MCQs on File Handling and Data Import/Export | MATLAB

Master File Handling and Data Management: Optimize Data Workflow Learn efficient file handling and data import/export techniques, including advanced file formats, binary operations, preprocessing, cleaning, and managing large datasets. Unlock streamlined solutions for data-driven projects.

File Handling and Data Import/Export – Multiple Choice Questions1. Advanced File Formats (CSV, HDF5, JSON)

Which MATLAB function is commonly used to read CSV files?

• A. freadB. readtableC. importdataD. jsondecode

To save a MATLAB table to a CSV file, which function is used?

• A. saveB. writetableC. writecsvD. csvwrite

What file format is most suitable for hierarchical data storage?

• A. CSVB. HDF5C. TXTD. XLSX

The function to write data into an HDF5 file is:

• A. h5writeB. writehdf5C. savehdfD. hdfwrite

JSON files are primarily used for:

• A. Large numerical datasetsB. Key-value pair data exchangeC. Image processingD. Encrypted file storage

To decode JSON data into MATLAB structures, you use:

• A. jsonreadB. jsondecodeC. readJSOND. decodejson

2. Reading and Writing Binary Files

7. Which function is used to open a file in binary mode?

   • A. fopenB. freadC. fcloseD. fwrite

   To read binary data from a file, you use:

   • A. fopenB. freadC. fwriteD. fprintf

   What does the fseek function accomplish in file handling?

   • A. Reads dataB. Moves the file position indicatorC. Closes the fileD. Writes data

   Which of the following modes is used to open a file for both reading and writing in binary format?

   • A. 'r+'B. 'w+'C. 'rb+'D. 'wb+'

   Binary files are typically preferred over text files because they:

   • A. Are human-readableB. Allow faster processing and smaller file sizesC. Use ASCII encodingD. Require no additional software

   To write an array as binary data, the function used is:

   • A. fprintfB. fwriteC. saveD. dlmwrite

3. Data Preprocessing and Cleaning

13. What MATLAB function removes missing values from data?

    • A. rmmissingB. isnanC. fillmissingD. replace

    The function fillmissing is used to:

    • A. Replace missing values with specified valuesB. Identify missing valuesC. Remove outliersD. Sort data

    Outlier detection can be performed using:

    • A. isnanB. fillmissingC. isoutlierD. replace

    To standardize data for preprocessing, which function is most appropriate?

    • A. normalizeB. meanC. fillmissingD. std

    Which MATLAB function identifies duplicate rows in a table?

    • A. uniqueB. findC. removedupsD. duplicaterows

    The process of transforming categorical data into numerical values is called:

    • A. NormalizationB. One-hot encodingC. PreprocessingD. Label encoding

4. Handling Large Datasets

19. What is a common method to handle large datasets efficiently in MATLAB?

    • A. Load all data at onceB. Use tall arraysC. Split data manually into chunksD. Use only CSV files

    The datastore function is used to:

    • A. Handle file I/O errorsB. Access and process large datasetsC. Create backup filesD. Perform database queries

    Which of the following supports memory-efficient operations on large datasets?

    • A. tablesB. arraysC. tallD. structs

    The mapreduce function is best suited for:

    • A. Creating plotsB. Parallel processing of large datasetsC. Reading JSON filesD. Managing binary data

    To preview a part of a large dataset without loading it entirely, you use:

    • A. headB. previewC. subsetD. chunk

    When working with large text files, MATLAB recommends:

    • A. Using readlinesB. Using fgetsC. Loading all data into memoryD. Writing custom file parsers

    To optimize computations with large matrices, you should consider:

    • A. Converting to sparse matricesB. Storing matrices in binary formatC. Parallelizing operationsD. All of the above

    What is the advantage of using parfor with large datasets?

    • A. Interactive plottingB. Parallelized loop executionC. Automatic data cleaningD. Simplified file I/O

    Which of the following can handle distributed computing across clusters?

    • A. mapreduceB. datastoreC. tallD. parcluster

    To convert a dataset into a chunked, memory-efficient format, you use:

    • A. tallB. chunkdataC. datastoreD. partition

    The gather function is used to:

    • A. Save tall arraysB. Bring distributed data back into memoryC. Sort datasetsD. Delete temporary data

    Which toolbox is commonly used to handle large datasets in MATLAB?

    • A. Optimization ToolboxB. Parallel Computing ToolboxC. Statistics ToolboxD. Signal Processing Toolbox

Answers TableQnoAnswer (Option with Text)1B. readtable2B. writetable3B. HDF54A. h5write5B. Key-value pair data exchange6B. jsondecode7A. fopen8B. fread9B. Moves the file position indicator10C. 'rb+'11B. Allow faster processing and smaller file sizes12B. fwrite13A. rmmissing14A. Replace missing values with specified values15C. isoutlier16A. normalize17A. unique18B. One-hot encoding19B. Use tall arrays20B. Access and process large datasets21C. tall22B. Parallel processing of large datasets23B. preview24A. Using readlines25D. All of the above26B. Parallelized loop execution27A. mapreduce28A. tall29B. Bring distributed data back into memory30B. Parallel Computing Toolbox