Need Help - finding efficient way to solve grouping or loop problem

[srini]

Hi I have a problem and need the help
I am trying to build a for loop in R . but facing the error as the loop is not creating the exact variable and may be double counting. Also if you can suggest efficient way of doing this.
What i trying to do is

1. I would like to develop a code which can create a variable which can sum up all the values in the column "nos" based on the filter conditions.Below are the conditions. i want to add a counter called sum (nos[i]) to sum all the rows which satisify below conditions but missing something .

The logic for less6 month calculation
library(lubridate)
dataji$Date_Created <- as.Date(dataji$Date_Created, "%m/%d/%Y") # convert to date
dataji$less6month <- dataji$Date_Created %m-% months(6) # subtract 6 months

dataji$count <- 0 # initialise counter
i <- 1
for (i in 1:nrow(datanew1)){
compare <- (dataji$country==dataji$country) &
(dataji$grade==dataji$grade ) &
(dataji$department==dataji$department ) &
(dataji$Date_Created >=dataji$less6month[i])&
(dataji$Date_Created <= dataji$Date_Created[i])
dataji$count[i] <- sum(compare)

}
Please find below the data

structure(list(id = 1:293, nos = c(4L, 2L, 3L, 4L, 5L, 19L, 7L,
1L, 2L, 1L, 9L, 2L, 2L, 3L, 2L, 1L, 2L, 1L, 6L, 1L, 3L, 17L,
16L, 12L, 7L, 4L, 3L, 2L, 2L, 1L, 3L, 3L, 12L, 5L, 4L, 7L, 3L,
9L, 10L, 11L, 4L, 13L, 12L, 17L, 1L, 3L, 2L, 1L, 5L, 4L, 1L,
8L, 1L, 1L, 1L, 16L, 7L, 4L, 1L, 2L, 1L, 2L, 2L, 5L, 1L, 1L,
8L, 1L, 1L, 9L, 2L, 9L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 4L, 1L, 1L,
1L, 4L, 3L, 2L, 9L, 1L, 1L, 1L, 4L, 4L, 7L, 3L, 5L, 5L, 4L, 9L,
3L, 1L, 6L, 1L, 7L, 3L, 10L, 19L, 1L, 2L, 3L, 1L, 7L, 3L, 5L,
5L, 7L, 4L, 10L, 4L, 1L, 1L, 3L, 5L, 4L, 5L, 4L, 8L, 2L, 5L,
9L, 6L, 5L, 4L, 8L, 6L, 4L, 9L, 5L, 5L, 6L, 9L, 8L, 6L, 4L, 1L,
7L, 7L, 8L, 2L, 9L, 4L, 9L, 7L, 7L, 4L, 8L, 2L, 1L, 6L, 2L, 8L,
1L, 4L, 1L, 4L, 1L, 1L, 4L, 6L, 1L, 5L, 1L, 4L, 2L, 1L, 7L, 1L,
3L, 7L, 6L, 3L, 7L, 3L, 1L, 6L, 8L, 14L, 17L, 5L, 15L, 4L, 4L,
9L, 1L, 1L, 5L, 3L, 2L, 3L, 9L, 1L, 2L, 2L, 1L, 4L, 3L, 2L, 5L,
4L, 1L, 1L, 4L, 6L, 1L, 2L, 5L, 5L, 2L, 6L, 4L, 7L, 6L, 7L, 7L,
1L, 3L, 1L, 1L, 6L, 3L, 5L, 8L, 1L, 5L, 3L, 3L, 2L, 1L, 3L, 1L,
1L, 2L, 1L, 5L, 2L, 2L, 2L, 6L, 3L, 3L, 2L, 2L, 1L, 3L, 1L, 2L,
6L, 1L, 1L, 3L, 4L, 2L, 13L, 5L, 3L, 6L, 1L, 3L, 2L, 3L, 1L,
5L, 2L, 2L, 2L, 3L, 1L, 3L, 4L, 1L, 1L, 1L, 3L, 2L, 5L, 2L, 2L,
4L, 2L, 1L, 9L, 2L, 1L, 2L), JG = c(3L, 3L, 3L, 4L, 4L, 4L, 3L,
4L, 3L, 2L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 4L, 4L, 4L, 3L, 4L, 4L,
3L, 4L, 2L, 3L, 2L, 2L, 3L, 4L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L,
4L, 2L, 3L, 3L, 4L, 4L, 4L, 2L, 4L, 3L, 4L, 4L, 2L, 3L, 3L, 2L,
4L, 4L, 4L, 2L, 3L, 3L, 3L, 4L, 3L, 4L, 2L, 3L, 4L, 4L, 2L, 4L,
3L, 3L, 4L, 3L, 3L, 4L, 4L, 4L, 3L, 4L, 3L, 2L, 3L, 3L, 3L, 4L,
4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 2L, 3L, 4L,
3L, 4L, 3L, 2L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 4L, 3L, 3L, 2L,
4L, 4L, 2L, 2L, 2L, 3L, 4L, 2L, 2L, 2L, 2L, 2L, 4L, 2L, 2L, 3L,
3L, 2L, 2L, 2L, 2L, 4L, 2L, 3L, 3L, 4L, 3L, 3L, 2L, 3L, 3L, 4L,
4L, 4L, 2L, 3L, 2L, 2L, 3L, 2L, 3L, 3L, 3L, 4L, 3L, 3L, 3L, 4L,
3L, 4L, 4L, 4L, 4L, 4L, 2L, 4L, 3L, 4L, 4L, 4L, 2L, 4L, 3L, 3L,
4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 3L, 4L,
