You can use the following methods to calculate a cumulative sum by group in R:

Method 1: Use Base R

df$cum_sum <- ave(df$values_var, df$group_var, FUN=cumsum)

Method 2: Use dplyr

library(dplyr)

df %>% group_by(group_var) %>% mutate(cum_sum = cumsum(values_var))

Method 3: Use data.table

library(data.table)

setDT(df)[, cum_sum := cumsum(values_var), group_var] 

The following examples show how to use each method in practice with the following data frame in R:

#create data frame
df <- data.frame(store=rep(c('A', 'B', 'C'), each=4),
                 sales=c(3, 4, 4, 2, 5, 8, 9, 7, 6, 8, 3, 2))

#view data frame
df

   store sales
1      A     3
2      A     4
3      A     4
4      A     2
5      B     5
6      B     8
7      B     9
8      B     7
9      C     6
10     C     8
11     C     3
12     C     2

Example 1: Calculate Cumulative Sum by Group Using Base R

The following code shows how to use the ave() function from base R to calculate the cumulative sum of sales, grouped by store:

#add column to show cumulative sales by store
df$cum_sales <- ave(df$sales, df$store, FUN=cumsum)

#view updated data frame
df

   store sales cum_sales
1      A     3         3
2      A     4         7
3      A     4        11
4      A     2        13
5      B     5         5
6      B     8        13
7      B     9        22
8      B     7        29
9      C     6         6
10     C     8        14
11     C     3        17
12     C     2        19

The new column called cum_sales displays the cumulative sum of sales, grouped by store.

Example 2: Calculate Cumulative Sum by Group Using dplyr

The following code shows how to use various functions from the dplyr package in R to calculate the cumulative sum of sales, grouped by store:

library(dplyr)

#add column to show cumulative sales by store
df %>% group_by(store) %>% mutate(cum_sales = cumsum(sales))

#view updated data frame
df

# A tibble: 12 x 3
# Groups:   store [3]
   store sales cum_sales
         
 1 A         3         3
 2 A         4         7
 3 A         4        11
 4 A         2        13
 5 B         5         5
 6 B         8        13
 7 B         9        22
 8 B         7        29
 9 C         6         6
10 C         8        14
11 C         3        17
12 C         2        19

The new column called cum_sales displays the cumulative sum of sales, grouped by store.

Example 3: Calculate Cumulative Sum by Group Using data.table

The following code shows how to use various functions from the data.table package in R to calculate the cumulative sum of sales, grouped by store:

library(data.table)

#add column to show cumulative sales by store
setDT(df)[, cum_sales := cumsum(sales), store] 

#view updated data frame
df

    store sales cum_sales
 1:     A     3         3
 2:     A     4         7
 3:     A     4        11
 4:     A     2        13
 5:     B     5         5
 6:     B     8        13
 7:     B     9        22
 8:     B     7        29
 9:     C     6         6
10:     C     8        14
11:     C     3        17
12:     C     2        19

The new column called cum_sales displays the cumulative sum of sales, grouped by store.

Note: All three methods produce the same result. However, the dplyr and data.table methods will tend to be quicker when working with extremely large data frames.

The following tutorials explain how to perform other common calculations in R: