select
Execute SQL SELECT
statement and import
data into MATLAB
Syntax
Description
returns
imported data from the database connection data
= select(conn
,selectquery
)conn
for
the specified SQL SELECT
statement selectquery
.
specifies additional options using one or more name-value pair arguments. For
example, data
= select(conn
,selectquery
,Name,Value
)'MaxRows',10
sets the maximum number of rows to return
to 10 rows.
Examples
Import and Access Data Immediately
Import data from a database in one step using the select
function. You can access data and perform immediate data analysis.
The code assumes that you have a database table Patients
stored on a Microsoft® SQL Server® database. This table contains patient data in 10 columns and rows. The table definition is:
CREATE TABLE Patients( LastName VARCHAR(50), Gender VARCHAR(10), Age TINYINT, Location VARCHAR(300), Height SMALLINT, Weight SMALLINT, Smoker BIT, Systolic FLOAT, Diastolic NUMERIC, SelfAssessedHealthStatus VARCHAR(20))
This example uses a Microsoft® SQL Server® Version 11.00.2100 database and the Microsoft® SQL Server® Driver 11.00.5058.
Create a database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password.
datasource = 'MS SQL Server Auth'; conn = database(datasource,'','');
Import all data from the Patients
table by executing the SQL SELECT
statement using the select
function. data
is a table that contains the imported data.
selectquery = 'SELECT * FROM Patients';
data = select(conn,selectquery)
data = 10×10 table LastName Gender Age Location Height Weight Smoker Systolic Diastolic SelfAssessedHealthStatus __________ ________ ___ __________________________ ______ ______ ______ ________ _________ ________________________ 'Smith' 'Male' 38 'Country General Hospital' -32768 176 true 124 93 'Excellent' 'Johnson' 'Male' 43 'VA Hospital' 69 163 false NaN 77 'Fair' 'Williams' 'Female' 38 '' 64 131 false 125 83 'Good' 'Jones' 'Female' 0 'VA Hospital' 67 133 false 117 75 'Fair' 'Broen' 'Female' 49 'Country General Hospital' 64 119 false 122 80 'Good' 'Davis' 'Female' 46 'St Mary's Medical Center' 68 142 false 121 NaN 'Good' 'Miller' 'Female' 33 'VA Hospital' 64 142 true 130 88 'Good' 'Wilson' 'Male' 40 'VA Hospital' -32768 180 false 115 82 'Good' 'Moore' 'Male' 28 'St Mary's Medical Center' 68 -32768 false 115 78 'Excellent' 'Taylor' 'Female' 31 'Country General Hospital' 68 132 false NaN 86 'Excellent'
Determine the number of male patients by immediately accessing the data. Use the count
function to find occurrences in the gender data of the character vector that represents a male. Determine the total number of occurrences.
males = count(data.Gender,'Male');
sum(males)
ans = 4
Close the database connection.
close(conn)
Limit Number of Rows in Imported Data
Import a limited number of rows from a database in one step using the select
function. Database Toolbox™ imports the data using MATLAB® numeric data types that correspond to data types in the database table. After importing data, you can access data and perform immediate data analysis.
The code assumes that you have a database table Patients
stored on a Microsoft® SQL Server® database. This table contains patient data in 10 columns and rows. The table definition is:
CREATE TABLE Patients( LastName VARCHAR(50), Gender VARCHAR(10), Age TINYINT, Location VARCHAR(300), Height SMALLINT, Weight SMALLINT, Smoker BIT, Systolic FLOAT, Diastolic NUMERIC, SelfAssessedHealthStatus VARCHAR(20))
Here, connect to a Microsoft® SQL Server® Version 11.00.2100 database using the Microsoft® SQL Server® Driver 11.00.5058.
