preview

Preview subset of data in datastore

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Syntax

data = preview(ds)

Description

example

data = preview(ds) returns a subset of data from datastore ds without changing its current position.

Examples

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Preview Data in TabularTextDatastore

Open Live Script

Create a datastore from the sample file, airlinesmall.csv, which contains tabular data.

ds = tabularTextDatastore('airlinesmall.csv','TreatAsMissing','NA',...
    'MissingValue',0);

Modify the SelectedVariableNames property to specify the variables of interest.

ds.SelectedVariableNames = {'DepTime','ArrTime','ActualElapsedTime'};

Preview the data for the selected variables.

data = preview(ds)

data=8×3 table
    DepTime    ArrTime    ActualElapsedTime
    _______    _______    _________________

      642        735              53       
     1021       1124              63       
     2055       2218              83       
     1332       1431              59       
      629        746              77       
     1446       1547              61       
      928       1052              84       
      859       1134             155

Preview Data in KeyValueDatastore

Open Live Script

Create a datastore from the sample file, mapredout.mat, which is the output file of the mapreduce function.

ds = datastore('mapredout.mat');

Preview the data in the datastore.

data = preview(ds)

data=1×2 table
     Key        Value  
    ______    _________

    {'AA'}    {[14930]}

Preview Data in CombinedDatastore

Open Live Script

Create a datastore that maintains parity between the pair of images of the underlying datastores. For instance, create two separate image datastores, and then create a combined datastore representing the two underlying datastores.

Create an image datastore imds1 representing a collection of three images.

imds1 = imageDatastore({'street1.jpg','street2.jpg','peppers.png'});

Create a second datastore imds2 by transforming the images of imds1 to grayscale and then reflecting the images horizontally.

imds2 = transform(imds1,@(x) fliplr(im2gray(x)));

Create a combined datastore from imds1 and imds2.

imdsCombined = combine(imds1,imds2);

Preview the data in the combined datastore. The output is a 1-by-2 cell array. The two columns represent the first subset of data from the two underlying datastores imds1 and imds2, respectively.

dataOut = preview(imdsCombined)

dataOut=1×2 cell array
    {480x640x3 uint8}    {480x640 uint8}

Display the previewed data as a pair of tiled images.

tile = imtile(dataOut);
imshow(tile)

Figure contains an axes object. The axes object contains an object of type image.

Input Arguments

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`ds` — Input datastore
datastore

Input datastore. You can use these datastores as input to the preview method.

MATLAB^® datastores — Datastores created using MATLAB datastore functions. For example, create a datastore for a collection of images using ImageDatastore. For a complete list of datastores, see Select Datastore for File Format or Application.
Combined and transformed datastores — Datastores created using the combine and transform functions.
Custom datastores — Datastores created using the custom datastore framework. See Develop Custom Datastore.

Output Arguments

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`data` — Subset of data
table | array

Subset of data, returned as a table or an array depending on the type of ds.

Type of Datastore	Data type of `data`	Description
`TabularTextDatastore` and `SpreadsheetDatastore`	Table	Table with variables specified by the `SelectedVariableNames` property. The table contains at most eight rows.
`ImageDatastore`	Integer array	Array of integers corresponding to the first image. The dimensions of the integer array depend on the type of image: For grayscale images, `data` is m-by-n. For truecolor images, `data` is m-by-n-by-3. For CMYK Tiff images, `data` is m-by-n-by-4. The `preview` function supports all image types supported by the `imread` function. For more information on the supported image types, see `imread`.
`KeyValueDatastore`	Table	Table with the variables `Key` and `Value`.
`FileDatastore`	Table	Table containing the output returned by the read function, specified by the `'ReadFcn'` parameter in the `fileDatastore` function.
`TransformedDatastore`	Varies	The output is the same as the output returned by the underlying datastore specified by the `UnderlyingDatastores` property. For example, if the underlying datastore is an image datastore with a `ReadSize` property value of 1, then `data` is returned as a integer array.
`CombinedDatastore`	Cell array	Each element of the cell array contains the output returned by the corresponding underlying datastore specified by the `UnderlyingDatastores` property.
`SequentialDatastore`	Varies	The output is a small amount of data from the first nonempty underlying datastore. If all underlying datastores are empty, output is the empty type based on the first underlying datastore. If there are no underlying datastores, output is an empty double.

Extended Capabilities

Thread-Based Environment
Run code in the background using MATLAB® `backgroundPool` or accelerate code with Parallel Computing Toolbox™ `ThreadPool`.

Usage notes and limitations:

In a thread-based environment, you can use preview only with the following datastores:
- ImageDatastore objects
- CombinedDatastore, SequentialDatastore, or TransformedDatastore objects you create from ImageDatastore objects by using combine or transform
You can use preview with other datastores if you have Parallel Computing Toolbox™. To do so, run the function using a process-backed parallel pool instead of using backgroundPool or ThreadPool (use either ProcessPool or ClusterPool).