Cumulative Sum calculation in R, using the dplyr package in R, you can calculate the cumulative sum of a column using the following methods.
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Approach 1: Calculate Cumulative Sum of One Column
df %>% mutate(cum_sum = cumsum(var1))
Approach 2: Calculate Cumulative Sum by Group
df %>% group_by(var1) %>% mutate(cum_sum = cumsum(var2))
The examples below demonstrate how to apply each strategy in practice.
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Example 1: Using dplyr, calculate the cumulative sum.
Let’s say we have the following R data frame:
Let’s make a dataset
df <- data.frame(day=c(1, 2, 3, 4, 5, 6, 7, 8), Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â sales=c(57, 42, 50, 99, 59, 51, 58, 45))
Now we can view the dataset
df
day sales 1Â Â 1Â Â Â 57 2Â Â 2Â Â Â 42 3Â Â 3Â Â Â 50 4Â Â 4Â Â Â 99 5Â Â 5Â Â Â 59 6Â Â 6Â Â Â 51 7Â Â 7Â Â Â 58 8Â Â 8Â Â Â 45
To create a new column that holds the cumulative sum of the values in the ‘sales’ column, use the following code.
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library(dplyr)
Let’s calculate the cumulative sum of sales
df %>% mutate(cum_sales = cumsum(sales))
day sales cum_sales 1Â Â 1Â Â Â 57Â Â Â Â Â Â Â 57 2Â Â 2Â Â Â 42Â Â Â Â Â Â Â 99 3Â Â 3Â Â Â 50Â Â Â Â Â Â 149 4Â Â 4Â Â Â 99Â Â Â Â Â Â 248 5Â Â 5Â Â Â 59Â Â Â Â Â Â 307 6Â Â 6Â Â Â 51Â Â Â Â Â Â 358 7Â Â 7Â Â Â 58Â Â Â Â Â Â 416 8Â Â 8Â Â Â 45Â Â Â Â Â Â 461
Example 2: Using dplyr, calculate the Cumulative Sum by Group.
Let’s say we have the following R data frame.
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Make a dataset
df <- data.frame(store=c('X', 'X', 'X', 'X', 'Y', 'Y', 'Y', 'Y'), Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â day=c(1, 2, 3, 4, 1, 2, 3, 4), Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â sales=c(87, 82, 80, 98, 98, 81, 88, 83))
View the dataset now
df
   X  1   87 2    X  2   82 3    X  3   80 4    X  4   98 5    Y  1   98 6    Y  2   81 7    Y  3   88 8    Y  4   83
To construct a new column that holds the cumulative sum of the values in the ‘sales’ column, grouped by the ‘store’ column, we can use the following code:
library(dplyr)
Now we can calculate the cumulative sum of sales by store.
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df %>% group_by(store) %>% mutate(cum_sales = cumsum(sales))
store  day sales cum_sales  <chr> <dbl> <dbl>    <dbl> 1 X        1   87       87 2 X        2   82      169 3 X        3   80      249 4 X        4   98      347 5 Y        1   98       98 6 Y        2   81      179 7 Y        3   88      267 8 Y        4   83      350