Create a database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password.
datasource = 'MS SQL Server Auth'; conn = database(datasource,'','');
Import data from the Patients
table by executing the SQL SELECT
statement using the select
function. Limit the number of imported rows using the name-value pair argument 'MaxRows'
.
data
is a table. The MATLAB® data types in the table correspond to the data types in the database. Here, Age
has data type uint8
that corresponds to TINYINT
in the table definition.
metadata
is a table that contains additional information about each variable in data
.
VariableType
-- MATLAB® data typeMissingValue
--NULL
value representationMissingRows
-- Vector of row indices that contain a missing value
selectquery = 'SELECT * FROM Patients'; [data,metadata] = select(conn,selectquery,'MaxRows',5)
data = 5×10 table LastName Gender Age Location Height Weight Smoker Systolic Diastolic SelfAssessedHealthStatus __________ ________ ___ __________________________ ______ ______ ______ ________ _________ ________________________ 'Smith' 'Male' 38 'Country General Hospital' -32768 176 true 124 93 'Excellent' 'Johnson' 'Male' 43 'VA Hospital' 69 163 false NaN 77 'Fair' 'Williams' 'Female' 38 '' 64 131 false 125 83 'Good' 'Jones' 'Female' 0 'VA Hospital' 67 133 false 117 75 'Fair' 'Broen' 'Female' 49 'Country General Hospital' 64 119 false 122 80 'Good' metadata = 10×3 table VariableType MissingValue MissingRows ____________ ____________ ____________ LastName 'char' '' [0×1 double] Gender 'char' '' [0×1 double] Age 'uint8' [ 0] [ 4] Location 'char' '' [0×1 double] Height 'int16' [-32768] [ 1] Weight 'int16' [-32768] [0×1 double] Smoker 'logical' [ 0] [0×1 double] Systolic 'single' [ NaN] [ 2] Diastolic 'double' [ NaN] [0×1 double] SelfAssessedHealthStatus 'char' '' [0×1 double]
Determine the number of male patients by immediately accessing the data. Use the count
function to find occurrences in the gender data of the character vector that represents a male. Determine the total number of occurrences.
males = count(data.Gender,'Male');
sum(males)
ans = 2
Close the database connection.
close(conn)
View Information About Imported Data
Import data from a database in one step using the select
function. Database Toolbox™ imports the data using MATLAB® numeric data types that correspond to data types in the database table. You can view data type information in the imported data. You can also access data and perform immediate data analysis.
The code assumes that you have a database table Patients
stored on a Microsoft® SQL Server® database. This table contains patient data in 10 columns and rows. The table definition is:
CREATE TABLE Patients( LastName VARCHAR(50), Gender VARCHAR(10), Age TINYINT, Location VARCHAR(300), Height SMALLINT, Weight SMALLINT, Smoker BIT, Systolic FLOAT, Diastolic NUMERIC, SelfAssessedHealthStatus VARCHAR(20))
Here, connect to a Microsoft® SQL Server® Version 11.00.2100 database using the Microsoft® SQL Server® Driver 11.00.5058.
Create a database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password.
datasource = 'MS SQL Server Auth'; conn = database(datasource,'','');
Import all data from the Patients
table by executing the SQL SELECT
statement using the select
function.
data
is a table. The MATLAB® data types in the table correspond to the data types in the database. Here, Age
has the MATLAB® data type uint8
that corresponds to TINYINT
in the table definition.
metadata
is a table that contains additional information about each variable in data
.
