MCQs

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Overall MCQs for Reference

Which file format is most commonly used for exchanging tabular data between machine learning platforms?
a. PDF
b. TXT
c. CSV
d. HTML
Answer: c. CSVdatascientest+1
What does “CSV” stand for in data science?
a. Continuous Standard Values
b. Comma-Separated Values
c. Comma Standard Variable
d. Computed Sequential Vectors
Answer: b. Comma-Separated Valuesml-science+1
In a CSV file, what character is primarily used to separate values within a record?
a. Semicolon
b. Tab
c. Comma
d. Colon
Answer: c. Commadatascientest+1
Which line in a CSV file typically contains column names?
a. The first line
b. Any random line
c. The last line
d. No line has headers
Answer: a. The first lineml-science+1
Why are CSV files popular in machine learning workflows?
a. Ease of use and broad compatibility
b. File encryption by default
c. Support for embedded images
d. Multilingual support
Answer: a. Ease of use and broad compatibilityskillbee+1
When importing a CSV in Python using pandas, which function is widely used?
a. pandas.loadtxt()
b. pandas.read_csv()
c. pandas.import_csv()
d. pandas.csv_read()
Answer: b. pandas.read_csv()geeksforgeeks+1
Which of the following is NOT a benefit of using CSV files?
a. Human-readability
b. Wide software support
c. Built-in support for hierarchical data
d. Easy data exchange
Answer: c. Built-in support for hierarchical datadatascientest+1
How are records represented in a CSV file?
a. By semicolons
b. Each in a new line
c. Encoded as JSON objects
d. As XML nodes
Answer: b. Each in a new linewikipedia+1
Which Python standard library allows reading and writing CSV files?
a. json
b. sqlite
c. csv
d. xml
Answer: c. csvpythonforall+1
What is a potential issue when a data field in a CSV contains a comma?
a. Field splitting errors
b. Date mismatch
c. File corruption
d. Unicode errors
Answer: a. Field splitting errorsml-science+1
How are commas within a CSV field usually handled?
a. Ignored
b. Enclosed in quotation marks
c. Escaped with a slash
d. Removed
Answer: b. Enclosed in quotation marksdatascientest+1
Which of the following is NOT typically stored in CSV format?
a. Images
b. Numeric data
c. Textual attributes
d. Categorical variables
Answer: a. Imagesalooba+1
What makes CSV preferable for batch data processing in machine learning?
a. Simplicity and efficiency in parsing
b. Automatic data validation
c. Native graph storage
d. End-to-end encryption
Answer: a. Simplicity and efficiency in parsingskillbee+1
If a CSV contains NA values, what must often be done before using the data?
a. Encrypt the field
b. Handle missing values
c. Add more columns
d. Convert to JSON
Answer: b. Handle missing valuespaperspace+1
What extension do CSV files typically use?
a. .dat
b. .json
c. .csv
d. .xls
Answer: c. .csvwikipedia+1
A dataset is stored as:
a. Nested objects in JSON
b. Comma-delimited records in CSV
c. Inline HTML markup
d. Binary streams
Answer: b. Comma-delimited records in CSVml-science+1
Which delimiter is NOT standard for CSV files in machine learning?
a. Comma
b. Semicolon
c. Tab
d. Space
Answer: d. Spacedatascientest+1
What is a common reason to use csv.DictReader in Python?
a. Converts rows into dictionaries by column header
b. Exports to binary format
c. Randomly selects columns
d. Encrypts the CSV
Answer: a. Converts rows into dictionaries by column headerpythonforall
Which of the following best describes the data type of a CSV file?
a. Binary
b. Plaintext
c. Encrypted
d. Proprietary
Answer: b. Plaintextml-science+1
What is the impact of missing headers in a CSV?
a. Data processing confusion
b. Faster loading time
c. Enhanced security
d. More accurate data
Answer: a. Data processing confusiongeeksforgeeks+1
How are categorical variables often stored in CSV for machine learning?
a. As text labels
b. As embedded images
c. As JSON objects
d. As encrypted strings
Answer: a. As text labelsalooba+1
What issue can arise if newline characters appear inside CSV fields?
a. Misaligned records
b. Automatic correction
c. No impact on data
d. File recovery
Answer: a. Misaligned recordspythonforall+1
Which is a disadvantage of CSV for big data?
a. Efficient streaming
b. Lack of schema enforcement
c. High readability
d. Broad compatibility
Answer: b. Lack of schema enforcementalooba+1
In machine learning pipelines, CSV is frequently used for:
a. Model serialization
b. Feature dataset exchange
c. GPU acceleration
d. Visualization engines
Answer: b. Feature dataset exchangeskillbee+1
What approach should be used for a CSV file with inconsistent columns?
a. Validate and clean the file
b. Ignore extra columns
c. Automatically fill with zeros
d. Delete the file
Answer: a. Validate and clean the fileintegrate+1
What is the result of reading a CSV file in pandas without specifying column names when no headers exist?
a. Automatic integer column labels
b. Data loss
c. Type conversion
d. Encryption
Answer: a. Automatic integer column labelsrealpython+1
