Excel SUMIFS equivalent in R

Question

I\'m very very new to R and am looking at ways of recreating an Excel VBA macro and Excel worksheet functions such as SUMIFS. SUMIFS sums a column if the row has entries ma

Answer 1

Assuming you have the above data in a data frame called df:

sum(df$Sample[EndDate >= df$StartDate & StartDate <= df$EndDate])

That is:

• df$Sample[...] selects the Sample column, with conditions specified in [...]
• EndDate >= df$StartDate and StartDate <= df$EndDate are from your example, converted to R conditions, with & in between to require both conditions to be true at the same time. Notice that there are no i indexes in the expression. That's how it works in R, the expression is evaluated for each row in the data frame, and the result of df$Sample[...] is a vector of values, only the values where the expression in [...] was true
• sum is of course a built-in function to calculate the sum, naturally

Answer 2

You could use lapply/sapply from base R to do this. x from @cameron.bracken's post.

x$sumifs <- sapply(seq_len(nrow(x)), function(i) with(x, 
             sum(Sample[EndDate >= StartDate[i] & StartDate <= EndDate[i]])))

x
#   StartDate    EndDate Sample sumifs
#1 2014-01-10 2014-01-24    139    697
#2 2014-01-12 2014-01-26    136   1459
#3 2014-01-19 2014-02-02    422   2358
#4 2014-01-25 2014-02-08    762   3671
#5 2014-01-29 2014-02-12    899   3715
#6 2014-02-05 2014-02-19    850   4159
#7 2014-02-07 2014-02-21    602   4159
#8 2014-02-09 2014-02-23    180   3397
#9 2014-02-18 2014-03-04    866   2498

Answer 3

You can use the 'by' function to get the value. In 'by' data frame is split by row into data frames subsetted by the values of one or more factors, and a function is applied to each subset in turn.

x$sumifs <- by(Sample[EndDate >= StartDate[i] & StartDate <= EndDate[i]],sum)

More details about the function can be found here

Answer 4

You could do this with a loop or with a Cartesian merge. I don't know of any built in functions to do exactly this.

library(dplyr)

x = structure(list(StartDate = structure(c(1389312000, 1389484800, 
1390089600, 1390608000, 1390953600, 1391558400, 1391731200, 1391904000, 
1392681600), tzone = "UTC", class = c("POSIXct", "POSIXt")), 
    EndDate = structure(c(1390521600, 1390694400, 1391299200, 
    1391817600, 1392163200, 1392768000, 1392940800, 1393113600, 
    1393891200), tzone = "UTC", class = c("POSIXct", "POSIXt"
    )), Sample = c(139L, 136L, 422L, 762L, 899L, 850L, 602L, 
    180L, 866L)), .Names = c("StartDate", "EndDate", "Sample"
), row.names = c(NA, -9L), class = "data.frame")

x2 = x
names(x2)=c('StartDate2','EndDate2','Sample2')
x3 = merge(x,x2,allow.cartesian =T)
x4 = summarise(group_by(x3,StartDate,EndDate),
    sumifs=sum(Sample2[EndDate2 >= StartDate & StartDate2 <= EndDate]))
x_sumifs = merge(x,x4,by=c('StartDate','EndDate'))

This is what the output looks like.

> x_sumifs
   StartDate    EndDate Sample sumifs
1 2014-01-10 2014-01-24    139    697
2 2014-01-12 2014-01-26    136   1459
3 2014-01-19 2014-02-02    422   2358
4 2014-01-25 2014-02-08    762   3671
5 2014-01-29 2014-02-12    899   3715
6 2014-02-05 2014-02-19    850   4159
7 2014-02-07 2014-02-21    602   4159
8 2014-02-09 2014-02-23    180   3397
9 2014-02-18 2014-03-04    866   2498