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Pythonprogramming~30 mins

Reading and writing CSV data in Python - Mini Project: Build & Apply

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Reading and writing CSV data
📖 Scenario: You work in a small bookstore. You have a list of books with their titles and prices. You want to save this list to a CSV file and then read it back to check the data.
🎯 Goal: Learn how to write a list of dictionaries to a CSV file and then read the CSV file back into a list of dictionaries using Python.
📋 What You'll Learn
Create a list of dictionaries with book data
Set the CSV filename in a variable
Write the list of dictionaries to a CSV file
Read the CSV file back and print the data
💡 Why This Matters
🌍 Real World
CSV files are a common way to store and share tabular data like product lists, contacts, or sales records.
💼 Career
Knowing how to read and write CSV files is important for data processing, reporting, and automation tasks in many jobs.
Progress0 / 4 steps
1
Create the book data list
Create a list called books with these exact dictionaries: {'title': 'Python Basics', 'price': '29.99'}, {'title': 'Data Science', 'price': '39.99'}, and {'title': 'Web Development', 'price': '24.99'}.
Python
Hint

Use square brackets [] to create a list and curly braces {} for dictionaries.

2
Set the CSV filename
Create a variable called filename and set it to the string 'books.csv'.
Python
Hint

Use a simple string assignment like filename = 'books.csv'.

3
Write the books list to the CSV file
Import the csv module. Use open(filename, 'w', newline='') to open the file for writing. Create a csv.DictWriter with fieldnames ['title', 'price']. Write the header and then write all rows from books.
Python
Hint

Remember to import csv and use DictWriter with the correct fieldnames.

4
Read the CSV file and print the data
Open the file filename for reading. Use csv.DictReader to read the rows. Convert the rows to a list called read_books. Print read_books.
Python
Hint

Use csv.DictReader and convert the reader to a list before printing.

Practice

(1/5)
1. What does the Python csv.reader function do when reading a CSV file?
easy
A. It deletes rows from the CSV file.
B. It reads the file and returns each row as a list of strings.
C. It converts CSV data into a dictionary automatically.
D. It writes data to a CSV file.

Solution

  1. Step 1: Understand csv.reader purpose

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

    Functions like csv.DictReader return dictionaries, and writing functions save data, not read it.
  3. Final Answer:

    It reads the file and returns each row as a list of strings. -> Option B
  4. Quick Check:

    csv.reader returns lists [OK]
Hint: csv.reader reads rows as lists, not dictionaries [OK]
Common Mistakes:
  • Confusing csv.reader with csv.DictReader
  • Thinking csv.reader writes data
  • Assuming it deletes or modifies files
2. Which of the following is the correct way to open a CSV file for writing in Python?
easy
A. open('file.csv', 'w', newline='')
B. open('file.csv', 'r')
C. open('file.csv', 'a', encoding='utf-8')
D. open('file.csv', 'rb')

Solution

  1. Step 1: Identify mode for writing CSV

    To write CSV files, open the file in write mode 'w' and use newline='' to prevent extra blank lines on Windows.
  2. Step 2: Check other options

    'r' is read mode, 'a' is append (valid but not asked), 'rb' is binary read mode (not for writing text CSV).
  3. Final Answer:

    open('file.csv', 'w', newline='') -> Option A
  4. Quick Check:

    Write mode with newline='' [OK]
Hint: Use 'w' mode with newline='' to write CSV files correctly [OK]
Common Mistakes:
  • Forgetting newline='' causes blank lines
  • Using 'r' mode when writing
  • Using binary mode for text CSV
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)
    for row in reader:
        print(row)
medium
A. ['Name', 'Age']\n['Alice', 30]
B. Name,Age\nAlice,30
C. ['Name', 'Age']\n['Alice', '30']
D. Error because of missing encoding

Solution

  1. Step 1: Writing rows with csv.writer

    The code writes two rows: header ['Name', 'Age'] and data ['Alice', 30]. Numbers are converted to strings when written.
  2. Step 2: Reading rows with csv.reader and printing

    Reading returns each row as a list of strings. print(row) shows repr with quotes: ['Name', 'Age'] and ['Alice', '30'].
  3. Final Answer:

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

    csv.writer writes lists, csv.reader reads lists [OK]
Hint: csv.reader returns lists of strings, print shows quotes around all elements [OK]
Common Mistakes:
  • Expecting printed rows as comma strings
  • Confusing string and integer types in output
  • Assuming encoding error without cause
4. Identify the error in this code that reads a CSV file:
import csv
with open('file.csv', 'r') as f:
    reader = csv.reader(f)
    for row in reader:
    print(row)
medium
A. Indentation error in the for loop
B. Missing import statement for csv module
C. File opened in wrong mode
D. csv.reader requires newline argument

Solution

  1. Step 1: Check code indentation

    The print statement inside the for loop must be indented to be part of the loop body.
  2. Step 2: Verify other parts

    Import is present, file mode 'r' is correct for reading, and newline argument is not needed for reading.
  3. Final Answer:

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

    Python requires correct indentation [OK]
Hint: Indent inside loops to avoid syntax errors [OK]
Common Mistakes:
  • Forgetting to indent inside loops
  • Thinking newline is needed for reading
  • Confusing file modes
5. You want to read a CSV file where the first row contains column names, and then write a new CSV file with only rows where the 'Age' column is greater than 25. Which approach is correct?
hard
A. Use csv.reader to read, skip first row manually, filter rows, then write with csv.writer.
B. Use csv.writer to read and write files directly without filtering.
C. Use csv.reader to read all rows, convert 'Age' to int, then write with csv.DictWriter without header.
D. Use csv.DictReader to read rows as dictionaries, filter by 'Age' key, then write with csv.DictWriter including header.

Solution

  1. Step 1: Choose reading method with headers

    csv.DictReader reads CSV rows as dictionaries using the first row as keys, making it easy to filter by column names like 'Age'.
  2. Step 2: Filter and write with headers

    Filter rows where 'Age' > 25, then write using csv.DictWriter with fieldnames to include headers properly.
  3. Final Answer:

    Use csv.DictReader to read rows as dictionaries, filter by 'Age' key, then write with csv.DictWriter including header. -> Option D
  4. Quick Check:

    DictReader + DictWriter for header and filtering [OK]
Hint: Use DictReader/DictWriter for header-based filtering [OK]
Common Mistakes:
  • Skipping header manually instead of using DictReader
  • Writing without headers causing missing columns
  • Using csv.writer without filtering logic