4L, 4L, 4L, 3L, 4L, 4L, 4L, 3L, 4L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
4L, 3L, 4L, 4L, 4L, 4L, 3L, 4L, 4L, 3L, 4L, 4L, 2L, 3L, 3L, 4L,
4L, 3L, 2L, 4L, 4L, 4L, 3L, 3L, 3L, 4L, 3L, 4L, 2L, 3L, 4L, 3L,
4L, 4L, 4L, 2L, 3L, 3L, 3L, 4L, 3L, 4L, 3L, 3L, 4L, 4L, 4L, 4L,
3L, 4L, 4L, 3L, 4L, 4L, 3L, 2L, 3L, 3L, 3L, 4L, 3L, 4L, 2L, 4L,
4L, 4L, 4L, 4L, 4L, 3L, 2L, 3L, 4L, 4L, 3L, 4L, 4L, 4L), Department = structure(c(1L,
1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L,
2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L,
2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L,
3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L,
3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L,
3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L,
2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L,
3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L,
3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L,
2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L,
3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L,
3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L,
3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L,
2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L,
3L, 3L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L,
3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L,
2L, 3L, 3L, 3L, 3L, 1L, 3L, 1L, 2L, 3L, 3L, 3L, 3L, 1L, 2L, 3L,
3L, 3L, 3L, 1L), .Label = c("Fin", "Ops", "RE"), class = "factor"),
Country = structure(c(10L, 10L, 10L, 18L, 18L, 18L, 2L, 2L,
10L, 11L, 18L, 17L, 17L, 17L, 17L, 17L, 17L, 3L, 3L, 3L,
3L, 4L, 4L, 4L, 8L, 17L, 10L, 10L, 10L, 8L, 10L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 18L, 9L, 18L, 13L, 10L, 18L,
12L, 18L, 10L, 15L, 16L, 9L, 5L, 5L, 2L, 5L, 15L, 5L, 6L,
11L, 17L, 11L, 4L, 16L, 18L, 18L, 18L, 8L, 17L, 18L, 18L,
8L, 10L, 10L, 10L, 10L, 2L, 2L, 2L, 2L, 17L, 17L, 18L, 11L,
11L, 11L, 4L, 1L, 1L, 11L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 10L, 9L, 10L, 9L, 2L, 15L, 18L, 11L, 10L,
9L, 8L, 4L, 4L, 4L, 18L, 18L, 18L, 18L, 18L, 8L, 8L, 8L,
18L, 10L, 10L, 18L, 18L, 17L, 10L, 8L, 8L, 10L, 8L, 18L,
18L, 18L, 18L, 18L, 18L, 10L, 17L, 8L, 8L, 8L, 8L, 18L, 18L,
18L, 10L, 18L, 10L, 18L, 18L, 18L, 17L, 17L, 17L, 17L, 17L,
17L, 17L, 17L, 17L, 17L, 10L, 9L, 2L, 16L, 16L, 18L, 18L,
16L, 11L, 10L, 18L, 2L, 7L, 2L, 8L, 8L, 10L, 8L, 8L, 18L,
18L, 8L, 8L, 8L, 8L, 9L, 18L, 18L, 18L, 8L, 8L, 18L, 18L,
2L, 3L, 4L, 10L, 14L, 8L, 18L, 9L, 18L, 18L, 18L, 8L, 9L,
17L, 4L, 11L, 9L, 11L, 11L, 8L, 18L, 18L, 4L, 4L, 4L, 4L,
4L, 18L, 18L, 18L, 10L, 2L, 2L, 2L, 2L, 16L, 18L, 10L, 10L,
16L, 18L, 9L, 8L, 10L, 16L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 10L, 18L,
18L, 18L, 9L, 9L, 18L, 9L, 18L, 18L, 5L, 18L, 10L, 2L, 10L,
2L, 5L, 2L, 18L, 8L, 18L, 17L, 10L, 17L, 11L, 10L, 9L, 11L,
18L, 17L, 17L, 17L, 11L, 10L, 11L, 8L), .Label = c("Argentina",
"Australia", "Brazil", "Canada", "China", "Egypt", "Germany",
"India", "Malaysia", "Netherlands", "Nigeria", "Norway",
"Oman", "Philippines", "Qatar", "Singapore", "United Kingdom",
"United States"), class = "factor"), Date_Created = structure(c(66L,
67L, 71L, 74L, 74L, 78L, 90L, 96L, 97L, 103L, 104L, 109L,
109L, 109L, 109L, 109L, 109L, 111L, 111L, 111L, 111L, 114L,
