CODEWITHSUNDEEP
rcumsum
GrBa
GrBa

Reputation: 659

Counting the number of observations cumulatively with an additional condition

I have data on the outside temperature

df1 <- read.table(text = "DT   temp.out
'2023-01-18 00:00:00'   6.8
'2023-02-18 23:00:00'   1.5
'2023-03-04 00:00:00'   2.6
'2023-04-20 03:00:00'   -5.0
'2023-06-21 05:00:00'   11.9
'2023-08-10 19:00:00'   6.2
'2023-08-21 23:00:00'   -2.8
'2023-09-19 01:00:00'   5.7
'2023-11-3 07:00:00'    9.1
'2023-12-21 13:00:00'   -19.8", header = TRUE) %>% 
  mutate (DT = as.POSIXct(DT))

I want to get a summary of the number of observations that are less than or equal to the cutoff value. For the data presented, expected result:

> result
   T.gr l.obs
1   -20     0
2   -19     1
3   -18     1
4   -17     1
5   -16     1
6   -15     1
7   -14     1
8   -13     1
9   -12     1
10  -11     1
11  -10     1
12   -9     1
13   -8     1
14   -7     1
15   -6     1
16   -5     2
17   -4     2
18   -3     2
19   -2     3
20   -1     3
21    0     3
22    1     3
23    2     4
24    3     5
25    5     5
26    6     6
27    7     8
28    8     8
29    9     8
30   10     9
31   11     9
32   12    10
33   13    10
34   14    10
35   15    10
36   16    10
37   17    10
38   18    10
39   19    10
40   20    10
>

The presented summary ranges from -20 to 20. Ultimately, the summary should start from -20 and end with the larger of the following two values:

Upvotes: 0

Views: 28

Answers (1)

Ronak Shah
Ronak Shah

Reputation: 389235

Using cut we divide the data in the required range. Use table to calculate it's frequency, take a cumulative sum (cumsum) and stack it to present in a data frame format.

lvls <- seq(-21, max(20, max(df1$temp.out)+1))

cut(df1$temp.out, breaks = lvls, labels = lvls[-1]) |>
  table() |>
  cumsum() |>
  stack() |>
  rev()

Output of this is :

   ind values
1  -20      0
2  -19      1
3  -18      1
4  -17      1
5  -16      1
6  -15      1
7  -14      1
8  -13      1
9  -12      1
10 -11      1
11 -10      1
12  -9      1
13  -8      1
14  -7      1
15  -6      1
16  -5      2
17  -4      2
18  -3      2
19  -2      3
20  -1      3
21   0      3
22   1      3
23   2      4
24   3      5
25   4      5
26   5      5
27   6      6
28   7      8
29   8      8
30   9      8
31  10      9
32  11      9
33  12     10
34  13     10
35  14     10
36  15     10
37  16     10
38  17     10
39  18     10
40  19     10
41  20     10

Upvotes: 0

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