summary
Print summary of table, timetable, or categorical array
Description
summary(
prints a summary of the table or
timetable T
)T
.
If
T
is a table, then the table summary displays the description fromT.Properties.Description
followed by a summary of the table variables.If
T
is a timetable, then the timetable summary displays the description fromT.Properties.Description
, a summary of the row times, and then a summary of the timetable variables.
summary(
prints a summary of the
categorical array A
)A
.
If
A
is a vector, thensummary(A)
displays the category names along with the number of elements in each category (the category counts). It also displays the number of elements that are undefined.If
A
is a matrix, thensummary
treats the columns ofA
as vectors and displays the category counts for each column ofA
.If
A
is a multidimensional array, thensummary
acts along the first array dimension whose size does not equal1
.
Examples
Summary of Table
Create a table.
load patients BloodPressure = [Systolic Diastolic]; T = table(Gender,Age,Smoker,BloodPressure,'RowNames',LastName);
Add descriptions and units to table T
. You can add a description for the table as a whole, and also for individual variables.
T.Properties.Description = 'Simulated patient data'; T.Properties.VariableUnits = {'' 'Yrs' '' 'mm Hg'}; T.Properties.VariableDescriptions{4} = 'Systolic/Diastolic';
Print a summary of table T
.
format compact
summary(T)
Description: Simulated patient data Variables: Gender: 100x1 cell array of character vectors Age: 100x1 double Properties: Units: Yrs Values: Min 25 Median 39 Max 50 Smoker: 100x1 logical Values: True 34 False 66 BloodPressure: 100x2 double Properties: Units: mm Hg Description: Systolic/Diastolic Values: Column 1 Column 2 ________ ________ Min 109 68 Median 122 81.5 Max 138 99
summary
displays the minimum, median, and maximum values for each column of the variable BloodPressure
.
Summary of Timetable
Create a small timetable.
Time = [seconds(1:5)]'; TT = timetable(Time,[98;97.5;97.9;98.1;97.9],[120;111;119;117;116],... 'VariableNames',{'Reading1','Reading2'})
TT=5×2 timetable
Time Reading1 Reading2
_____ ________ ________
1 sec 98 120
2 sec 97.5 111
3 sec 97.9 119
4 sec 98.1 117
5 sec 97.9 116
Print a summary of the timetable. summary
prints a summary of the row times, followed by a summary of the variables. If the timetable is regular, then summary
also prints the size of the time step between row times.
summary(TT)
RowTimes: Time: 5x1 duration Values: Min 1 sec Median 3 sec Max 5 sec TimeStep 1 sec Variables: Reading1: 5x1 double Values: Min 97.5 Median 97.9 Max 98.1 Reading2: 5x1 double Values: Min 111 Median 117 Max 120
Return Summary of Table as Structure
Create a table. Add units to the table variables. Then display the first few rows.
load patients BloodPressure = [Systolic Diastolic]; T = table(Gender,Age,Smoker,BloodPressure,'RowNames',LastName); T.Properties.VariableUnits = {'' 'Years' '' 'mm Hg'}; head(T,3)
Gender Age Smoker BloodPressure __________ ___ ______ _____________ Smith {'Male' } 38 true 124 93 Johnson {'Male' } 43 false 109 77 Williams {'Female'} 38 false 125 83
Return a summary of the table. To return a summary as a structure, specify an output argument when using the summary
function.
s = summary(T)
s = struct with fields:
Gender: [1x1 struct]
Age: [1x1 struct]
Smoker: [1x1 struct]
BloodPressure: [1x1 struct]
Display the summary of the table variable Age
. For each variable of T
, the output argument s
has a field that contains its summary.
s.Age
ans = struct with fields:
Size: [100 1]
Type: 'double'
Description: ''
Units: 'Years'
Continuity: []
Min: 25
Median: 39
Max: 50
NumMissing: 0
The NumMissing
field shows the number of elements that are the missing value. In this case, Age
does not contain any NaN
values, so NumMissing
is zero. summary
includes the NumMissing
field for numeric, duration
, datetime
, and categorical
variables.
