Calculate Cumulative Sum of a Numeric Object - cumsum() Function in R

The cumsum() function in R computes the cumulative sum of elements in a numeric object. This is useful for a variety of applications, including running totals or understanding the growth of a value over time.

Let's go over the basics of the cumsum() function with some examples:

1. Basic Usage

The most straightforward use of cumsum() is to calculate the cumulative sum of a numeric vector:

numbers <- c(1, 2, 3, 4, 5)
cumulative_sum <- cumsum(numbers)
print(cumulative_sum)  # Output: 1 3 6 10 15

In this example, the first value is 1 (the sum of just the first element), the second is 1+2=3, the third is 1+2+3=6, and so on.

2. Cumulative Sum with Negative Values

The cumsum() function handles negative values as expected:

numbers <- c(5, -3, 7, -2, 4)
cumulative_sum <- cumsum(numbers)
print(cumulative_sum)  # Output: 5 2 9 7 11

3. Cumulative Sum with NA Values

If there are any NA values in the numeric object, the cumulative sum will return NA for that value and all subsequent values:

numbers <- c(1, 2, NA, 4, 5)
cumulative_sum <- cumsum(numbers)
print(cumulative_sum)  # Output: 1 3 NA NA NA

4. Cumulative Sum of Matrix Columns or Rows

You can use cumsum() with matrices to get the cumulative sum of each column or row:

mat <- matrix(1:9, ncol=3)
print(mat)

# 1 4 7
# 2 5 8
# 3 6 9

# Cumulative sum of columns
col_cumsum <- apply(mat, 2, cumsum)
print(col_cumsum)

# Cumulative sum of rows
row_cumsum <- t(apply(mat, 1, cumsum))
print(row_cumsum)

5. Cumulative Sum in Data Frames

To compute the cumulative sum for specific columns in a data frame, use cumsum() directly on the desired column:

df <- data.frame(A = c(1, 2, 3, 4), B = c(5, 6, 7, 8))
df$A_cumsum <- cumsum(df$A)
df$B_cumsum <- cumsum(df$B)
print(df)

Summary

The cumsum() function in R is a simple yet powerful tool for calculating the running total of numeric objects. Whether you're working with vectors, matrices, or data frames, cumsum() provides a straightforward way to track the accumulation of values.

R cumsum() Function Example:

# Basic cumsum() example
x <- c(1, 2, 3, 4, 5)
cumulative_sum <- cumsum(x)

How to Use cumsum() to Calculate Cumulative Sum in R:

# Calculate cumulative sum in R
x <- c(1, 2, 3, 4, 5)
cumulative_sum <- cumsum(x)

Cumulative Sum by Groups in R Using cumsum():

# Cumulative sum by groups
data <- data.frame(group = rep(1:2, each = 5), value = 1:10)
data$cumulative_sum <- ave(data$value, data$group, FUN = cumsum)

Rolling Cumulative Sum in Time Series Data with cumsum() in R:

# Rolling cumulative sum
set.seed(123)
time_series <- rnorm(10)
rolling_cumsum <- cumsum(time_series)

Visualizing Cumulative Sum with ggplot2 in R:

# Visualizing cumulative sum with ggplot2
library(ggplot2)
set.seed(123)
data <- data.frame(value = rnorm(10))
data$cumulative_sum <- cumsum(data$value)

ggplot(data, aes(x = seq_along(value), y = cumulative_sum)) +
  geom_line() +
  labs(title = "Cumulative Sum with ggplot2", x = "Index", y = "Cumulative Sum")

Cumulative Sum with Conditional Statements Using cumsum() in R:

# Cumulative sum with conditional statements
x <- c(1, 2, 3, 4, 5)
conditional_cumsum <- cumsum(ifelse(x > 2, x, 0))

Resetting Cumulative Sum at Specific Points in R:

# Resetting cumulative sum at specific points
x <- c(1, 2, 3, 4, 5, 1, 2, 3, 4, 5)
reset_indices <- c(5, 10)
reset_cumsum <- cumsum(x * !duplicated(cumsum(x > 2) * cumsum(x > 2) %in% reset_indices))

Cumulative Sum vs Running Sum in R:
- Cumulative sum includes all previous values.
- Running sum considers only the current and previous values.
```
# Cumulative sum vs running sum
x <- c(1, 2, 3, 4, 5)
cumulative_sum <- cumsum(x)
running_sum <- cumsum(x)
```

Calculating Moving Average with cumsum() in R:

# Calculating moving average
set.seed(123)
time_series <- rnorm(10)
window_size <- 3
moving_average <- cumsum(time_series) / seq_along(time_series)