Package 'lest'

A general vectorised if

Description

This function allows you to vectorise multiple if and ⁠else if⁠ statements. It is an R equivalent of the SQL ⁠CASE WHEN⁠ statement.

Usage

case_when(...)

Arguments

...

A sequence of two-sided formulas. The left hand side (LHS) determines which values match this case. The right hand side (RHS) provides the replacement value. The LHS must evaluate to a logical vector. The RHS does not need to be logical, but all RHSs must evaluate to the same type of vector. Both LHS and RHS may have the same length of either 1 or n. The value of n must be consistent across all cases. The case of n == 0 is treated as a variant of n != 1.

Value

A vector of length 1 or n, matching the length of the logical input or output vectors, with the type (and attributes) of the first RHS. Inconsistent lengths or types will generate an error.

Examples

x <- 1:50
case_when(
  x %% 35 == 0 ~ "fizz buzz",
  x %% 5 == 0 ~ "fizz",
  x %% 7 == 0 ~ "buzz",
  TRUE ~ as.character(x)
)

# Like an if statement, the arguments are evaluated in order, so you must
# proceed from the most specific to the most general. This won't work:
case_when(
  TRUE ~ as.character(x),
  x %%  5 == 0 ~ "fizz",
  x %%  7 == 0 ~ "buzz",
  x %% 35 == 0 ~ "fizz buzz"
)

# All RHS values need to be of the same type. Inconsistent types will throw an error.
# This applies also to NA values used in RHS: NA is logical, use
# typed values like NA_real_, NA_complex, NA_character_, NA_integer_ as appropriate.
case_when(
  x %% 35 == 0 ~ NA_character_,
  x %% 5 == 0 ~ "fizz",
  x %% 7 == 0 ~ "buzz",
  TRUE ~ as.character(x)
)
case_when(
  x %% 35 == 0 ~ 35,
  x %% 5 == 0 ~ 5,
  x %% 7 == 0 ~ 7,
  TRUE ~ NA_real_
)
# This throws an error as NA is logical not numeric
try({
case_when(
  x %% 35 == 0 ~ 35,
  x %% 5 == 0 ~ 5,
  x %% 7 == 0 ~ 7,
  TRUE ~ NA
)
})
dat <- iris[1:5, ]
dat$size <- case_when(
  dat$Sepal.Length < 5.0 ~ "small",
  TRUE ~ "big"
)
dat

---

Cumulative all and any

Description

Cumulative all and any

Usage

cumall(x)

cumany(x)

Arguments

x	a logical vector.

Value

a logical vector

Examples

cumall(c(TRUE, TRUE, NA, TRUE, FALSE))
cumany(c(FALSE, FALSE, NA, TRUE, FALSE))

---

Check When the Tumbling Sum of a Vector Exceeds a Threshold

Description

The tumbling sum is calculated as the partial cumulative sum of a vector until a threshold is exceeded. Once this happens, the tumbling sum is calculated from zero again. exceeds_tumbling_sum() returns TRUE whenever this threshold is hit/exceeded and FALSE otherwise.

Usage

exceeds_tumbling_sum(x, threshold, inclusive = TRUE)

Arguments

x	a numeric vector
threshold	a numeric scalar
inclusive	a logical scalar. If TRUE inclusive bounds are used (i.e. the threshold is checked with >=), otherwise exclusive

Details

This is for example useful if you have high frequency GPS positions and want to keep only points that are at least x seconds apart.

Value

a logical vector of the same length as x that is TRUE whenever threshold was exceeded and FALSE otherwise

See Also

MESS::cumsumbinning() does something very similar, but returns group indices instead of a logical vector.

Examples

exceeds_tumbling_sum(c(1, 3, 3, 3), 4)

---

Vectorised if

Description

Compared to the base ifelse(), this function is more strict. It checks that true and false are the same type. This strictness makes the output type more predictable, and makes it somewhat faster.

Usage

if_else(condition, true, false, missing = NULL)

Arguments

condition	Logical vector
true, false	Values to use for TRUE and FALSE values of condition. They must be either the same length as condition, or length 1. They must also be the same type: if_else() checks that they have the same type and same class. All other attributes are taken from true.
missing	If not NULL, will be used to replace missing values.

Value

Where condition is TRUE, the matching value from true, where it's FALSE, the matching value from false, otherwise NA.

Examples

x <- c(-5:5, NA)
if_else(x < 0, NA_integer_, x)
if_else(x < 0, "negative", "positive", "missing")

# Unlike ifelse, if_else preserves types
x <- factor(sample(letters[1:5], 10, replace = TRUE))
ifelse(x %in% c("a", "b", "c"), x, factor(NA))
if_else(x %in% c("a", "b", "c"), x, factor(NA))
# Attributes are taken from the `true` vector,

---