MCQs

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Overall MCQs for Reference

Which data preprocessing step is essential before applying filtering techniques to a dataset?
a. Data visualization
b. Data cleaning
c. Model selection
d. Data labeling
Answer: b. Data cleaningsanfoundry
What is the main goal of data filtering in data science?
a. To reduce memory usage
b. To remove irrelevant or noisy data
c. To improve computation speed only
d. To increase data redundancy
Answer: b. To remove irrelevant or noisy datasanfoundry
Which method is commonly used for filtering outliers in a numerical dataset?
a. One-hot encoding
b. Z-score thresholding
c. Bag-of-words encoding
d. Data aggregation
Answer: b. Z-score thresholdingsanfoundry
What does a Boolean filter operate on in tabular data?
a. Only numeric columns
b. Conditional logic (True/False)
c. Time-stamp columns
d. List indexes
Answer: b. Conditional logic (True/False)sanfoundry
Which filtering technique is best for removing duplicate records in a database?
a. Row selection
b. Deduplication
c. Data normalization
d. Data transformation
Answer: b. Deduplicationsanfoundry
How can missing values be filtered from a DataFrame in Python using pandas?
a. Using the dropna() function
b. Using the fillna() function
c. Using the merge() function
d. Using the groupby() function
Answer: a. Using the dropna() functionsanfoundry
Which filter is effective for categorical data in SQL queries?
a. BETWEEN
b. CASE WHEN
c. WHERE
d. LIKE
Answer: c. WHEREsanfoundry
What does the ‘loc’ function in pandas primarily filter by?
a. Column names
b. Index labels
c. Data types
d. Unique values
Answer: b. Index labelssanfoundry
What type of filter would you apply to remove records with missing or null values in SQL?
a. WHERE column = NULL
b. WHERE column NOT NULL
c. GROUP BY column
d. JOIN ON column
Answer: b. WHERE column NOT NULLsanfoundry
Which process involves selecting data within a specific range, such as ages 20–30?
a. Slicing
b. Binning
c. Range filtering
d. Encoding
Answer: c. Range filteringsanfoundry
In Excel, which feature allows users to quickly filter a table to view rows that meet certain conditions?
a. PivotTable
b. Named Range
c. AutoFilter
d. Conditional Formatting
Answer: c. AutoFilterscribd
What parameter can be used in the pandas read_csv() function to filter specific columns?
a. usecols
b. skiprows
c. delimiter
d. header
Answer: a. usecolssanfoundry
Which type of filter in image processing helps reduce noise by averaging pixel values?
a. High-pass filter
b. Median filter
c. Butterworth filter
d. Mean filter
Answer: d. Mean filtersanfoundry
What is a rolling filter used for in time series analysis?
a. Normalizing data
b. Calculating moving averages
c. Encoding time stamps
d. Splitting data
Answer: b. Calculating moving averagessanfoundry
Which filtering operation can be accomplished using ‘groupby’ in pandas?
a. Sorting rows
b. Aggregating subsets
c. Filling missing values
d. Data normalization
Answer: b. Aggregating subsetssanfoundry
What is the result of applying a filter that keeps only unique values in a list?
a. Sorted list
b. Normalized list
c. Deduplicated list
d. Encoded list
Answer: c. Deduplicated listsanfoundry
In machine learning, which type of feature selection uses correlation-based filtering?
a. Wrapper method
b. Embedded method
c. Filter method
d. Hybrid method
Answer: c. Filter methodinterviewkickstart
Which keyword is used in SQL for pattern-based data filtering?
a. IN
b. BETWEEN
c. LIKE
d. UNION
Answer: c. LIKEsanfoundry
What is the advantage of filtering data before visualization?
a. It reduces the need for storage space
b. It helps focus on relevant trends
c. It increases file size
d. It slows computation
Answer: b. It helps focus on relevant trendssanfoundry
Which pandas method can filter rows based on column values equal to a condition?
a. subset()
b. iloc[]
c. query()
d. resample()
Answer: c. query()sanfoundry
When filtering for top N values in a series, which pandas function is preferred?
a. max()
b. min()
c. nlargest()
d. sort()
Answer: c. nlargest()sanfoundry
In distributed big data environments, what operation is typically used for basic row-level filtering?
a. MapReduce filter
b. Window function
c. Lambda triggers
d. Cross join
Answer: a. MapReduce filterplacementpreparation
What type of filter in statistics keeps only values above a given percentile?
a. Lower bound filter
b. Upper quartile filter
c. Percentile filter
d. Median filter
Answer: c. Percentile filterinterviewkickstart
How can you filter strings in a Python list that contain a specific substring?
a. Using map()
b. Using filter() with lambda
c. Using reduce()
