removevars
Delete variables from table or timetable
Syntax
Description
Examples
Remove Variable
Create a table and remove variables one at a time. You can specify variables by name or by position in the table.
Read data from a spreadsheet into a table. Display the first three rows.
T1 = readtable('outages.csv');
head(T1,3)
Region OutageTime Loss Customers RestorationTime Cause _____________ ________________ ______ __________ ________________ ________________ {'SouthWest'} 2002-02-01 12:18 458.98 1.8202e+06 2002-02-07 16:50 {'winter storm'} {'SouthEast'} 2003-01-23 00:49 530.14 2.1204e+05 NaT {'winter storm'} {'SouthEast'} 2003-02-07 21:15 289.4 1.4294e+05 2003-02-17 08:14 {'winter storm'}
Remove the variable that is named Region
.
T2 = removevars(T1,'Region');
head(T2,3)
OutageTime Loss Customers RestorationTime Cause ________________ ______ __________ ________________ ________________ 2002-02-01 12:18 458.98 1.8202e+06 2002-02-07 16:50 {'winter storm'} 2003-01-23 00:49 530.14 2.1204e+05 NaT {'winter storm'} 2003-02-07 21:15 289.4 1.4294e+05 2003-02-17 08:14 {'winter storm'}
Remove the fourth variable from T2
.
T3 = removevars(T2,4); head(T3,3)
OutageTime Loss Customers Cause ________________ ______ __________ ________________ 2002-02-01 12:18 458.98 1.8202e+06 {'winter storm'} 2003-01-23 00:49 530.14 2.1204e+05 {'winter storm'} 2003-02-07 21:15 289.4 1.4294e+05 {'winter storm'}
Specify Multiple Variables
Remove multiple table variables using the removevars
function. You can specify variables by name or by position.
Read data from a spreadsheet into a table.
T1 = readtable('outages.csv');
head(T1,3)
Region OutageTime Loss Customers RestorationTime Cause _____________ ________________ ______ __________ ________________ ________________ {'SouthWest'} 2002-02-01 12:18 458.98 1.8202e+06 2002-02-07 16:50 {'winter storm'} {'SouthEast'} 2003-01-23 00:49 530.14 2.1204e+05 NaT {'winter storm'} {'SouthEast'} 2003-02-07 21:15 289.4 1.4294e+05 2003-02-17 08:14 {'winter storm'}
Remove the variables named Loss
and Customers
. Specify names using a cell array of character vectors.
T2 = removevars(T1,{'Loss','Customers'}); head(T2,3)
Region OutageTime RestorationTime Cause _____________ ________________ ________________ ________________ {'SouthWest'} 2002-02-01 12:18 2002-02-07 16:50 {'winter storm'} {'SouthEast'} 2003-01-23 00:49 NaT {'winter storm'} {'SouthEast'} 2003-02-07 21:15 2003-02-17 08:14 {'winter storm'}
Remove the first and fourth variables, using a numeric array to indicate their positions in T2
.
T3 = removevars(T2,[1 4]); head(T3,3)
OutageTime RestorationTime ________________ ________________ 2002-02-01 12:18 2002-02-07 16:50 2003-01-23 00:49 NaT 2003-02-07 21:15 2003-02-17 08:14
Input Arguments
T1
— Input table
table | timetable
Input table, specified as a table or timetable.
vars
— Variables in input table
string array | character vector | cell array of character vectors | pattern
scalar | numeric array | logical array | subscript object
Variables in the input table, specified as a string array, character
vector, cell array of character vectors, pattern
scalar, numeric array, logical array, or subscript
object.
You can specify vars
as a subscript object that detects
variables of a specified data type by using the vartype
function.
Example: T2 = removevars(T1,2)
removes the second table
variable.
Example: T2 = removevars(T1,'Date')
removes the table
variable named Date
.
Example: T2 =
removevars(T1,{'Latitude','Longitude','Elevation'})
removes
the table variables named Latitude
,
Longitude
, and
Elevation
.
Example: vars = vartype('numeric'); T =
removevars(T,vars)
removes all of the numeric variables in
T
.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
The
removevars
function fully supports tall arrays. For more information,
see Tall Arrays.
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
The
vars
input argument does not support pattern expressions.
Thread-Based Environment
Run code in the background using MATLAB® backgroundPool
or accelerate code with Parallel Computing Toolbox™ ThreadPool
.
This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.
Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced in R2018a
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