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MCQs

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Overall MCQs for Reference

  1. Which file format is most commonly used as a workbook in data science workflows?
    a. .txt
    b. .csv
    c. .ipynb
    d. .exe
    Answer: c. .ipynbdasca+1​
  2. What is a primary benefit of splitting a large notebook into modular workbooks?
    a. Increased program speed
    b. Enhanced readability and maintenance
    c. Reduced storage requirements
    d. Decreased memory usage
    Answer: b. Enhanced readability and maintenanceneptune+1​
  3. What does the DRY principle stand for in workbook management?
    a. Don’t Repeat Yourself
    b. Data Reuse Yearly
    c. Data Rationalization Yield
    d. Design Reviewing Year
    Answer: a. Don’t Repeat Yourselfdasca+1​
  4. Which of the following is a good practice for organizing code and markdown in Jupyter Notebooks?
    a. Randomly mixing code and markdown cells
    b. Grouping all markdown at the end
    c. Structuring with logical sections and headings
    d. Placing all code at the start
    Answer: c. Structuring with logical sections and headingsreddit+1​
  5. Why is it important to document every step in a workbook?
    a. Only for beginners
    b. For exercise practice
    c. For reproducibility and collaboration
    d. It is not necessary
    Answer: c. For reproducibility and collaborationneptune+1​
  6. Which function allows notebook export to different formats in Jupyter?
    a. Export()
    b. Download()
