5
ve <- c(17, -9, 9, -17, 17, -17, 11, -9, 16, -18, 17, 0, 0, -18, 17, 0, 0, -17, 14, -14, 17, -2, 0, -15, 9, -9, 17, -16, 16, -17, 17, -17, 17, -17, 17, -17, 17, -8, 7, -16, 17, -14, 14, -10, 10, -16, 16, -10, 10, -12, 12, -11, 11, -17, 17, -17, 17, -9, 8, -17, 17, -17, 17, -16, 16, -17, 17, -8, 8, -9, 9, -17, 17, -17, 17, -13, 13, -10, 7, -10, 13, -16, 17, -13, 13, -13, 13, -9, 8, -17, 17, -10, 9, -17, 17, -17, 17, -16, 16, -10, 10, -15, 15, -14, 14, -14, 15, -13, 13, -9, 9, -13, 13, -12, 12, -10, 9, -11, 12, -8, 7, -10, 10, -9, 9, -11, 11, -9, 9, -7, 7, -12, 11, -11, 12, -11, 11, -14, 14, -13, 13, -10, 10, -13, 13, -17, 17, -7, 7, -17, 17, -17, 17, -14, 14, NA)

df <- data.frame(ve = ve, calc = 0)

I need to calculate cumsum in column calc, but it needs to reset to zero and start again whenever its value goes negative.. I've tried several conditions but it's not really working...

Also, is it possible to achieve this in dplyr? I'm new to dplyr and find it somewhat difficult whenever I need to use dependent value..

Thank you for your help!

it should go as..

     ve calc
1    17    17
2    -9    8
3     9    17
4   -17    0
5    17    17
6   -17    0
7    11    11
8    -9    2
9    16    18
10  -18    0
11   17    17
12    0    17
13    0    17
14  -18    0
15   17    17

If you see row 14 and 15, with the normal cumsum it would be -1 and 16 but I want it to reset to 0 instead of -1 and continue cumsum, hence the next would be 17

user5813583
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5 Answers5

2

We can replace the NA values with 0 and use cumsum

library(dplyr)
df1 <- df %>%
      group_by(grp = cumsum(lag(cumsum(replace(ve, is.na(ve), 0)) < 0, default = TRUE))) %>%
     mutate(calc = cumsum(replace(ve, is.na(ve), 0)), calc = replace(calc, calc < 0, 0)) %>%
      ungroup() %>%
      select(-grp)
head(df1, 15)
# A tibble: 15 x 2
#      ve  calc
#   <dbl> <dbl>
# 1    17    17
# 2    -9     8
# 3     9    17
# 4   -17     0
# 5    17    17
# 6   -17     0
# 7    11    11
# 8    -9     2
# 9    16    18
#10   -18     0
#11    17    17
#12     0    17
#13     0    17
#14   -18     0
#15    17    17
akrun
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2

base R's Reduce or purrr::accumulate are designed for these scenarios

df$calc <- Reduce(\(.x, .y) ifelse(.x + .y < 0, 0, .x + .y), df$ve, accumulate = TRUE)
df
#>      ve calc
#> 1    17   17
#> 2    -9    8
#> 3     9   17
#> 4   -17    0
#> 5    17   17
#> 6   -17    0
#> 7    11   11
#> 8    -9    2
#> 9    16   18
#> 10  -18    0
#> 11   17   17
#> 12    0   17
#> 13    0   17
#> 14  -18    0
#> 15   17   17
.
.
.

or in purrr

library(purrr)
library(dplyr)

df %>% mutate(calc = accumulate(ve,  ~ ifelse(.x + .y < 0, 0, .x + .y)))
AnilGoyal
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1

Not using dplyr, but this should work:

ve = as.data.frame(ve)
ve = na.omit(ve)
ve$cumS = 0
ve$cumS[1] = ve$ve[1]

for (i in 2 : length(ve$ve)) {

ve$cumS[i] = ifelse((ve$cumS[i - 1] + ve$ve[i]) < 0,
                     0, (ve$cumS[i - 1] + ve$ve[i]))
}
AK88
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    This looks about right, but I think it fails because your `ifelse` statement doesn't actually do anything, you would need to assign the result to `ve$cumS[i]` I think. – Marius Jun 13 '17 at 04:44
1

Here is an iterative solution. I can't think of how to do this vectorized/using dplyr without multiple passes over the data, but I'm sure someone else will:

ve_csum = numeric(length(ve))

current_total = 0
for (i in 1:length(ve)) {
    if (is.na(ve[i])) {
        ve_csum[i] = current_total
        next
    }
    current_total = current_total + ve[i]
    if (current_total < 0) {
        current_total = 0
    }
    ve_csum[i] = current_total
}

result = data.frame(ve, ve_csum)
Marius
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-1
> df$calc=ifelse(cumsum(df$ve)<0,0,cumsum(df$ve))
Ajay Ohri
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