Package 'naflex'

Check missing values conditions

Description

na_check checks conditions on missing values in a vector. If all the checks pass it returns TRUE, otherwise FALSE.

Usage

na_check(
  x,
  prop = NULL,
  n = NULL,
  consec = NULL,
  n_non = NULL,
  prop_strict = FALSE
)

Arguments

x	Vector to check the missing values properties of.
prop	The maximum proportion (0 to 1) of missing values allowed.
n	The maximum number of missing values allowed.
consec	The maximum number of consecutive missing values allowed.
n_non	The minimum number of non-missing values required.
prop_strict	A logical (default FALSE) indicating if the proportion of missing values must be strictly less than prop (prop_strict = TRUE) or only less than prop (prop_strict = FALSE).

Details

There are four type of checks available:

• a maximum proportion of missing values allowed (prop)

• a maximum number of missing values allowed (n)

• a maximum number of consecutive missing values allowed (consec), and

• a minimum number of non-missing values required (n_non).

Any number of checks may be specified, including none. If multiple checks are specified, they must all pass in order to return TRUE. If no checks are specified then TRUE is returned, since this is considered as "all" checks passing.

Value

TRUE if all specified checks pass, and FALSE otherwise.

Examples

x <- c(1:3, NA, NA, NA, 4, NA, NA, 3)
# check if no more than 50% of values are missing
na_check(x, prop = 0.5)
# check if no more than 50% of values are missing
# and if there are no more than 2 consecutive missing values.
na_check(x, prop = 0.5, consec = 2)

---

Check missing values conditions (single condition)

Description

These set of functions check a condition on missing values in a vector x. They return TRUE if check passes, and FALSE otherwise. They are special cases of na_check, which is the general case for specifying multiple checks.

Usage

na_check_prop(x, prop = NULL, strict = FALSE)

na_check_n(x, n = NULL)

na_check_consec(x, consec = NULL)

na_check_non_na(x, n_non = NULL)

Arguments

x	Vector to check the missing values properties of.
prop	The maximum proportion (0 to 1) of missing values allowed.
strict	A logical (default FALSE) indicating if the proportion of missing values must be strictly less than prop (strict = TRUE) or only less than prop (strict = FALSE).
n	The maximum number of missing values allowed.
consec	The maximum number of consecutive missing values allowed.
n_non	The minimum number of non-missing values required.

Details

These functions replicate the functionality of na_check as individual functions for single checks.

For example, na_check_n(x, 5) is equivalent to na_check(x, n = 5).

This more restricted form may be desirable when only a single check is required.

Value

These functions return TRUE if the check passes, and FALSE otherwise.

They are convenient wrapper functions for:

• na_prop(x) <= prop or na_prop(x) < prop (if strict = TRUE)

• na_n(x) <= n

• na_consec(x) <= consec

• na_non_na(x) >= n_non

Examples

na_check_prop(c(1, 2, NA, 4), 0.6)

na_check_prop(c(1, 2, NA, 4), 0.4)

na_check_prop(c(1:10, NA), 0.1)

na_check_prop(c(1:9, NA), 0.1, strict = TRUE)

na_check_n(c(1, 2, NA, 4, NA, NA, 7), 5)

na_check_n(c(1:9, NA, NA, NA), 2)

na_check_consec(c(1, NA, NA, NA, 2, NA, NA, 7), 4)

na_check_consec(c(rep(NA, 5), 1:2, rep(NA, 6)), 5)

na_check_non_na(c(1, 2, NA, 4, NA, NA, 7), 5)

na_check_non_na(c(1:9, NA, NA, NA), 2)

---

Conditionally omit missing values

Description

na_omit_if removes missing values from x if the specified checks are satisfied, and returns x unmodified otherwise. When used within summary functions, na_omit_if provides greater flexibility than the na.rm option e.g. sum(na_omit_if(x, prop = 0.05)).

Usage

na_omit_if(
  x,
  prop = NULL,
  n = NULL,
  consec = NULL,
  n_non = NULL,
  prop_strict = FALSE
)

Arguments

x	Vector to omit missing values in if checks pass.
prop	The maximum proportion (0 to 1) of missing values allowed.
n	The maximum number of missing values allowed.
consec	The maximum number of consecutive missing values allowed.
n_non	The minimum number of non-missing values required.
prop_strict	A logical (default FALSE) indicating if the proportion of missing values must be strictly less than prop (prop_strict = TRUE) or only less than prop (prop_strict = FALSE).

Details

There are four type of checks available:

• a maximum proportion of missing values allowed (prop)

• a maximum number of missing values allowed (n)

• a maximum number of consecutive missing values allowed (consec), and

• a minimum number of non-missing values required (n_non).