VariableType
-- MATLAB® data typeMissingValue
-- Null value representationMissingRows
-- Vector of row indices that contain a missing value
selectquery = 'SELECT * FROM Patients';
[data,metadata] = select(conn,selectquery)
data = 10×10 table LastName Gender Age Location Height Weight Smoker Systolic Diastolic SelfAssessedHealthStatus __________ ________ ___ __________________________ ______ ______ ______ ________ _________ ________________________ 'Smith' 'Male' 38 'Country General Hospital' -32768 176 true 124 93 'Excellent' 'Johnson' 'Male' 43 'VA Hospital' 69 163 false NaN 77 'Fair' 'Williams' 'Female' 38 '' 64 131 false 125 83 'Good' 'Jones' 'Female' 0 'VA Hospital' 67 133 false 117 75 'Fair' 'Broen' 'Female' 49 'Country General Hospital' 64 119 false 122 80 'Good' 'Davis' 'Female' 46 'St Mary's Medical Center' 68 142 false 121 NaN 'Good' 'Miller' 'Female' 33 'VA Hospital' 64 142 true 130 88 'Good' 'Wilson' 'Male' 40 'VA Hospital' -32768 180 false 115 82 'Good' 'Moore' 'Male' 28 'St Mary's Medical Center' 68 -32768 false 115 78 'Excellent' 'Taylor' 'Female' 31 'Country General Hospital' 68 132 false NaN 86 'Excellent' metadata = 10×3 table VariableType MissingValue MissingRows ____________ ____________ ____________ LastName 'char' '' [0×1 double] Gender 'char' '' [0×1 double] Age 'uint8' [ 0] [ 4] Location 'char' '' [0×1 double] Height 'int16' [-32768] [2×1 double] Weight 'int16' [-32768] [ 9] Smoker 'logical' [ 0] [0×1 double] Systolic 'single' [ NaN] [2×1 double] Diastolic 'double' [ NaN] [ 6] SelfAssessedHealthStatus 'char' '' [0×1 double]
View data types of each variable in the table.
metadata.VariableType
ans = 10×1 cell array 'char' 'char' 'uint8' 'char' 'int16' 'int16' 'logical' 'single' 'double' 'char'
Determine the number of male patients by immediately accessing the data. Use the count
function to find occurrences in the gender data of the character vector that represents a male. Determine the total number of occurrences.
males = count(data.Gender,'Male');
sum(males)
ans = 4
Close the database connection.
close(conn)
Change Missing Values in Imported Data Using for Loop
Import data from a database in one step using the select
function. During import, the select
function sets default values for missing data in each row. Use the information about the imported data to change the default values.
The code assumes that you have a database table Patients
stored on a Microsoft® SQL Server® database. This table contains patient data in 10 columns and rows. The table definition is:
CREATE TABLE Patients( LastName VARCHAR(50), Gender VARCHAR(10), Age TINYINT, Location VARCHAR(300), Height SMALLINT, Weight SMALLINT, Smoker BIT, Systolic FLOAT, Diastolic NUMERIC, SelfAssessedHealthStatus VARCHAR(20))
Here, connect to a Microsoft® SQL Server® Version 11.00.2100 database using the Microsoft® SQL Server® Driver 11.00.5058.
Create a database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password.
datasource = 'MS SQL Server Auth'; conn = database(datasource,'','');
Import all data from the Patients
table by executing the SQL SELECT
statement using the select
function.
data
is a table that contains the imported data.
metadata
is a table that contains additional information about each variable in data
.
VariableType
-- MATLAB® data typeMissingValue
--NULL
value representationMissingRows
-- Vector of row indices that indicate the location of missing values
selectquery = 'SELECT * FROM Patients';
[data,metadata] = select(conn,selectquery)
data = 10×10 table array LastName Gender Age Location Height Weight Smoker Systolic Diastolic SelfAssessedHealthStatus __________ ________ ___ __________________________ ______ ______ ______ ________ _________ ________________________ 'Smith' 'Male' 38 'Country General Hospital' -32768 176 true 124 93 'Excellent' 'Johnson' 'Male' 43 'VA Hospital' 69 163 false NaN 77 'Fair' 'Williams' 'Female' 38 '' 64 131 false 125 83 'Good' 'Jones' 'Female' 0 'VA Hospital' 67 133 false 117 75 'Fair' 'Broen' 'Female' 49 'Country General Hospital' 64 119 false 122 80 'Good' 'Davis' 'Female' 46 'St Mary's Medical Center' 68 142 false 121 NaN 'Good' 'Miller' 'Female' 33 'VA Hospital' 64 142 true 130 88 'Good' 'Wilson' 'Male' 40 'VA Hospital' -32768 180 false 115 82 'Good' 'Moore' 'Male' 28 'St Mary's Medical Center' 68 -32768 false 115 78 'Excellent' 'Taylor' 'Female' 31 'Country General Hospital' 68 132 false NaN 86 'Excellent' metadata = 10×3 table array VariableType MissingValue MissingRows ____________ ____________ ____________ LastName 'char' '' [0×1 double] Gender 'char' '' [0×1 double] Age 'uint8' [ 0] [ 4] Location 'char' '' [0×1 double] Height 'int16' [-32768] [2×1 double] Weight 'int16' [-32768] [ 9] Smoker 'logical' [ 0] [0×1 double] Systolic 'single' [ NaN] [2×1 double] Diastolic 'double' [ NaN] [ 6] SelfAssessedHealthStatus 'char' '' [0×1 double]
Retrieve indices that indicate the location of missing values in the Height
variable using the metadata
output argument.
