Access Data in Tables
A table is a container that stores column-oriented data in variables. Table variables can have different data types and sizes as long as all variables have the same number of rows. Table variables have names, just as the fields of a structure have names. The rows of a table can have names, but row names are not required. To access table data, index into the rows and variables using either their names or numeric indices.
Typical reasons for indexing into tables include:
Reordering or removing rows and variables.
Adding arrays as new rows or variables.
Extracting arrays of data to use as input arguments to functions.
Summary of Table Indexing Syntaxes
Depending on the type of indexing you use, you can access either a subtable or an array extracted from the table. Indexing with:
Smooth parentheses, (), returns a table that has selected rows and variables.
Dot notation returns the contents of a variable as an array.
Curly braces, {}, returns an array concatenated from the contents of selected rows and variables.
You can specify rows and variables by name, numeric index, or data type.
Starting in R2019b, variable names and row names can include any characters, including spaces and non-ASCII characters. Also, they can start with any characters, not just letters. Variable and row names do not have to be valid MATLAB® identifiers (as determined by the
isvarnamefunction).Starting in R2022a, when you specify rows and variables by name, you can use a
patternobject to specify names. For example,"Var" + digitsPatternmatches all names that start withVarand end with any number of digits.
Type of Output | Syntax | Rows | Variables | Examples |
|---|---|---|---|---|
Table, containing specified rows and variables |
| Specified as:
| Specified as:
|
|
Table, containing variables that have specified data type |
| Specified as:
| Specified as a data type, such as |
|
Array, extracting data from one variable |
| Not specified | Specified as:
|
|
Array, extracting data from one variable and specified rows |
| Specified as numeric or logical indices of the array | Specified as:
|
|
Array, concatenating data from specified rows and variables |
| Specified as:
| Specified as:
|
|
Array, concatenating data from specified rows and variables with specified data type |
| Specified as:
| Specified as a data type, such as |
|
Array, concatenating data from all rows and variables |
| Not specified | Not specified |
|
Table Indexing with Specified Rows and Variables
Load sample data for 100 patients from the patients MAT-file to workspace variables.
load patients
whosName Size Bytes Class Attributes Age 100x1 800 double Diastolic 100x1 800 double Gender 100x1 11412 cell Height 100x1 800 double LastName 100x1 11616 cell Location 100x1 14208 cell SelfAssessedHealthStatus 100x1 11540 cell Smoker 100x1 100 logical Systolic 100x1 800 double Weight 100x1 800 double
Create a table and populate it with the Age, Height, Weight, Smoker, and SelfAssessedHealthStatus workspace variables. Use the unique identifiers in LastName as row names. T is a 100-by-5 table, with 100 rows and five variables. (When you specify a vector of row names, it does not count as a table variable). Also, convert SelfAssessedHealthStatus to a categorical variable because it contains only the unique values Excellent, Good, Fair, and Poor. It can be useful to treat a variable as a categorical array when it has a fixed set of values that you can think of as categories.
SelfAssessedHealthStatus = categorical(SelfAssessedHealthStatus); T = table(Age,Height,Weight,Smoker,SelfAssessedHealthStatus,... 'RowNames',LastName)
T=100×5 table
Age Height Weight Smoker SelfAssessedHealthStatus
___ ______ ______ ______ ________________________
Smith 38 71 176 true Excellent
Johnson 43 69 163 false Fair
Williams 38 64 131 false Good
Jones 40 67 133 false Fair
Brown 49 64 119 false Good
Davis 46 68 142 false Good
Miller 33 64 142 true Good
Wilson 40 68 180 false Good
Moore 28 68 183 false Excellent
Taylor 31 66 132 false Excellent
Anderson 45 68 128 false Excellent
Thomas 42 66 137 false Poor
Jackson 25 71 174 false Poor
White 39 72 202 true Excellent
Harris 36 65 129 false Good
Martin 48 71 181 true Good
⋮
Index Using Numeric Indices or end Keyword
Create a subtable containing the first five rows and all the variables from T. To specify the desired rows and variables, use numeric indices within parentheses. This type of indexing is similar to indexing into numeric arrays.
