How to Add a Cumulative Column to an R Dataframe Using Dplyr

How to add a cumulative column to an R dataframe using dplyr?

Like this?

df <- data.frame(id = rep(1:3, each = 5),
                 hour = rep(1:5, 3),
                 value = sample(1:15))

mutate(group_by(df,id), csum=cumsum(value))

Or if you use the dplyr's piping operator:

df %>% group_by(id) %>% mutate(csum = cumsum(value))

Result in both cases:

Source: local data frame [15 x 4]
Groups: id

   id hour value csum
1   1    1     4      4
2   1    2    14     18
3   1    3     8     26
4   1    4     2     28
5   1    5     3     31
6   2    1    10     10
7   2    2     7     17
8   2    3     5     22
9   2    4    12     34
10  2    5     9     43
11  3    1     6      6
12  3    2    15     21
13  3    3     1     22
14  3    4    13     35
15  3    5    11     46

a function to add the cumulative sum of multiple columns

You can rewrite colColsum like this:

colCumsum <- function(x) {
  check <- sapply(x, is.numeric)
  x[paste0(names(x)[check], "_cumsum")] <- lapply(x[check], cumsum)
  x
}

Here it is used on your sample data:

colCumsum(df)
#   name    sex born v4  v5 v6 v7 v4_cumsum v5_cumsum v6_cumsum v7_cumsum
# 1  tim   male 1985  5  10  1  0         5        10         1         0
# 2  tom   male 1986  4  20  2  0         9        30         3         0
# 3  ben   male 1985  3 600  3 20        12       630         6        20
# 4 mary female 1986  2  20  4  4        14       650        10        24
# 5 jane female 1984  1   5  5 60        15       655        15        84

---

For reference, you can rewrite your loop to just focus on the numeric columns to get it to work:

colCumsum2 <- function(x) { 
  for (i in 1:ncol(x)) {
    if (is.numeric(x[, i])) {
      x[, paste0(names(x)[i], "_cumsum")] <- cumsum(x[, i])
    }
  }
  x
}

Create series of variables that are cumulative sums of other variables using dplyr

You could take rowSums incrementing one column at a time.

df[letters[5:8]] <- do.call(cbind, lapply(seq(ncol(df)), 
                            function(x) rowSums(df[1:x])))
df

#   a  b  c d  e  f  g  h
#1 10 30  5 5 10 40 45 50
#2 10 50  5 5 10 60 65 70
#3 20 60  5 5 20 80 85 90
#4 20 20  1 3 20 40 41 44
#5 30 10 10 5 30 40 50 55

Or if you are interested in a tidyverse solution :

library(dplyr)

df %>%
  bind_cols(purrr::map_dfc(seq(ncol(df)), 
                 ~df %>% select(1:.x) %>% rowSums) %>% setNames(letters[5:8]))
                          

---

Related Topics