114L, 114L, 116L, 116L, 121L, 121L, 121L, 130L, 134L, 125L,
126L, 126L, 126L, 126L, 126L, 126L, 126L, 126L, 128L, 132L,
29L, 14L, 14L, 16L, 20L, 25L, 26L, 44L, 36L, 36L, 37L, 38L,
50L, 9L, 2L, 5L, 6L, 64L, 56L, 58L, 60L, 70L, 76L, 77L, 68L,
72L, 75L, 85L, 86L, 79L, 80L, 80L, 80L, 80L, 80L, 80L, 80L,
81L, 87L, 87L, 100L, 89L, 94L, 94L, 102L, 106L, 119L, 108L,
112L, 112L, 112L, 112L, 112L, 112L, 112L, 112L, 112L, 115L,
122L, 133L, 123L, 124L, 127L, 136L, 142L, 139L, 140L, 28L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 13L, 17L, 18L, 18L, 18L, 18L, 18L,
18L, 27L, 34L, 34L, 40L, 48L, 51L, 52L, 52L, 52L, 52L, 52L,
52L, 52L, 52L, 52L, 52L, 52L, 10L, 10L, 10L, 1L, 3L, 3L,
4L, 7L, 8L, 63L, 65L, 54L, 55L, 57L, 59L, 61L, 61L, 62L,
69L, 73L, 84L, 82L, 82L, 83L, 101L, 101L, 101L, 88L, 91L,
92L, 93L, 93L, 93L, 93L, 93L, 95L, 95L, 98L, 99L, 107L, 107L,
107L, 107L, 117L, 118L, 118L, 105L, 110L, 113L, 120L, 135L,
135L, 129L, 131L, 131L, 131L, 131L, 131L, 131L, 131L, 131L,
131L, 131L, 131L, 131L, 131L, 131L, 131L, 131L, 141L, 141L,
137L, 138L, 24L, 24L, 24L, 30L, 31L, 31L, 32L, 11L, 15L,
19L, 19L, 21L, 21L, 21L, 22L, 23L, 42L, 42L, 43L, 45L, 46L,
46L, 33L, 35L, 39L, 41L, 41L, 41L, 47L, 49L, 49L, 53L), .Label = c("1/10/2018",
"1/12/2017", "1/12/2018", "1/15/2018", "1/20/2017", "1/25/2017",
"1/25/2018", "1/29/2018", "1/6/2017", "1/8/2018", "10/10/2018",
"10/11/2017", "10/12/2017", "10/14/2016", "10/15/2018", "10/17/2016",
"10/17/2017", "10/20/2017", "10/22/2018", "10/23/2016", "10/23/2018",
"10/24/2018", "10/25/2018", "10/3/2018", "10/30/2016", "10/31/2016",
"10/31/2017", "10/4/2017", "10/5/2016", "10/5/2018", "10/8/2018",
"10/9/2018", "11/13/2018", "11/15/2017", "11/15/2018", "11/18/2016",
"11/24/2016", "11/25/2016", "11/26/2018", "11/29/2017", "11/29/2018",
"11/5/2018", "11/6/2018", "11/7/2016", "11/7/2018", "11/8/2018",
"12/10/2018", "12/11/2017", "12/11/2018", "12/13/2016", "12/18/2017",
"12/22/2017", "12/26/2018", "2/12/2018", "2/14/2018", "2/16/2017",
"2/16/2018", "2/17/2017", "2/21/2018", "2/23/2017", "2/26/2018",
"2/27/2018", "2/6/2018", "2/8/2017", "2/8/2018", "3/1/2016",
"3/15/2016", "3/15/2017", "3/19/2018", "3/2/2017", "3/21/2016",
"3/21/2017", "3/28/2018", "3/31/2016", "3/31/2017", "3/6/2017",
"3/8/2017", "4/1/2016", "4/11/2017", "4/13/2017", "4/14/2017",
"4/25/2018", "4/30/2018", "4/4/2018", "4/5/2017", "4/7/2017",
"5/1/2017", "5/11/2018", "5/12/2017", "5/13/2016", "5/14/2018",
"5/15/2018", "5/16/2018", "5/17/2017", "5/21/2018", "5/24/2016",
"5/25/2016", "5/25/2018", "5/29/2018", "5/3/2017", "5/3/2018",
"5/31/2017", "6/1/2016", "6/13/2016", "6/13/2018", "6/2/2017",
"6/2/2018", "6/20/2017", "6/22/2016", "6/22/2018", "6/26/2016",
"6/26/2017", "6/26/2018", "6/28/2016", "6/29/2017", "6/30/2016",
"6/4/2018", "6/5/2018", "6/6/2017", "7/10/2018", "7/29/2016",
"7/7/2017", "8/10/2017", "8/11/2017", "8/12/2016", "8/16/2016",
"8/16/2017", "8/17/2016", "8/17/2018", "8/2/2016", "8/21/2018",
"8/25/2016", "8/3/2017", "8/4/2016", "8/6/2018", "9/1/2017",
"9/18/2018", "9/20/2018", "9/21/2017", "9/27/2017", "9/4/2018",
"9/5/2017"), class = "factor")), class = "data.frame", row.names = c(NA,
-293L))
The final output should like this

There is something similar to this problem but i am unable to replicate it.

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