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Python CSV DictReader Quiz

Question 1

What does csv.DictReader(file) return for each row?

  • A list of strings
  • A dictionary using column names as keys
  • A single string
  • A tuple of values

Answer: 2 Type: single Time: 45 Explanation: csv.DictReader reads each CSV row as a dictionary, using the header row as keys.

Question 2

Why is dictionary-style access often clearer than index-based access in CSV files?

  • Because dictionaries are always faster
  • Because column names are more meaningful than numeric indexes
  • Because dictionaries remove missing values
  • Because dictionaries convert values to numbers automatically

Answer: 2 Type: single Time: 45 Explanation: Accessing columns by name, such as row["title"], is usually clearer and easier to maintain than using indexes.

Question 3

When using csv.DictReader, what type are CSV values read as?

  • Integers
  • Floats
  • Strings
  • Booleans

Answer: 3 Type: single Time: 45 Explanation: CSV values are still read as strings, so numeric conversion must be done manually when needed.

Question 4

Which of the following are used in this session?

  • csv.DictReader
  • key-based access like row["title"]
  • break for first-match search
  • pandas.DataFrame

Answer: 1,2,3 Type: multiple Time: 45 Explanation: This session focuses on csv.DictReader, key-based access, counters, loops, and break, not pandas.

Question 5

What does reader.fieldnames give you?

  • The first 5 rows
  • The list of column names
  • The missing values
  • The average of a column

Answer: 2 Type: single Time: 45 Explanation: reader.fieldnames returns the column names taken from the CSV header row.

Question 6

Why do we still use a counter with dictionary rows?

  • Because dictionaries cannot be printed
  • Because counting logic still uses loop + condition + counter
  • Because dictionaries only work with counters
  • Because counters convert strings to numbers

Answer: 2 Type: single Time: 45 Explanation: Even though access is by key, counting still depends on looping through rows and increasing a counter when a condition is true.

Question 7

What is the purpose of break when finding the first matching row?

  • It skips the header row
  • It stops the loop after the first match
  • It converts a row into a dictionary
  • It sorts the data

Answer: 2 Type: single Time: 45 Explanation: break stops the loop immediately once the first matching row is found.

Question 8

What is the difference between checking genres == "Action" and "Action" in genres?

  • They are always exactly the same
  • The first checks exact equality, while the second checks whether Action appears inside a longer string
  • The first is for numbers and the second is for text
  • The second only works with lists

Answer: 2 Type: single Time: 45 Explanation: Exact equality matches only Action, while in also matches values like Action, Adventure.

Question 9

Which of the following are valid tasks from this session?

  • Count how many movies are from the USA
  • Find the missing data point in an incomplete dataset
  • Replace missing years with researched values
  • Print only the first 5 data rows

Answer: 1,2,4 Type: multiple Time: 45 Explanation: Part 1 includes counting, first rows, exact and partial matches, and finding missing data in movies_incomplete. Replacing missing years belongs to Part 2.

Question 10

What is the time complexity of scanning the CSV row by row to find a match in the worst case?

  • O(1)
  • O(log n)
  • O(n)
  • O(n²)

Answer: 3 Type: single Time: 45 Explanation: In the worst case, the script may inspect every row once, so the time complexity is O(n).