Display the minimum age contained in the table. You can access any field of the summary by name.
s.Age.Min
ans = 25
Display the summary of the table variable Smoker
. You can determine the numbers of smokers and nonsmokers from the True
and False
fields. The information contained in the summary of a table variable depends on the data type of the variable.
s.Smoker
ans = struct with fields:
Size: [100 1]
Type: 'logical'
Description: ''
Units: ''
Continuity: []
True: 34
False: 66
Return Summary of Timetable as Structure
Create a timetable.
Time = datetime({'20151218 08:00:00';'20151218 10:00:00';'20151218 12:00:00'}); Temp = [37.3;39.1;42.3]; Pressure = [30.1;30.03;29.9]; TT = timetable(Time,Temp,Pressure)
TT=3×2 timetable
Time Temp Pressure
____________________ ____ ________
18Dec2015 08:00:00 37.3 30.1
18Dec2015 10:00:00 39.1 30.03
18Dec2015 12:00:00 42.3 29.9
Return a summary of the timetable as a structure.
s = summary(TT)
s = struct with fields:
Time: [1x1 struct]
Temp: [1x1 struct]
Pressure: [1x1 struct]
Display the summary of the row times. The TimeStep
field shows that the time interval between consecutive row times is two hours. The NumMissing
field shows there are no missing values (NaT
) in the vector of row times.
s.Time
ans = struct with fields:
Size: [3 1]
Type: 'datetime'
Min: 18Dec2015 08:00:00
Median: 18Dec2015 10:00:00
Max: 18Dec2015 12:00:00
NumMissing: 0
TimeStep: 02:00:00
Change the last row time so that the row times have different intervals between them.
TT.Time(3) = '20151218 11:00:00';
TT
TT=3×2 timetable
Time Temp Pressure
____________________ ____ ________
18Dec2015 08:00:00 37.3 30.1
18Dec2015 10:00:00 39.1 30.03
18Dec2015 11:00:00 42.3 29.9
Return a summary of the updated timetable. Since the time steps between row times are different, the TimeStep
field has a NaN
.
s = summary(TT); s.Time
ans = struct with fields:
Size: [3 1]
Type: 'datetime'
Min: 18Dec2015 08:00:00
Median: 18Dec2015 10:00:00
Max: 18Dec2015 11:00:00
NumMissing: 0
TimeStep: NaN
Table Summary Including Custom Properties
Starting in R2018b, you can add custom properties to tables and timetables. If you add custom properties, then the summary of a table or timetable includes those properties.
First, create a table and add values to some of its predefined properties.
load patients BloodPressure = [Systolic Diastolic]; T = table(Gender,Age,Smoker,BloodPressure,'RowNames',LastName); T.Properties.Description = 'Simulated patient data'; T.Properties.VariableUnits = {'' 'Yrs' '' 'mm Hg'}; T.Properties.VariableDescriptions{4} = 'Systolic/Diastolic';
Add custom properties using the addprop
function. For each custom property, specify a name. Also, specify whether the value of each custom property stores metadata that applies to the table or to individual table variables.
T = addprop(T,{'SourceFile','DataOrigin'},{'table','variable'});
Store metadata values in the custom properties.
T.Properties.CustomProperties.SourceFile = 'patients.mat'; T.Properties.CustomProperties.DataOrigin = {'census','census','self report','blood pressure reading'};
Print a summary of the table. Aside from T.Properties.Description
, the summary
function does not display properties that apply to the table as a whole. So, it does not display the value of T.Properties.CustomProperties.SourceFile
. However, summary
does display properties that apply to table variables. For each variable, summary
displays the corresponding value from T.Properties.CustomProperties.DataOrigin
.
