Reading and writing CSV data in Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to open a CSV file for reading.

Python

import csv

with open('data.csv', [1]) as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

Drag options to blanks, or click blank then click option'

A'a'

B'w'

C'r'

D'x'

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'w' which opens the file for writing and erases content.

Using 'a' which opens the file for appending, not reading.

The mode 'r' opens the file for reading, which is needed to read CSV data.

2fill in blank

medium

Complete the code to write rows to a CSV file.

Python

import csv

with open('output.csv', 'w', newline=[1]) as file:
    writer = csv.writer(file)
    writer.writerow(['Name', 'Age'])
    writer.writerow(['Alice', 30])

Drag options to blanks, or click blank then click option'

A''

BTrue

CNone

D'\n'

Attempts:

3 left

💡 Hint

Common Mistakes

Setting newline to True which is invalid.

Using '\n' as a string which causes errors.

Setting newline to an empty string prevents extra blank lines on some systems when writing CSV files.

3fill in blank

hard

Fix the error in the code to read CSV data as dictionaries.

Python

import csv

with open('data.csv', 'r') as file:
    reader = csv.DictReader(file)
    for row in [1]:
        print(row['Name'])

Drag options to blanks, or click blank then click option'

Afile

Breader

Ccsv

DDictReader

Attempts:

3 left

💡 Hint

Common Mistakes

Trying to loop over 'file' which is the file object, not the CSV reader.

Using 'csv' or 'DictReader' which are modules or classes, not iterators.

The variable 'reader' is the iterator over CSV rows as dictionaries.

4fill in blank

hard

Fill both blanks to create a dictionary from CSV rows where age is over 25.

Python

import csv

with open('people.csv', 'r') as file:
    reader = csv.DictReader(file)
    result = {row[[1]]: int(row[[2]]) for row in reader if int(row['Age']) > 25}
print(result)

Drag options to blanks, or click blank then click option'

A'Name'

B'Age'

C'City'

D'Country'

Attempts:

3 left

💡 Hint

Common Mistakes

Using fields that don't exist or are not relevant like 'City' or 'Country'.

Not converting age to int causing type errors.

The dictionary keys are the 'Name' field and values are the integer 'Age' field for rows where age is greater than 25.

5fill in blank

hard

Fill all three blanks to write a CSV file with headers and two rows.

Python

import csv

with open('newfile.csv', [1], newline=[2]) as file:
    writer = csv.[3](file)
    writer.writerow(['Product', 'Price'])
    writer.writerow(['Book', 12.99])
    writer.writerow(['Pen', 1.5])

Drag options to blanks, or click blank then click option'

A'w'

B''

Cwriter

Dwriterow

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong file mode like 'r' when writing.

Not setting newline properly causing extra blank lines.

Using csv.writerow instead of csv.writer to create the writer.

Open the file in write mode ('w'), set newline to empty string to avoid blank lines, and use csv.writer to create the writer object.

Practice

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