    c. File > Download as
    d. Save As
    Answer: c. File > Download asreddit+1​
  7. Which cell type is used to provide explanatory text in Jupyter notebooks?
    a. Input cell
    b. Output cell
    c. Markdown cell
    d. Expression cell
    Answer: c. Markdown celldasca+1​
  8. What is one key advantage of leveraging utility modules in workbook projects?
    a. Slower performance
    b. Reduced code reuse
    c. Centralized reusable functions
    d. More manual updates
    Answer: c. Centralized reusable functionsreddit+1​
  9. Which action best maintains workbook version control?
    a. Manual file backups
    b. Using git repositories
    c. Emailing copies to team
    d. Saving with new names
    Answer: b. Using git repositoriessanfoundry+1​
  10. Why should notebooks avoid hardcoding configuration values?
    a. To confuse readers
    b. To maximize reproducibility
    c. To decrease security
    d. To reduce modularity
    Answer: b. To maximize reproducibilitydatamation+1​
  11. What should be documented in the first cell of a data science notebook?
    a. Import statements
    b. Session time
    c. Project title, description, and goals
    d. Visualization code
    Answer: c. Project title, description, and goalsneptune+1​
  12. Which format is most recommended for sharing data analysis results from Jupyter notebooks?
    a. .exe
    b. .txt
    c. .html
    d. .zip
    Answer: c. .htmldasca+1​
  13. What is the main purpose of cell outputs in a notebook?
    a. They are for saving disk
    b. They show program status
    c. They display code results and data visualizations
    d. They are not important
    Answer: c. They display code results and data visualizationsreddit+1​
  14. Which practice is discouraged in collaborative notebook work?
    a. Using consistent variable names
    b. Writing duplicate code
    c. Adding comments
    d. Keeping code modular
    Answer: b. Writing duplicate codedasca​
  15. Which tool can help automatically check code formatting in notebooks?
    a. Manual review
    b. Linter
    c. Calculator
    d. Sorter
    Answer: b. Linterdasca​
  16. What should you do before sharing a workbook publicly?
    a. Run all cells, clear outputs
    b. Review and remove sensitive data
    c. Give edit access to everyone
    d. Add irrelevant code
    Answer: b. Review and remove sensitive datalearn.microsoft+1​
  17. When should you save a checkpoint in a notebook?
    a. Only when closing
    b. At significant milestones or after major edits
    c. Never
    d. Only after errors
    Answer: b. At significant milestones or after major editsreddit+1​
  18. Which is NOT a benefit of using markdown cells?
    a. Adding context to analysis
    b. Providing inline visuals
    c. Increasing computational speed
    d. Documenting assumptions
    Answer: c. Increasing computational speedreddit+1​
  19. Why use version control with workbooks?
    a. To lose track of changes
    b. For tracking edits, collaboration, and reverting changes
    c. To use more disk space
    d. To avoid sharing
    Answer: b. For tracking edits, collaboration, and reverting changessanfoundry+1​
  20. Which practice is essential for managing output cells with large data visualizations?
    a. Deleting them
    b. Hiding or collapsing outputs
    c. Color-coding outputs
    d. Printing to external files
    Answer: b. Hiding or collapsing outputsreddit​
  21. What is the benefit of using notebook templates?
    a. Reduces standardization
    b. Increases setup time
    c. Promotes consistency and best practices
    d. Inhibits sharing
    Answer: c. Promotes consistency and best practicesdatabricks+1​
  22. What can be used to organize related notebooks in a project?
    a. Placing in a single folder with clear naming
    b. Randomly on the desktop
    c. Multiple cloud drives
    d. Email threads
    Answer: a. Placing in a single folder with clear namingneptune+1​
  23. Which extension helps manage large Jupyter notebooks?
    a. Jupyter Nbextensions
    b. Video player
    c. Image resizer
    d. Syntax highlighter
    Answer: a. Jupyter Nbextensionsdasca​
  24. Why should random seeds be set in notebooks?
    a. For privacy
    b. To slow computation
    c. Ensure reproducibility of results
    d. Increase randomness
    Answer: c. Ensure reproducibility of resultsdatamation+1​
  25. What is a security risk when managing workbooks?
    a. Over-documentation
    b. Importing untrusted code
    c. Using markdown cells
    d. Running as guest
    Answer: b. Importing untrusted codelearn.microsoft+1​
  26. Which feature helps check code execution history in Jupyter?
    a. Notebook logs
    b. Cell execution count
    c. Variable explorer
    d. Sorting cells
    Answer: b. Cell execution countdasca+1​
  27. For regularly updated analytics, which notebook feature is essential?
    a. Static data snapshots
    b. Live data refresh and rerun capability
    c. Hidden cells
    d. Export to PDF
    Answer: b. Live data refresh and rerun capabilitydasca​
  28. Which license is best for widely sharing your analysis workbook?
    a. MIT License
    b. Unlisted
    c. Proprietary
    d. Restricted access
    Answer: a. MIT Licensedatabricks​
  29. What helps make a notebook accessible to non-technical stakeholders?
    a. Removing all comments
    b. Adding visualizations and narrative explanations
    c. Using raw data only
    d. Technical jargon
    Answer: b. Adding visualizations and narrative explanationsneptune+1​
  30. How can large datasets be handled in notebooks without performance issues?
    a. Load only needed data portions
    b. Remove all outputs
    c. Export models
    d. Use desktop icons
    Answer: a. Load only needed data portionsneptune​
  31. What marks a well-documented notebook?
    a. Has no comments
    b. Lacks title and sections
    c. Contains clear explanations and outines
    d. Only code
    Answer: c. Contains clear explanations and outlinesneptune+1​
  32. Which command restarts a notebook kernel in Jupyter?
    a. Shutdown()
    b. Restart Kernel
    c. Exit()
    d. Terminate()
