common (version 1.1.3)

changed: 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)

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.

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.

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