firstRows = T(1:5,:)
firstRows=5×5 table
Age Height Weight Smoker SelfAssessedHealthStatus
___ ______ ______ ______ ________________________
Smith 38 71 176 true Excellent
Johnson 43 69 163 false Fair
Williams 38 64 131 false Good
Jones 40 67 133 false Fair
Brown 49 64 119 false Good
You can also use the end keyword to mean the last row or variable. Use the end keyword to index into the last five rows of the table.
lastRows = T(end-4:end,:)
lastRows=5×5 table
Age Height Weight Smoker SelfAssessedHealthStatus
___ ______ ______ ______ ________________________
Alexander 25 69 171 true Good
Russell 44 69 188 true Good
Griffin 49 70 186 false Fair
Diaz 45 68 172 true Good
Hayes 48 66 177 false Fair
In addition to numeric indices, you can use row or variable names inside the parentheses. (In this case, using row indices and a colon is more compact than using row or variable names.)
Index Using Names
Select all the data for the patients with the last names Griffin, Diaz, and Hayes. Since T has row names that are the last names of patients, index into T using row names.
rowsByName = T(["Griffin","Diaz","Hayes"],:)
rowsByName=3×5 table
Age Height Weight Smoker SelfAssessedHealthStatus
___ ______ ______ ______ ________________________
Griffin 49 70 186 false Fair
Diaz 45 68 172 true Good
Hayes 48 66 177 false Fair
You also can select variables by name. Create a table that has only the first five rows of T and the Height and Weight variables. Display it.
variablesByName = T(1:5,["Height","Weight"])
variablesByName=5×2 table
Height Weight
______ ______
Smith 71 176
Johnson 69 163
Williams 64 131
Jones 67 133
Brown 64 119
Table variable names do not have to be valid MATLAB identifiers. They can include spaces and non-ASCII characters, and can start with any character.
For example, rename the SelfAssessedHealthStatus variable by using the renamevars function. Add spaces and a dash to make that variable name more readable. Then index into T using variable names.
T = renamevars(T,"SelfAssessedHealthStatus","Self-Assessed Health Status"); T(1:5,["Age","Smoker","Self-Assessed Health Status"])
ans=5×3 table
Age Smoker Self-Assessed Health Status
___ ______ ___________________________
Smith 38 true Excellent
Johnson 43 false Fair
Williams 38 false Good
Jones 40 false Fair
Brown 49 false Good
Specify Row or Variable Names Using Patterns
When you specify table row or variable names, you can use a pattern that defines a rule for matching text. For example, you can match variable names that start with "Var" followed by any digits. You can build pattern expressions using pattern objects, strings, and operators.
For example, index into T by row name to find all rows where the last name of the patient begins with the letter G. To match any letters after G use the wildcardPattern function.
beginsWithG = "G" + wildcardPatternbeginsWithG = pattern
Matching:
"G" + wildcardPattern
T(beginsWithG,:)
ans=6×5 table
Age Height Weight Smoker Self-Assessed Health Status
___ ______ ______ ______ ___________________________
Garcia 27 69 131 true Fair
Green 44 71 193 false Good
Gonzalez 35 66 118 false Fair
Gray 31 64 130 false Excellent
Gonzales 48 71 174 false Good
Griffin 49 70 186 false Fair
Index into T by variable name to find any name that contains Status as part of the name.
containsStatus = wildcardPattern + "Status" + wildcardPattern;
T(1:5,containsStatus)ans=5×1 table
Self-Assessed Health Status
___________________________
Smith Excellent
Johnson Fair
Williams Good
Jones Fair
Brown Good
Index by Data Type of Variables
Instead of specifying variables using names or numbers, you can create a data type subscript that matches all variables having the same data type.
