.r.t the previous Count_ID as per Date) show status as "False-B".
In count column, show difference of days between same Count_ID created from previous Count_ID.
Where no condition show it as "-".
Required Output:
Count_ID Stats Date Status Count
123 A 10-01-2017 False-B 0
123 A 12-01-2017 False-B 2
123 B 15-01-2017 False 3
456 B 18-01-2017 - 0
456 C 17-01-2017 False 1
789 A 20-01-2017 - 0
486 A 25-01-2017 False-B 0
486 A 28-01-2017 False-B 3
Dput:
structure(list(Count_ID = c(123L, 123L, 123L, 456L, 456L, 789L,
486L, 486L), Stats = c("A", "A", "B", "B", "C", "A", "A", "A"
), Date = c("10/01/2017", "12/01/2017", "15/01/2017", "18/01/2017",
"17/01/2017", "20/01/2017", "25/01/2017", "28/01/2017")), .Names = c("Count_ID",
"Stats", "Date"), class = "data.frame", row.names = c(NA, -8L
))

Answer 1

If I understood the question correctly then you can try this
library(dplyr)
df %>%
group_by(Count_ID) %>%
mutate(Count = c(0, abs(as.numeric(diff(Date)))),
Status = ifelse((Date==min(Date[Stats=='A']) | Date>min(Date[Stats=='A'])) & (n()>1), "FALSE", "-")) %>%
mutate(Status = ifelse(Stats=='A' & Count < 30 & Status=='FALSE', 'FALSE-B', Status)) %>%
data.frame()
Note that the condition for "row item 5" is not clear so I have left it as -. I am not sure how you want to go about this row as there is no Stats = A for Count_ID = 456.
Output is:
Count_ID Stats Date Count Status
1 123 A 2017-01-10 0 FALSE-B
2 123 A 2017-01-12 2 FALSE-B
3 123 B 2017-01-15 3 FALSE
4 456 B 2017-01-18 0 -
5 456 C 2017-01-17 1 -
6 789 A 2017-01-20 0 -
7 486 A 2017-01-25 0 FALSE-B
8 486 A 2017-01-28 3 FALSE-B
Sample data:
df <- structure(list(Count_ID = c(123L, 123L, 123L, 456L, 456L, 789L,
486L, 486L), Stats = c("A", "A", "B", "B", "C", "A", "A", "A"
), Date = structure(c(17176, 17178, 17181, 17184, 17183, 17186,
17191, 17194), class = "Date")), .Names = c("Count_ID", "Stats",
"Date"), row.names = c(NA, -8L), class = "data.frame")