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Maximum rolling sum in data frame

I want to obtain the largest possible sum for a time period.

For example, I have a data frame with units in store for a certain product:

library(tidyverse)

data <- tibble(
date = paste("Day", 1:5),
units_in_store = c(10,3,-2,1,-1)
)


cumsum(data$units_in_store) would return 11 but the largest possible sum in that case is 13, and summing one by one the values would be 13, 11, 12 and 11.

cumsum(data$units_in_store)

Is there a way to compute the maximum moving/rolling sum?

In other words: How can I compute the largest possible sum with

Day 1 + Day2

Day 1 + Day 2 + Day 3

Day 1 + Day 2 + Day 3 + Day 4

etc?

This would be the expected output:

data %>% mutate(units2 = something(units_in_store))

# A tibble: 5 x 3
date units_in_store units2
<chr> <dbl> <dbl>
1 Day 1 10 13
2 Day 2 3 13
3 Day 3 -2 13
4 Day 4 1 13
5 Day 5 -1 13


2 Answers
2

You mean something like this?

data<-mutate(data,units2=max(cumsum(units_in_store)))


output:

date units_in_store units2
<chr> <dbl> <dbl>
1 Day 1 10 13
2 Day 2 3 13
3 Day 3 -2 13
4 Day 4 1 13
5 Day 5 -1 13


We can use Reduce to get the result "summing one by one":

Reduce

> Reduce("+",data$units_in_store, accumulate = TRUE)[-1]
[1] 13 11 12 11


This is an alternative to cumsum see @doviod´s answer. Then you can select the max value.

cumsum

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