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Working with CSV files in Python - Cheat Sheet & Quick Revision

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Recall & Review
beginner
What is a CSV file?
A CSV (Comma-Separated Values) file is a simple text file that stores tabular data. Each line is a row, and columns are separated by commas.
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beginner
Which Python module is commonly used to work with CSV files?
The built-in csv module is used to read from and write to CSV files easily.
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beginner
How do you read a CSV file using Python's csv module?
You open the file with open(), then create a csv.reader object to loop through rows.
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beginner
How do you write data to a CSV file in Python?
Open the file in write mode with open(), create a csv.writer object, then use writer.writerow() to add rows.
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beginner
Why should you use with open() when working with files?
Using with open() automatically closes the file after the block ends, preventing file corruption or leaks.
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What does each line in a CSV file represent?
AA single character
BA column of data
CA file header
DA row of data
Which Python function is used to open a CSV file for reading?
Afile.open()
Bcsv.open()
Copen()
Dread_csv()
What method writes a single row to a CSV file using csv.writer?
Awriterow()
Bwrite()
Cwriteline()
Dwritecsv()
Why is it important to close a file after working with it?
ATo save changes and free system resources
BTo delete the file
CTo rename the file
DTo open it again
Which delimiter is most commonly used in CSV files?
ASemicolon
BComma
CTab
DSpace
Explain how to read data from a CSV file in Python using the csv module.
Think about opening the file and then reading each line as a list.
You got /4 concepts.
    Describe the steps to write multiple rows of data to a CSV file in Python.
    Remember to open the file first, then write rows one by one or all at once.
    You got /4 concepts.

      Practice

      (1/5)
      1. What does the Python csv.reader function do when working with CSV files?
      easy
      A. Reads the CSV file and returns each row as a list of values
      B. Writes data to a CSV file
      C. Deletes a CSV file
      D. Converts CSV data into JSON format

      Solution

      1. Step 1: Understand the purpose of csv.reader

        The csv.reader function reads CSV files and returns each row as a list of strings representing the columns.
      2. Step 2: Differentiate from other CSV functions

        Functions like writing or deleting files are not done by csv.reader. It only reads and parses rows.
      3. Final Answer:

        Reads the CSV file and returns each row as a list of values -> Option A
      4. Quick Check:

        csv.reader reads rows as lists [OK]
      Hint: Remember: reader reads rows as lists [OK]
      Common Mistakes:
      • Confusing reader with writer
      • Thinking it deletes files
      • Assuming it converts formats
      2. Which of the following is the correct way to open a CSV file for reading in Python?
      easy
      A. open('data.csv', 'a')
      B. open('data.csv', 'w')
      C. open('data.csv', 'r')
      D. open('data.csv', 'x')

      Solution

      1. Step 1: Understand file modes in Python

        The mode 'r' means open for reading, which is needed to read a CSV file.
      2. Step 2: Check other modes

        'w' is for writing (overwrites), 'a' is for appending, and 'x' is for creating a new file. None are for reading existing files.
      3. Final Answer:

        open('data.csv', 'r') -> Option C
      4. Quick Check:

        Use 'r' mode to read files [OK]
      Hint: Use 'r' mode to read files [OK]
      Common Mistakes:
      • Using 'w' which overwrites file
      • Using 'a' which appends data
      • Using 'x' which fails if file exists
      3. What will be the output of this code snippet?
      import csv
      with open('data.csv', 'w', newline='') as f:
          writer = csv.writer(f)
          writer.writerow(['Name', 'Age'])
          writer.writerow(['Alice', '30'])
      
      with open('data.csv', 'r') as f:
          reader = csv.reader(f)
          rows = list(reader)
      print(rows)
      medium
      A. ['Name', 'Age', 'Alice', '30']
      B. SyntaxError
      C. [['Name, Age'], ['Alice, 30']]
      D. [['Name', 'Age'], ['Alice', '30']]

      Solution

      1. Step 1: Writing rows with csv.writer

        The code writes two rows: header ['Name', 'Age'] and data ['Alice', '30'] as lists.
      2. Step 2: Reading rows with csv.reader

        Reading back returns a list of lists, each inner list is a row split by commas.
      3. Final Answer:

        [['Name', 'Age'], ['Alice', '30']] -> Option D
      4. Quick Check:

        csv.reader returns list of lists [OK]
      Hint: csv.reader returns list of lists, not flat list [OK]
      Common Mistakes:
      • Expecting a flat list instead of list of lists
      • Thinking rows are single strings
      • Syntax errors from missing newline='' in open
      4. Identify the error in this code that reads a CSV file:
      import csv
      with open('data.csv', 'r') as f:
          reader = csv.reader(f)
          for row in reader:
          print(row)
      medium
      A. csv.reader cannot be used with 'with' statement
      B. Indentation error in the for loop body
      C. File mode should be 'w' instead of 'r'
      D. Missing import statement

      Solution

      1. Step 1: Check indentation inside the for loop

        The print statement must be indented inside the for loop to run for each row.
      2. Step 2: Verify other parts

        Import is present, file mode 'r' is correct for reading, and csv.reader works with 'with' statement.
      3. Final Answer:

        Indentation error in the for loop body -> Option B
      4. Quick Check:

        Indent loop body correctly [OK]
      Hint: Indent inside loops to avoid errors [OK]
      Common Mistakes:
      • Not indenting loop body
      • Changing file mode incorrectly
      • Thinking csv.reader can't be used with 'with'
      5. You have a CSV file with columns 'Name', 'Age', and 'City'. You want to read it and create a dictionary where keys are names and values are ages (as integers). Which code snippet correctly does this?
      hard
      A. import csv with open('data.csv', 'r') as f: reader = csv.DictReader(f) result = {row['Name']: int(row['Age']) for row in reader} print(result)
      B. import csv with open('data.csv', 'r') as f: reader = csv.reader(f) result = {row[0]: int(row[1]) for row in reader} print(result)
      C. import csv with open('data.csv', 'r') as f: reader = csv.DictReader(f) result = {row['Age']: row['Name'] for row in reader} print(result)
      D. import csv with open('data.csv', 'r') as f: reader = csv.reader(f) result = {int(row[1]): row[0] for row in reader} print(result)

      Solution

      1. Step 1: Use csv.DictReader to access columns by name

        DictReader reads rows as dictionaries, so we can use keys like 'Name' and 'Age'.
      2. Step 2: Create dictionary with names as keys and ages as integer values

        The comprehension uses row['Name'] as key and converts row['Age'] to int for value.
      3. Final Answer:

        import csv with open('data.csv', 'r') as f: reader = csv.DictReader(f) result = {row['Name']: int(row['Age']) for row in reader} print(result) -> Option A
      4. Quick Check:

        DictReader + dict comprehension with int conversion [OK]
      Hint: Use DictReader and convert age to int in comprehension [OK]
      Common Mistakes:
      • Using csv.reader without column names
      • Swapping keys and values
      • Not converting age to int