First, create a data type subscript to match numeric table variables by using the vartype function.
subscriptObject = vartype("numeric")subscriptObject = table vartype subscript: Select table variables matching the type 'numeric' See Access Data in a Table.
Create a table that has only the numeric variables from T. The Smoker variable is a logical variable and Self-Assessed Health Status is a categorical variable so they are excluded.
onlyNumericVariables = T(:,subscriptObject)
onlyNumericVariables=100×3 table
Age Height Weight
___ ______ ______
Smith 38 71 176
Johnson 43 69 163
Williams 38 64 131
Jones 40 67 133
Brown 49 64 119
Davis 46 68 142
Miller 33 64 142
Wilson 40 68 180
Moore 28 68 183
Taylor 31 66 132
Anderson 45 68 128
Thomas 42 66 137
Jackson 25 71 174
White 39 72 202
Harris 36 65 129
Martin 48 71 181
⋮
Find Rows Where Values Meet Logical Conditions
Create another, smaller table from the data in the patients MAT-file.
load patients.mat
T = table(Age,Height,Weight,Smoker);To find the rows of a table where values meet a logical condition, use logical indexing. First use dot notation to access table variables. Then you can create an array of logical indices where values in the variables meet a condition that you specify. Index into the table using the logical indices.
Extract Data from Table Variable Using Dot Notation
To extract data from a table variable, use dot notation.
For example, plot a histogram of numeric values from the table variable Weight. With dot notation, you can treat T.Weight as a numeric array. T.Weight is a double-precision column vector with 100 rows.
histogram(T.Weight)
title("Patient Weights")
Index into Rows That Meet Logical Conditions
You can index into an array or a table using an array of logical indices. Typically, you use a logical expression that determines which values in a table variable meet a logical condition. The result of the expression is an array of logical indices.
For example, create logical indices matching patients whose age is less than 40.
rows = T.Age < 40
rows = 100x1 logical array
1
0
1
0
0
0
1
0
1
1
⋮
To extract heights for patients whose age is less than 40, index into the Height variable using rows. There are 56 patients younger than 40.
T.Height(rows)
ans = 56×1
71
64
64
68
66
71
72
65
69
69
⋮
You can index into a table with logical indices. Display the rows of T for the patients who are younger than 40.
T(rows,:)
ans=56×4 table
Age Height Weight Smoker
___ ______ ______ ______
38 71 176 true
38 64 131 false
33 64 142 true
28 68 183 false
31 66 132 false
25 71 174 false
39 72 202 true
36 65 129 false
32 69 191 true
27 69 131 true
37 70 179 false
39 64 117 false
28 65 123 true
25 70 189 false
39 63 143 false
25 63 114 false
⋮
You can match multiple conditions with one logical expression. Display the rows for smoking patients younger than 40.
rows = (T.Smoker==true & T.Age<40); T(rows,:)
ans=18×4 table
Age Height Weight Smoker
___ ______ ______ ______
38 71 176 true
33 64 142 true
39 72 202 true
32 69 191 true
27 69 131 true
28 65 123 true
30 67 186 true
33 66 180 true
39 71 164 true
37 70 194 true
33 67 115 true
31 72 178 true
28 69 189 true
39 68 182 true
37 65 120 true
31 66 141 true
⋮
Dot Notation with Any Variable Name or Expression
When you index using dot notation, there are two ways to specify a variable.
By name, without quotation marks. For example,
T.Datespecifies a variable named"Date".By an expression, where the expression is enclosed by parentheses after the dot. For example,
T.("Start Date")specifies a variable named"Start Date".
Use the first syntax when a table variable name also happens to be a valid MATLAB® identifier. (A valid identifier starts with a letter and includes only letters, digits, and underscores.)
Use the second syntax when you specify:
A number that indicates the position of the variable in the table.
A variable name that isn't a valid MATLAB identifier.
A function whose output is the name of a variable in the table, or a variable you add to the table. The output of the function must be a character vector or a string scalar.
