rmmissing
statistics: R = rmmissing (A)
statistics: R = rmmissing (A, dim)
statistics: R = rmmissing (…, Name, Value)
statistics: [R, TF] = rmmissing (…)
Remove missing data from arrays.
Given an input vector or matrix (2-D array) A, R =
rmmissing (A) returns an output vector or matrix R of the same
type as input A and any missing elements removed. If A is a
vector, missing elements are removed individually, if A is a matrix,
then rows containing missing elements are removed.
Standard missing values and their corresponding data types are:
NaN - for double, single, duration, and
calendarDuration arrays.
NaT - for datetime arrays.
<missing> - for string arrays.
<undefined> - for categorical arrays.
{0x0 char} - for cell arrays of character vectors.
For any data types that do not support missing values, rmmissing
returns R == A and if a second output argument is
requested it also returns TF = false (size (A)).
Given an input matrix (2-D array) A, R = rmmissing
(A, dim) further specifies whether rows or columns containing
missing data are removed from the output R based on the value of
dim, which must be either 1 or 0.
1: remove rows.
2: remove columns.
R = rmmissing (…, Name, Value) also accepts
the following paired arguments.
| Name | Value | |
|---|---|---|
'MinNumMissing' | A positive integer scalar value specifying the required minimum number of missing values for removing any particular row or column from a matrix input. Note that this argument is ignored if input A is a vector. | |
'MissingLocations' | A logical array of the same size
as input A indexing the locations of missing values in input array
A. Note that specifying 'MissingLocations' overrides any
standard missing values in A. |
Optional return value TF is a logical array where true values
represent removed entries, rows or columns from the original data A.
See also: fillmissing, ismissing, standardizeMissing
Source Code: rmmissing