values = metadata.MissingRows{'Height'}
values = 1 8
Change the default value for missing data from -32768
to 0
using a for loop. Access the imported data using the indices.
for i = 1:length(values) data.Height(values(i)) = 0; end
View the imported data.
data.Height
ans = 10×1 int16 column vector 0 69 64 67 64 68 64 0 68 68
Missing values appear as 0
.
Close the database connection.
close(conn)
Change Missing Values in Imported Data Using Vector Indexing
Import data from a database in one step using the select
function. During import, the select
function sets default values for missing data in each row. Use the information about the imported data to change default values by indexing into the vector.
The code assumes that you have a database table Patients
stored on a Microsoft® SQL Server® database. This table contains patient data in 10 columns and rows. The table definition is:
CREATE TABLE Patients( LastName VARCHAR(50), Gender VARCHAR(10), Age TINYINT, Location VARCHAR(300), Height SMALLINT, Weight SMALLINT, Smoker BIT, Systolic FLOAT, Diastolic NUMERIC, SelfAssessedHealthStatus VARCHAR(20))
Here, connect to a Microsoft® SQL Server® Version 11.00.2100 database using the Microsoft® SQL Server® Driver 11.00.5058.
Create a database connection to a Microsoft® SQL Server® database with Windows® authentication. Specify a blank user name and password.
datasource = 'MS SQL Server Auth'; conn = database(datasource,'','');
Import all data from the Patients
table by executing the SQL SELECT
statement using the select
function.
data
is a table that contains the imported data.
metadata
is a table that contains additional information about each variable in data
.
VariableType
-- MATLAB® data typeMissingValue
--NULL
value representationMissingRows
-- Vector of row indices that indicate the location of missing values
selectquery = 'SELECT * FROM Patients';
[data,metadata] = select(conn,selectquery)
data = 10×10 table array LastName Gender Age Location Height Weight Smoker Systolic Diastolic SelfAssessedHealthStatus __________ ________ ___ __________________________ ______ ______ ______ ________ _________ ________________________ 'Smith' 'Male' 38 'Country General Hospital' -32768 176 true 124 93 'Excellent' 'Johnson' 'Male' 43 'VA Hospital' 69 163 false NaN 77 'Fair' 'Williams' 'Female' 38 '' 64 131 false 125 83 'Good' 'Jones' 'Female' 0 'VA Hospital' 67 133 false 117 75 'Fair' 'Broen' 'Female' 49 'Country General Hospital' 64 119 false 122 80 'Good' 'Davis' 'Female' 46 'St Mary's Medical Center' 68 142 false 121 NaN 'Good' 'Miller' 'Female' 33 'VA Hospital' 64 142 true 130 88 'Good' 'Wilson' 'Male' 40 'VA Hospital' -32768 180 false 115 82 'Good' 'Moore' 'Male' 28 'St Mary's Medical Center' 68 -32768 false 115 78 'Excellent' 'Taylor' 'Female' 31 'Country General Hospital' 68 132 false NaN 86 'Excellent' metadata = 10×3 table array VariableType MissingValue MissingRows ____________ ____________ ____________ LastName 'char' '' [0×1 double] Gender 'char' '' [0×1 double] Age 'uint8' [ 0] [ 4] Location 'char' '' [0×1 double] Height 'int16' [-32768] [2×1 double] Weight 'int16' [-32768] [ 9] Smoker 'logical' [ 0] [0×1 double] Systolic 'single' [ NaN] [2×1 double] Diastolic 'double' [ NaN] [ 6] SelfAssessedHealthStatus 'char' '' [0×1 double]
Retrieve indices that indicate the location of missing values in the Height
variable using the metadata
output argument.