For example, create a table from the patients MAT-file. Then use dot notation to access the contents of table variables.
load patients
T = table(Age,Height,Weight,Smoker);To specify a variable by position in the table, use a number. Age is the first variable in T, so use the number 1 to specify its position.
T.(1)
ans = 100×1
38
43
38
40
49
46
33
40
28
31
⋮
To specify a variable by name, either specify it after the dot or enclose it in quotation marks and parentheses. Since Age is a valid identifier, you can specify it using either T.Age or T.("Age").
T.Age
ans = 100×1
38
43
38
40
49
46
33
40
28
31
⋮
You can specify table variable names that are not valid MATLAB identifiers. Variable names can include spaces and non-ASCII characters, and can start with any character. However, when you use dot notation to access a table variable with such a name, you must specify it using quotation marks and parentheses.
For example, add a variable name with spaces and a hyphen to T.
SelfAssessedHealthStatus = categorical(SelfAssessedHealthStatus); T = addvars(T,SelfAssessedHealthStatus,'NewVariableNames',"Self-Assessed Health Status"); T(1:5,:)
ans=5×5 table
Age Height Weight Smoker Self-Assessed Health Status
___ ______ ______ ______ ___________________________
38 71 176 true Excellent
43 69 163 false Fair
38 64 131 false Good
40 67 133 false Fair
49 64 119 false Good
Access the new table variable using dot notation. Display the first five elements.
healthStatus = T.("Self-Assessed Health Status");
healthStatus(1:5)ans = 5x1 categorical
Excellent
Fair
Good
Fair
Good
You also can use the output of a function as a variable name. Delete the T.("Self-Assessed Health Status") variable. Then replace it with a variable whose name includes the current date.
T.("Self-Assessed Health Status") = []; T.(string(datetime("today")) + " Self Report") = SelfAssessedHealthStatus; T(1:5,:)
ans=5×5 table
Age Height Weight Smoker 26-Feb-2022 Self Report
___ ______ ______ ______ _______________________
38 71 176 true Excellent
43 69 163 false Fair
38 64 131 false Good
40 67 133 false Fair
49 64 119 false Good
Extract Data from Specified Rows and Variables
Indexing with curly braces extracts data from a table and results in an array, not a subtable. But other than that difference, you can specify rows and variables using numbers, names, and data type subscripts, just as you can when you index using smooth parentheses. To extract values from a table, use curly braces. If you extract values from multiple table variables, then the variables must have data types that allow them to be concatenated together.
Specify Rows and Variables
Create a table from numeric and logical arrays from the patients file.
load patients T = table(Age,Height,Weight,Smoker,... 'RowNames',LastName);
Extract data from multiple variables in T. Unlike dot notation, indexing with curly braces can extract values from multiple table variables and concatenate them into one array.
Extract the height and weight for the first five patients. Use numeric indices to select the first five rows, and variable names to select the variables Height and Weight.
A = T{1:5,["Height","Weight"]}A = 5×2
71 176
69 163
64 131
67 133
64 119
A is a 5-by-2 numeric array, not a table.
If you specify one variable name, then curly brace indexing results in the same array you can get with dot notation. However, you must specify both rows and variables when you use curly brace indexing. For example, the syntaxes T.Height and T{:,"Height"} return the same array.
Extract Data from All Rows and Variables
If all the table variables have data types that allow them to be concatenated together, then you can use the T.Variables syntax to put all the table data into an array. This syntax is equivalent to T{:,:} where the colons indicate all rows and all variables. If the table has row names, they are not included in the output from T.Variables. Row names are not stored in a table variable. Row names are part of the metadata that describes a table.
A2 = T.Variables
A2 = 100×4
38 71 176 1
43 69 163 0
38 64 131 0
40 67 133 0
49 64 119 0
46 68 142 0
33 64 142 1
40 68 180 0
28 68 183 0
31 66 132 0
⋮
See Also
table | histogram | addvars | vartype | renamevars
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