    Answer: b. Restart Kerneldasca​
  33. Why group notebooks by project or purpose?
    a. To confuse users
    b. For easier organization and navigation
    c. To waste time
    d. For better randomness
    Answer: b. For easier organization and navigationreddit+1​
  34. How do you ensure consistent environment setup for workbooks?
    a. Ignore dependencies
    b. Use environment.yml or requirements.txt
    c. Only use default packages
    d. Copy and paste
    Answer: b. Use environment.yml or requirements.txtdatabricks+1​
  35. What is the primary file extension for R notebooks?
    a. .r
    b. .rmd
    c. .ipynb
    d. .dat
    Answer: b. .rmdgyansetu+1​
  36. What can help track data pipeline logic in notebooks?
    a. Hide code cells
    b. Use schematic diagrams and workflow visualization
    c. Only describe in markdown
    d. Use random coding
    Answer: b. Use schematic diagrams and workflow visualizationneptune​
  37. What is the function of “nbconvert” in Jupyter?
    a. Install packages
    b. Convert notebooks to various formats
    c. Run scripts only
    d. Hide data
    Answer: b. Convert notebooks to various formatsreddit+1​
  38. Versioning notebooks allows you to:
    a. Monitor code changes over time
    b. Increase notebook size
    c. Remove test cases
    d. Reduce collaboration
    Answer: a. Monitor code changes over timesanfoundry+1​
  39. What is one way to ensure backups of your workbooks?
    a. Use local-only storage
    b. Regularly sync with cloud storage
    c. Do not save
    d. Print all outputs
    Answer: b. Regularly sync with cloud storagedatabricks+1​
  40. Which notebook feature helps illustrate data relationships?
    a. Text cell
    b. Visualization libraries
    c. Simple output cell
    d. Audio output
    Answer: b. Visualization librariesneptune+1​
  41. Why is consistent code style vital in workbooks?
    a. Slows down analysis
    b. Increases accessibility and teamwork
    c. Uses more comments
    d. Increases errors
    Answer: b. Increases accessibility and teamworkdatabricks+1​
  42. Before archiving a workbook, which step is best?
    a. Delete all comments
    b. Clear all outputs and add final documentation
    c. Add random text
    d. Merge with others
    Answer: b. Clear all outputs and add final documentationneptune+1​
  43. How can hidden cells benefit a published notebook?
    a. Decrease transparency
    b. Hide irrelevant code for audience focus
    c. Reduce file size
    d. Increase error rates
    Answer: b. Hide irrelevant code for audience focusreddit​
  44. What helps users rerun a notebook from scratch?
    a. Shuffled cell order
    b. Sequential, clean cell ordering without dependency errors
    c. Skipped import cells
    d. Cells with missing code
    Answer: b. Sequential, clean cell ordering without dependency errorsdasca+1​
  45. What is the impact of messy workbook directories?
    a. Increases productivity
    b. Reduces findability and slows collaboration
    c. Promotes teamwork
    d. No impact
    Answer: b. Reduces findability and slows collaborationreddit+1​
  46. Which method helps ensure sensitive data is not exposed when sharing a workbook?
    a. Replace with dummy/sample data before sharing
    b. Ignore the data
    c. Remove all code
    d. Convert to PDF
    Answer: a. Replace with dummy/sample data before sharinglearn.microsoft​
  47. What should you do if a notebook becomes unmanageably large?
    a. Ignore changes
    b. Split into logical sub-notebooks
    c. Delete all output
    d. Add more code
    Answer: b. Split into logical sub-notebooksdasca+1​
  48. What is a common sign of poor workbook management?
    a. Well-labeled sections
    b. Frequent crashes and confusion
    c. Regular versioning
    d. Good documentation
    Answer: b. Frequent crashes and confusionneptune​
  49. Why use comments within code cells?
    a. For fun only
    b. To clarify logic and intent for self and others
    c. Standardizes outputs
    d. Increases code volume
    Answer: b. To clarify logic and intent for self and othersneptune+1​
  50. What does exporting a workbook using “File > Download as” NOT support by default?
    a. .ipynb
    b. .pdf
    c. .docx
    d. .html
    Answer: c. .docxreddit+1​
  1. https://www.dasca.org/world-of-data-science/article/master-data-science-with-these-best-practices-for-jupyter-notebook
  2. https://www.reddit.com/r/datascience/comments/17y72e7/ds_professionalism_notebook_best_practices/
  3. https://neptune.ai/blog/best-practices-for-data-science-project-workflows-and-file-organizations
  4. https://www.sanfoundry.com/1000-data-science-questions-answers/
  5. https://www.datamation.com/big-data/data-science-best-practices/
  6. https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/cloud-scale-analytics/best-practices/data-science-best-practices
  7. https://www.databricks.com/resources/guide/data-scientists
  8. https://www.gyansetu.in/blog/data-science-objective-type-mcq-quiz-interview-preparation/
  9. https://www.scribd.com/document/856379688/Data-Science-100-MCQs
  10. https://www.gyansetu.in/blog/data-analytics-mcq-quiz-interview-preparation/
  11. https://scholarexpress.com/multiple-choice-questions-on-data-science/
  12. https://helion.pl/pobierz-fragment/mcq-for-data-science-users-dr-dhananjay-bisen-dr-neeraj-sahu-dr-brijesh,e_42hn/pdf
  13. https://books.google.com/books/about/MCQ_for_Data_Science_Users.html?id=AiwREQAAQBAJ
  14. https://testbook.com/objective-questions/mcq-on-data-analytics–5fb547866a5f67e73384f18c
  15. https://www.interviewbit.com/data-science-mcq/
  16. https://interviewkickstart.com/blogs/articles/data-science-mcq-answers
  17. https://www.scribd.com/document/705848941/Data-Science-MCQ-Questions-and-Answer-PDF
  18. https://www.youtube.com/watch?v=_4SdjnCQ6LE
  19. https://www.includehelp.com/mcq/data-science-mcqs.aspx
  20. https://testbook.com/objective-questions/mcq-on-data-analysis–5eea6a0d39140f30f369e1bb

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