Working with CSV files in Python

Introduction

CSV files store data in a simple table format. Learning to work with them helps you read and save data easily.

You want to save a list of contacts from your program to a file.

You need to read data from a spreadsheet saved as CSV.

You want to share data with others in a simple text format.

You want to process data exported from a database or website.

You want to automate reading or writing data in a format many programs understand.

Syntax

Python

import csv

# Reading CSV file
with open('file.csv', newline='') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

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

Use newline='' when opening files to avoid extra blank lines on some systems.

csv.reader reads rows as lists of strings.

Examples

This reads each row from data.csv and prints it as a list.

Python

import csv

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

This writes two rows to output.csv: a header and one data row.

Python

import csv

with open('output.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(['City', 'Country'])
    writer.writerow(['Paris', 'France'])

DictReader reads rows as dictionaries using the header row as keys.

Python

import csv

with open('people.csv', newline='') as file:
    reader = csv.DictReader(file)
    for row in reader:
        print(row['Name'], row['Age'])

DictWriter writes rows using dictionary keys matching the header fields.

Python

import csv

with open('people.csv', 'w', newline='') as file:
    fieldnames = ['Name', 'Age']
    writer = csv.DictWriter(file, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerow({'Name': 'Bob', 'Age': 25})

Sample Program

This program first writes two rows of data to sample.csv. Then it reads the file and prints each row as a list.

Python

import csv

# Write sample data to CSV
with open('sample.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(['Name', 'Score'])
    writer.writerow(['Alice', 85])
    writer.writerow(['Bob', 90])

# Read and print the CSV data
with open('sample.csv', newline='') as file:
    reader = csv.reader(file)
    for row in reader:
        print(row)

Important Notes

CSV files separate values by commas by default, but you can change the separator with the delimiter option.

Always close files or use with to handle files safely.

When reading, all data is read as text (strings). Convert to numbers if needed.

Summary

CSV files store data in rows and columns separated by commas.

Use Python's csv module to read and write CSV files easily.

Use csv.reader for simple lists and csv.DictReader for named columns.

Practice

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