summary(T)
Description: Simulated patient data Variables: Gender: 100x1 cell array of character vectors Custom Properties: DataOrigin: census Age: 100x1 double Properties: Units: Yrs Custom Properties: DataOrigin: census Values: Min 25 Median 39 Max 50 Smoker: 100x1 logical Custom Properties: DataOrigin: self report Values: True 34 False 66 BloodPressure: 100x2 double Properties: Units: mm Hg Description: Systolic/Diastolic Custom Properties: DataOrigin: blood pressure reading Values: Column 1 Column 2 ________ ________ Min 109 68 Median 122 81.5 Max 138 99
Return the summary as a structure. Each field has a structure corresponding to one of the table variables.
s = summary(T)
s = struct with fields:
Gender: [1x1 struct]
Age: [1x1 struct]
Smoker: [1x1 struct]
BloodPressure: [1x1 struct]
The structure s.Age
stores the summary for the Age
variable.
s.Age
ans = struct with fields:
Size: [100 1]
Type: 'double'
Description: ''
Units: 'Yrs'
Continuity: []
Min: 25
Median: 39
Max: 50
NumMissing: 0
CustomProperties: [1x1 struct]
The s.Age.CustomProperties
structure stores the corresponding value from the T.Properties.CustomProperties.DataOrigin
property.
s.Age.CustomProperties
ans = struct with fields:
DataOrigin: {'census'}
Summary of Categorical Vector
Create a 1by5 categorical vector.
A = categorical({'plane' 'car' 'train' 'car' 'plane'})
A = 1x5 categorical
plane car train car plane
A
has three categories, car
, plane
, and train
.
Print a summary of A
.
summary(A)
car plane train 2 2 1
car
appears in two elements of A
, plane
appears in two elements, and train
appears in one element.
Since A
is a row vector, summary
lists the occurrences of each category horizontally.
Summary of Each Column in Categorical Array
Create a 4by2 categorical array, A
, from a numeric array.
X = [1 3; 2 1; 3 1; 4 2]; valueset = 1:3; catnames = {'red','green','blue'}; A = categorical(X,valueset,catnames)
A = 4x2 categorical
red blue
green red
blue red
<undefined> green
A
has three categories, red
, green
, and blue
. The value, 4
, was not included in the valueset
input to the categorical
function. Therefore, the corresponding element, A(4,1)
, does not have a corresponding category and is undefined.
Print a summary of A
.
summary(A)
red 1 2 green 1 1 blue 1 1 <undefined> 1 0
red
appears once in the first column of A
and twice in the second column.
green
appears once in the first column of A
and once in the second column.
blue
appears once in the first column of A
and once in the second column.
A
contains only one undefined element. It occurs in the first column.
Category Counts of Each Row in Categorical Array
Create a 3by2 categorical array, A
, from a numeric array.
A = categorical([1 3; 2 1; 3 1],1:3,{'red','green','blue'})
A = 3x2 categorical
red blue
green red
blue red
A
has three categories, red
, green
, and blue
.
Print a summary of A
along the second dimension.
summary(A,2)
red green blue 1 0 1 1 1 0 1 0 1
red
appears once in the first row of A
, once in the second row, and once in the third row.
green
appears in only one element. It occurs in the second row of A
.
blue
appears once in the first row of A
and once in the third row.
Input Arguments
T
— Input table
table  timetable
Input table, specified as a table or a timetable.
A
— Categorical array
vector  matrix  multidimensional array
Categorical array, specified as a vector, matrix, or multidimensional array.
dim
— Dimension of A
to operate along
positive integer scalar
Dimension of A
to operate to along, specified as a positive
integer scalar. If no value is specified, the default is the first array dimension whose
size does not equal 1.
Consider a twodimensional categorical array A
:
If dim = 1
, then summary(A,dim)
displays the
category counts for each column of A
.
If dim = 2
, then summary(A,dim)
displays the
category counts for each row of A
.
If dim
is greater than ndims(A)
, then
summary(A)
returns an array the same size as A
for each category. summary
returns 1
for elements
in the corresponding category and 0
otherwise.