Which is NOT a preprocessing step for using CSVs in ML?
a. Data cleaning
b. Feature extraction
c. Image compression
d. Handling missing values
Answer: c. Image compressionkaggle+1
Encoding categorical variables in CSV is important because:
a. Machine learning algorithms require numerical inputs
b. To reduce file size
c. For file encryption
d. For visualization only
Answer: a. Machine learning algorithms require numerical inputskaggle+1
What method is commonly used to read large CSV files efficiently in Python?
a. Read all at once into memory
b. Chunk processing
c. Image streaming
d. Encrypted transfer
Answer: b. Chunk processingrealpython+1
What is the primary role of CSV in machine learning?
a. Data visualization only
b. Data storage and transfer
c. Modeling algorithms
d. Data encryption
Answer: b. Data storage and transferskillbee+1
How do you write an array to a CSV in Python?
a. Using csv.writer()
b. Using json.dump()
c. Using pandas.save()
d. Using plt.plot()
Answer: a. Using csv.writer()pythonforall
The most important requirement for a valid CSV in ML is:
a. All rows have same number of fields
b. Large file size
c. Compressed format
d. Column headers must be numeric
Answer: a. All rows have same number of fieldsintegrate+1
For which operation is CSV not ideal in machine learning?
a. Storing matrices
b. Relational data with multiple tables
c. Training data export
d. Simple numerical datasets
Answer: b. Relational data with multiple tablesalooba+1
What causes CSV parsing errors in ML tools?
a. Missing delimiters
b. Well-formed headers
c. Numeric data only
d. UTF-8 encoding
Answer: a. Missing delimitersintegrate+1
The CSV file format emerged in which decade?
a. 1960s
b. 1970s
c. 1980s
d. 1990s
Answer: b. 1970sdatascientest
If a field in a CSV contains both double quotes and commas, how should it be formatted?
a. Enclose field in double quotes and escape quotes within
b. Split the field into two
c. Ignore the commas
d. Remove the field
Answer: a. Enclose field in double quotes and escape quotes withindatascientest
Which is true about CSV support in data science platforms?
a. Readable by most platforms
b. Limited to Excel only
c. Proprietary software required
d. Not compatible with cloud storage
Answer: a. Readable by most platformsml-science+1
What is a typical use for CSV in model deployment?
a. Input/output of prediction data
b. Model version control
c. Hyperparameter tuning
d. Loss calculation only
Answer: a. Input/output of prediction dataskillbee+1
CSV is said to be:
a. Highly structured with enforced schema
b. Semi-structured and flexible
c. Binary-only
d. Not readable by humans
Answer: b. Semi-structured and flexibleskillbee+1
Which method allows automatic type inference when loading a CSV with pandas?
a. read_csv() with dtype=None
b. read_csv() with dtype=”object”
c. Manual conversion only
d. read_line() function
Answer: a. read_csv() with dtype=Nonegeeksforgeeks+1
Which value delimiter may cause compatibility issues in standard CSVs?
a. Comma
b. Tab
c. Semicolon
d. Pipe
Answer: d. Pipeml-science+1
When exporting data for machine learning competitions (e.g., Kaggle), which format is most accepted?
a. PNG
b. CSV
c. PPTX
d. YAML
Answer: b. CSVkaggle+1
In which situation does CSV become inefficient for machine learning?
a. Extremely large files with hundreds of millions of rows
b. Small tabular files
c. Pre-processed image data
d. Feature labeling
Answer: a. Extremely large files with hundreds of millions of rowsalooba+1
Which of the following is NOT a correct statement about CSV files?
a. CSV is self-describing
b. CSV supports nested objects
c. CSV is text-based
d. CSV can be edited in notepad
Answer: b. CSV supports nested objectsdatascientest+1
How should null (missing) values be represented in CSV for ML preprocessing?
a. Left blank or ‘NA’
b. Inserted with semicolons
c. Marked as binary
d. Encrypted
Answer: a. Left blank or ‘NA’paperspace+1
What happens if a CSV has inconsistent quoting?
a. Parsing errors may occur
b. Improved data speed
c. More accurate learning
d. File auto-correction
Answer: a. Parsing errors may occurintegrate+1
CSV files are platform-agnostic because:
a. Plain text and open format
b. Require proprietary extensions
c. Work only on Windows
d. Use binary encoding
Answer: a. Plain text and open formatwikipedia+1
Which command lists the number of rows in a CSV using pandas?
a. len(df)
b. df.row_count()
c. df.length()
d. count(df)
Answer: a. len(df)realpython+1
For which type of data would you NOT use CSV?
a. Relational database backup
b. Simple tabular data
c. Feature dataset for ML
d. Output predictions in model deployment
Answer: a. Relational database backupml-science+1
In automation pipelines using AI and ML, CSVs are:
a. Used for ETL operations and data flow
b. Used for video processing only
c. Not supported by cloud services
d. Never used for reporting
Answer: a. Used for ETL operations and data flowalooba+1

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