Backtrack values in R for a logic - r

Question

My request is slightly complicated.
Below is how my data looks like.
**S.no Date City Sales diff Indicator
1 1 1/1/2017 New York 2795 0 0
2 2 1/31/2017 New York 4248 1453 0
3 3 3/2/2017 New York 1330 -2918 1
4 4 4/1/2017 New York 3535 2205 0
5 5 5/1/2017 New York 4330 795 0
6 6 5/31/2017 New York 3360 -970 1
7 7 6/30/2017 New York 2238 -1122 1
8 8 1/1/2017 Paris 1451 0 0
9 9 1/31/2017 Paris 2339 888 0
10 10 3/2/2017 Paris 2029 -310 1
11 11 4/1/2017 Paris 1850 -179 1
12 12 5/1/2017 Paris 2800 950 1
13 13 5/31/2017 Paris 1986 -814 0
14 14 6/30/2017 Paris 3776 1790 0
15 15 1/1/2017 London 1646 0 0
16 16 1/31/2017 London 3575 1929 0
17 17 3/2/2017 London 1161 -2414 1
18 18 4/1/2017 London 1766 605 0
19 19 5/1/2017 London 2799 1033 0
20 20 5/31/2017 London 2761 -38 1
21 21 6/30/2017 London 1048 -1713 1**
diff is Current Month Sales-Last Month Sales, for each group, and Indicator is when diff is negative or positive.
I want to compute a logic for each group starting from last row to first row, aka in reverse order.
I want to see in reverse order, the value of Sales when indicator was 1. The compare that captured Sales value to the threshold value(2000), for next steps.
Now below are two cases of comparison(Capture Sales v/s Threshold).
a. If captured value of sales, when Indicator is first 1(starting from last row to 1st row), is less than 2000, then store the captured values in a new dataset for each group.
b. If the captured of sales, when Indicator is first 1(starting from last row to 1st row), is greater than 2000, then skip that Indicator=1 row and move to the next row where Indicator=1, and repeat the same step for pt.a) and pt. b)
I want to bring the result in a new dataset, that will have a single row for each City providing me the "Sales value" for the aforementioned logic, along with the Date.
I simply want to understand how can i bring up this logic in R. Will rle function help?
Result:
S.no Date City Value(Sales)
3. 3/2/2017 New York 1330
11. 4/1/2017 Paris 1850
21. 6/30/2017 London 1048
Thanks,
J

Answer 1

If we assume that your data is already arranged it ascending order, you can do the following with base R:
threshold <- 2000
my_new_df <- my_df[my_df$Indicator == 1 & my_df$Sales < threshold, ]
my_new_df
# S.no Date City Sales diff Indicator
# 3 3 2017-03-02 New York 1330 -2918 1
# 11 11 2017-04-01 Paris 1850 -179 1
# 17 17 2017-03-02 London 1161 -2414 1
# 21 21 2017-06-30 London 1048 -1713 1
Now we have all rows where the Indicator is equal to one and the Salse value less than our threshold. But London has to rows and we only wnat the last one:
my_new_df <- my_new_df[!duplicated(my_new_df$City, fromLast = T),
c("S.no", "Date", "City", "Sales")]
my_new_df
# S.no Date City Sales
# 3 3 2017-03-02 New York 1330
# 11 11 2017-04-01 Paris 1850
# 21 21 2017-06-30 London 1048
With the fromLast-argument in the duplicated, we start in the last row to check, whether the City has already been in the data set.