| changed {common} | R Documentation |
Identify changed values
Description
The changed function identifies changes in a vector or
data frame. The function is used to locate grouping boundaries. It will
return a TRUE each time the current value is different from the previous
value. The changed function is similar to the Base R duplicated
function, except the changed function will return TRUE even if
the changed value is not unique.
Usage
changed(x, reverse = FALSE, simplify = FALSE)
Arguments
x |
A vector of values in which to identify changed values. Also accepts a data frame. In the case of a data frame, the function will use all columns. Input data can be any data type. |
reverse |
Reverse the direction of the scan to identify the last value in a group instead of the first. |
simplify |
If the input data to the function is a data frame, the simplify option will return a single vector of indicator values instead of a data frame of indicator values. |
Details
For a data frame, by default, the function will return another data frame with an equal number of change indicator columns. The column names will be the original column names, with a ".changed" suffix.
To collapse the multiple change indicators into one vector, use the "simplify" option. In this case, the returned vector will essentially be an "or" operation across all columns.
Value
A vector of TRUE or FALSE values indicating the grouping boundaries of the vector or data frame. If the input data is a data frame and the "simplify" parameter is FALSE, the return value will be a data frame of logical vectors describing changed values for each column.
Examples
# Create sample vector
v1 <- c(1, 1, 1, 2, 2, 3, 3, 3, 1, 1)
# Identify changed values
res1 <- changed(v1)
# View results
res1
# [1] TRUE FALSE FALSE TRUE FALSE TRUE FALSE FALSE TRUE FALSE
# Create sample data frame
v2 <- c("A", "A", "A", "A", "A", "A", "B", "B", "B", "B")
dat <- data.frame(v1, v2)
# View original data frame
dat
# v1 v2
# 1 1 A
# 2 1 A
# 3 1 A
# 4 2 A
# 5 2 A
# 6 3 A
# 7 3 B
# 8 3 B
# 9 1 B
# 10 1 B
# Get changed values for each column
res2 <- changed(dat)
# View results
res2
# v1.changed v2.changed
# 1 TRUE TRUE
# 2 FALSE FALSE
# 3 FALSE FALSE
# 4 TRUE FALSE
# 5 FALSE FALSE
# 6 TRUE FALSE
# 7 FALSE TRUE
# 8 FALSE FALSE
# 9 TRUE FALSE
# 10 FALSE FALSE
# Get changed values for all columns
res3 <- changed(dat, simplify = TRUE)
# View results
res3
# [1] TRUE FALSE FALSE TRUE FALSE TRUE TRUE FALSE TRUE FALSE
# Get last items in each group instead of first
res4 <- changed(dat, reverse = TRUE)
# View results
res4
# v1.changed v2.changed
# 1 FALSE FALSE
# 2 FALSE FALSE
# 3 TRUE FALSE
# 4 FALSE FALSE
# 5 TRUE FALSE
# 6 FALSE TRUE
# 7 FALSE FALSE
# 8 TRUE FALSE
# 9 FALSE FALSE
# 10 TRUE TRUE