Output Arguments
s
— Summary of table or timetable variables
scalar structure
Summary of the table or timetable variables, returned as a scalar structure. For
each variable T.
in the input
VarName
T
, the output structure s
contains a field
s.
with the summary for that
variable.VarName
If T
has variables whose names are not valid MATLAB^{®} identifiers, then summary
modifies them to create
valid field names, primarily by removing spaces and replacing nonASCII characters with
underscores.
For each data type, s.
contains
the fields shown below. You can access the fields with dot indexing. For example,
VarName
s.
returns the size of the
table variable named VarName
.Size
.VarName
Type of Table or Timetable Variable  Fields for Summary of Variable  Description 

Numeric,

 Size of variable, stored as a numeric array 
 Type of variable, stored as a character vector  
 Description of variable, stored as a character vector  
 Units of variable, stored as a character vector  
 Minimum value  
 Median value  
 Maximum value  
 Number of missing values (  
 Names and values for custom properties associated with variable, stored as a structure  
logical 
 Size of variable, stored as a numeric array 
 Type of variable, stored as a character vector  
 Description of variable, stored as a character vector  
 Units of variable, stored as a character vector  
 Number of  
 Number of  
 Names and values for custom properties associated with variable, stored as a structure  

 Size of variable, stored as a numeric array 
 Type of variable, stored as a character vector  
 Description of variable, stored as a character vector  
 Units of variable, stored as a character vector  
 Categories, stored as a cell array of character vectors  
 Number of elements in each category, stored as a numeric array  
 Number of missing values
(  
 Names and values for custom properties associated with variable, stored as a structure  
Other 
 Size of variable, stored as a numeric array 
 Type of variable, stored as a character vector  
 Description of variable, stored as a character vector  
 Units of variable, stored as a character vector  
 Names and values for custom properties associated with variable, stored as a structure 
If T
is a timetable, then s
also has a field
with a summary of the row times. For timetable row times only, the summary includes the
TimeStep
field. If the row times increase or decrease monotonically
by a fixed time step, then TimeStep
has a numeric value. If the row
times are irregular, then TimeStep
is NaN
.
Fields for Summary of Timetable Row Times  Description of Fields 

 Size of vector of row times, stored as a numeric array 
 Data type, stored as a character vector 
 Minimum value 
 Median value 
 Maximum value 
 Number of missing values ( 
 Time step between consecutive row times ( 
More About
Table Summary
The table summary displays the table description from
T.Properties.Description
followed by information on the variables of
T
.
The summary contains the following information on the variables:
Name: Size and Data Type — Variable name from
T.Properties.VariableNames
, the size of the variable, and the data type of the variable.Units — Variable units from
T.Properties.VariableUnits
.Description — Variable description from
T.Properties.VariableDescriptions
.Custom Properties: — Names of the custom properties that apply to variables, and their corresponding values, from
T.Properties.CustomProperties
. If there are no custom properties, then this section is omitted.Values — Only included for numeric, logical,
categorical
,datetime
, orduration
variables.Numeric,
datetime
, orduration
variables — minimum, median, and maximum values. Also, the number of missing values (NaN
s orNaT
s) is included when that number is greater than zero.Logical variables — number of values that are
true
and the number of values that arefalse
.categorical
variables — number of elements from each category. Also, the number of undefined elements is included when that number is greater than zero.
If T
is a timetable, then the summary contains the same information
on the vector of row times.
Extended Capabilities
Tall Arrays
Calculate with arrays that have more rows than fit in memory.
This function supports tall arrays with the limitation:
Some fields in the summary can be impossible to calculate in a reasonable amount of time, such as the median.
For more information, see Tall Arrays for OutofMemory Data.
ThreadBased Environment
Run code in the background using MATLAB® backgroundPool
or accelerate code with Parallel Computing Toolbox™ ThreadPool
.
This function fully supports threadbased environments. For more information, see Run MATLAB Functions in ThreadBased 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 R2013b
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