Any number of checks may be specified, including none. If multiple checks are specified, they must all pass in order for missing values to be omitted. If no checks are specified then missing values are omitted, since this is considered as "all" checks passing.

Value

A vector of the same type as x. Either x with missing values removed if all checks pass, or x unmodified if any checks fail.

For consistency with na.omit, if missing values are removed, the indices of the removed values form an na.action attribute of class omit in the result.

If missing values are not removed (because the checks failed or there were no missing values in x) then no na.action attribute is added.

Examples

x <- c(1, 3, NA, NA, NA, 4, 2, NA, 4, 6)

sum(na_omit_if(x, prop = 0.45, n = 10, consec = 5))
sum(na_omit_if(x, prop = 0.45))

require(magrittr)
sum(x %>% na_omit_if(prop = 0.45))

# WMO specification for calculating monthly values from daily data
daily_rain <- rnorm(30)
daily_rain[c(3, 5, 6, 7, 8, 9, 24, 28)] <- NA
sum(daily_rain %>% na_omit_if(n = 10, consec = 4))

---

Conditionally omit missing values (single condition)

Description

These set of functions remove missing values from x if the single, specified check is satisfied, and returns x unmodified otherwise. They are special cases of na_omit_if, which is the general case for specifying multiple checks.

Usage

na_omit_if_prop(x, prop = NULL, strict = FALSE)

na_omit_if_n(x, n = NULL)

na_omit_if_consec(x, consec = NULL)

na_omit_if_non_na(x, n_non = NULL)

Arguments

x	Vector to omit missing values in if checks pass.
prop	The maximum proportion (0 to 1) of missing values allowed.
strict	A logical (default FALSE) indicating if the proportion of missing values must be strictly less than prop (strict = TRUE) or only less than prop (strict = FALSE).
n	The maximum number of missing values allowed.
consec	The maximum number of consecutive missing values allowed.
n_non	The minimum number of non-missing values required.

Details

These functions replicate the functionality of na_omit_if as individual functions for single checks.

For example, na_omit_if_consec(x, 4) is equivalent to na_omit_if(x, consec = 4).

This more restricted form may be desirable when only a single check is required.

Value

A vector of the same type as x. Either x with missing values removed if all checks pass, or x unmodified if any checks fail.

For consistency with na.omit, if missing values are removed, the indices of the removed values form an na.action attribute of class omit in the result.

If missing values are not removed (because the checks failed or there were no missing values in x) then no na.action attribute is added.

---

Calculate missing value properties

Description

A set of functions for calculating missing values properties of a vector.

• na_prop: The proportion of missing values

• na_n: The number of missing values

• na_consec: The maximum number of consecutive missing values

• na_non_na: The number of non-missing values

Usage

na_prop(x)

na_n(x)

na_consec(x)

na_non_na(x)

Arguments

x	A vector to calculate the missing values property of.

Details

These functions are used by na_omit_if to omit missing values conditionally on the value of these properties. They are also useful summaries in their own right.

Value

Each function returns a number: a proportion (0 to 1) or a count.

Examples

na_prop(c(1, 2, NA, 4))

na_prop(c(1:9, NA))

na_n(c(1, 2, NA, 4, NA, NA, 7))

na_n(c(1:9, NA, NA))

na_consec(c(1, NA, NA, NA, 2, NA, NA, 7))

na_consec(c(rep(NA, 5), 1:2, rep(NA, 6)))

na_non_na(c(1, 2, NA, 4, NA, NA, 7))

na_non_na(c(1:9, NA, NA))

---

naflex: Flexible Options for Handling Missing Values

Description

The naflex package provides additional flexibility for handling missing values in summary functions beyond the two extreme options (na.rm = TRUE/FALSE) available in base R.

Details

Most summary functions in R e.g. mean provide the option for the two extremes:

• calculate the summary ignoring all missing values, na.rm = TRUE, or

• require no missing values for the summary to be calculated, na.rm = FALSE

In many applications something in between these two extremes is often appropriate. For example, you may wish to give a summary statistic if less than 5% of values are missing.

naflex provides helper functions to facilitate this flexibility for dealing with missing values, particularly within summary functions.

In particular naflex provides four types of missing value checks:

• a maximum proportion of missing values allowed

• a maximum number of missing values allowed

• a maximum number of consecutive missing values allowed, and

• a minimum number of non-missing values required.

These checks can be used individually or in combination with each other within summary functions.

Author(s)

Maintainer: Danny Parsons [email protected] (ORCID)

Authors:

• Shadrack Kibet

See Also

Useful links:

• https://github.com/dannyparsons/naflex

• Report bugs at https://github.com/dannyparsons/naflex/issues

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