values = metadata(5,3) valuesindex = values.MissingRows{1}
values = table MissingRows ____________ Height [2×1 double] valuesindex = 1 8
Change the default value for missing data from -32768
to 0
using vector indexing.
data.Height(valuesindex) = 0;
View the imported data.
data.Height
ans = 10×1 int16 column vector 0 69 64 67 64 68 64 0 68 68
Missing values appear as 0
.
Close the database connection.
close(conn)
Input Arguments
conn
— Database connection
connection
object
Database connection, specified as an ODBC connection
object or JDBC connection
object created using the
database
function.
selectquery
— SQL SELECT
statement
character vector | string
SQL SELECT
statement, specified as a character
vector or string. The select
function only executes
SQL SELECT
statements. To execute other SQL statements,
use the exec
function.
Example: 'SELECT * FROM inventoryTable'
Data Types: char
| string
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Before R2021a, use commas to separate each name and value, and enclose
Name
in quotes.
Example: 'MaxRows',100,'QueryTimeOut',5
returns 100 rows of data and waits 5
seconds to execute the SQL SELECT
statement.
MaxRows
— Maximum number of rows to return
positive numeric scalar
Maximum number of rows to return, specified as the comma-separated pair consisting of
'MaxRows'
and a positive numeric scalar. By default, the
select
function returns all rows from the executed SQL
query. Use this name-value pair argument to limit the number of rows imported into
MATLAB®.
Example: 'MaxRows',10
Data Types: double
QueryTimeOut
— SQL query timeout
positive numeric scalar
SQL query timeout, specified as the comma-separated pair consisting
of 'QueryTimeOut'
and a positive numeric scalar.
By default, the select
function ignores the timeout
value. Use this name-value pair argument to specify the number of
seconds to wait for executing the SQL query selectquery
.
Example: 'QueryTimeOut',15
Output Arguments
data
— Imported data
table
Imported data, returned as a table. The rows of the table correspond
to the rows of data returned from the executed SQL query selectquery
.
The variable names of the table specify the columns in the SQL query.
The select
function returns date or time data as character vectors in the
table. This function returns text as character vectors or a cell array of
character vectors. Strings are not supported in the table.
If no data to import exists, then data
is
an empty table.
metadata
— Information about imported data
table
Information about imported data, returned as a table. The row names of
metadata
are variable names in
data
. This function stores each variable name in
the metadata
table as a cell array.
metadata
has these variable names:
VariableType
— Data types of each variable indata
MissingValue
— Representation of missing value for each variable indata
MissingRows
— Vector of row indices that indicate locations of missing values for each variable indata
This table shows how MATLAB represents NULL
values
in the database by default after data import.
Database Data Type | Default NULL Value |
---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Boolean |
|
Date, time, or text |
|
To change the NULL
value representation in
the imported data, replace the default value by looping through the
imported data or using vector indexing.
Limitations
You cannot customize missing values in the output argument
data
using theselect
function. Index into the imported data using themetadata
output argument instead.The output argument
data
does not supportcell
andstruct
data types. Theselect
function only supportstable
.
Alternative Functionality
Use the exec
and fetch
functions for full functionality
when importing data. For differences between the select
function
and this alternative, see Data Import Using Database Explorer App or Command Line.
Version History
Introduced in R2017a
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