d. Using zip()
Answer: b. Using filter() with lambdasanfoundry
What would be an example of a real-time filtering application?
a. Batch data import
b. Email spam detection
c. Data archiving
d. Static data reporting
Answer: b. Email spam detectionsanfoundry
Which filter is preferred to exclude columns from a DataFrame in pandas?
a. drop()
b. keep()
c. select()
d. mask()
Answer: a. drop()sanfoundry
Filtering with “AND” logic in SQL requires which structure?
a. ORDER BY clause
b. HAVING clause
c. WHERE clause with AND
d. JOIN clause
Answer: c. WHERE clause with ANDsanfoundry
Which Python library provides efficient methods for large-scale data filtering?
a. matplotlib
b. numpy
c. pandas
d. seaborn
Answer: c. pandassanfoundry
What technique can be used to remove high-frequency noise in signal processing?
a. Low-pass filter
b. High-pass filter
c. Notch filter
d. Band-stop filter
Answer: a. Low-pass filtertestbook
To filter data entries based on a complex calculated field, which tool is suitable?
a. Excel Sort
b. SQL HAVING clause
c. Text Editor
d. Clipboard
Answer: b. SQL HAVING clausesanfoundry
In Power BI, what visual can be used for interactive filtering?
a. Timeline
b. Slicer
c. Card
d. Table
Answer: b. Slicergyansetu
Which logical filter would best identify rows where two conditions are met in Python using pandas?
a. &
b. |
c. ^
d. %
Answer: a. &sanfoundry
What is the first recommended step when filtering a massive unstructured dataset?
a. Data summarization
b. Data ingestion
c. Data cleansing
d. Feature generation
Answer: c. Data cleansingsanfoundry
What SQL clause is commonly used to filter grouped data after aggregation?
a. WHERE
b. HAVING
c. SELECT
d. LIMIT
Answer: b. HAVINGsanfoundry
Which function filters data based on row index in pandas?
a. iloc[]
b. groupby()
c. melt()
d. pivot()
Answer: a. iloc[]sanfoundry
A filter based on regular expressions in Python uses which module?
a. collections
b. re
c. math
d. sys
Answer: b. resanfoundry
When filtering dates in time-series data, which pandas function is commonly used?
a. date_range()
b. to_datetime()
c. between_time()
d. copy()
Answer: c. between_time()sanfoundry
Which Excel filter option allows filtering based on customized criteria?
a. Quick Filter
b. Advanced Filter
c. List Filter
d. Formula Filter
Answer: b. Advanced Filterscribd
In Spark SQL, what is the function for filtering rows?
a. filter()
b. sort()
c. count()
d. collect()
Answer: a. filter()sanfoundry
What tool is often used to filter streaming data in a big data pipeline?
a. DataLake
b. Kafka Streams
c. DataFrames
d. Pivot Tables
Answer: b. Kafka Streamssanfoundry
In SQL, which operator filters values belonging to a specific set?
a. WHERE … LIKE …
b. WHERE … IN (…)
c. WHERE … BETWEEN … AND …
d. WHERE … = …
Answer: b. WHERE … IN (…)sanfoundry
What is the output of filtering a DataFrame with a mask of True/False values?
a. Only rows where mask is True remain
b. Only columns remain
c. All values remain
d. The index is reset
Answer: a. Only rows where mask is True remainsanfoundry
What is a use-case for filtered data in machine learning training?
a. Reduces overfitting
b. Increases redundancy
c. Adds random noise
d. Increases bias
Answer: a. Reduces overfittingsanfoundry
If filtering is applied after sorting data, what is the possible effect?
a. No effect
b. Efficient querying
c. Loss of sorting
d. Increased null values
Answer: b. Efficient queryingsanfoundry
Filtering by range in SQL is done using which operator?
a. LIKE
b. IN
c. BETWEEN
d. EXISTS
Answer: c. BETWEENsanfoundry
Which method can filter records with non-unique values in SQL?
a. HAVING COUNT() > 1
b. GROUP BY only
c. INSERT INTO
d. WHERE NOT NULL
Answer: a. HAVING COUNT() > 1sanfoundry
What happens if no filtering is applied before an analysis?
a. Potential bias and noise remain
b. Data becomes normalized
c. Faster computation always
d. All data errors are eliminated
Answer: a. Potential bias and noise remainsanfoundry
What is a limitation of excessive filtering in a dataset?
a. Increased noise
b. Loss of valuable information
c. Enhances trends
d. Reduces sparsity
Answer: b. Loss of valuable informationsanfoundry
Using a Boolean mask to filter a NumPy array outputs:
a. Only values where the mask is False
b. Only values where the mask is True
c. Entire array unchanged
d. Only unique elements
Answer: b. Only values where the mask is Truesanfoundry
What is the recommended approach to filter sensitive information before data sharing?
a. Data normalization
b. Data masking/redaction
c. Feature scaling
d. Encoding
Answer: b. Data masking/redactionsanfoundry

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