stack
(Not Recommended) Stack dataset array from multiple variables into single variable
The dataset
data type is not recommended. To work with heterogeneous data,
use the MATLAB^{®}
table
data type instead. See MATLAB
table
documentation for more information.
Syntax
B = stack(A,datavars)
[B,iA] = stack(A,datavars)
B = stack(A,datavars,Parameter
,value
)
Description
B = stack(A,datavars)
stacks multiple variables in dataset array
A
into a single variable in B
. In general,
B
contains fewer variables but more observations than
A
.
datavars
specifies a group of m
data variables
in A
. stack
creates a single data variable in
B
by interleaving their values, and if A
has
n
observations, then B
has
m
byn
observations. In other words,
stack
takes the m
data values from each
observation in A
and stacks them up to create m
observations in B
. datavars
is a positive integer,
a vector of positive integers, a character vector, a string array, a cell array of
character vectors, or a logical vector. stack
also creates a grouping
variable in B
to indicate which of the m
data
variables in A
each observation in B
corresponds
to.
stack
assigns values for the "pervariable properties (e.g.,
Units
and
VarDescription
) for the new data variable in B
from
the corresponding property values for the first variable listed in
datavars
.
stack
copies the remaining variables from A
to
B
without stacking, by replicating each of their values
m
times. These variables are typically grouping variables.
Because their values are constant across each group of m
observations
in B
, they identify which observation in A
an
observation in B
came from.
[B,iA] = stack(A,datavars)
returns an index vector
iA
indicating the correspondence between observations in
B
and those in A
. stack
creates B(j,:)
using A(iA(j),datavarss)
.
For more information on grouping variables, see Grouping Variables.
Input Arguments
B = stack(A,datavars,
uses the following parameter name/value pairs to control how Parameter
,value
)stack
converts variables in A
to variables in
B
:
'ConstVars'  Variables in A to copy to B
without stacking. ConstVars is a positive
integer, a vector of positive integers, a character vector, a string
array, a cell array of character vectors, or a logical vector. The
default is all variables in A not specified in
datavars . 
'NewDataVarName'  A name for the data variable to be created in
B . The default is a concatenation of the
names of the m variables that are stacked up.

'IndVarName'  A name for the grouping variable to create in
B to indicate the source of each value in the
new data variable. The default is based on the
'NewDataVarName' parameter. 
You can also specify multiple groups of data variables in
A
, each of which becomes a variable in B
. All
groups must contain the same number of variables. Use a string array or cell array of
character vectors to contain multiple parameter values for datavars
or to contain multiple values for 'NewDataVarName'
.
Examples
Combine several variables for estimated influenza rates into a single variable. Then unstack the estimated influenza rates by date.
load flu % FLU has a 'Date' variable, and 10 variables for estimated influenza rates % (in 9 different regions, estimated from Google searches, plus a % nationwide estimate from the CDC). Combine those 10 variables into an % array that has a single data variable, 'FluRate', and an indicator % variable, 'Region', that says which region each estimate is from. [flu2,iflu] = stack(flu, 2:11, 'NewDataVarName','FluRate', ... 'IndVarName','Region') % The second observation in FLU is for 10/16/2005. Find the observations % in FLU2 that correspond to that date. flu(2,:) flu2(iflu==2,:) % Use the 'Date' variable from that array to split 'FluRate' into 52 % separate variables, each containing the estimated influenza rates for % each unique date. The new array has one observation for each region. In % effect, this is the original array FLU "on its side". dateNames = cellstr(datestr(flu.Date,'mmm_DD_YYYY')); [flu3,iflu2] = unstack(flu2, 'FluRate', 'Date', ... 'NewDataVarNames',dateNames) % Since observations in FLU3 represent regions, IFLU2 indicates the first % occurrence in FLU2 of each region. flu2(iflu2,:)