Python csv Module

CSV (Comma-Separated Values) files are a common file format for storing tabular data.

CSV files consist of plain text, where each row represents a row of data in the table, and each column is separated by a comma (or other delimiter).

CSV files are commonly used for data exchange because they are simple and easy to handle.

Python provides a built-in csv module for reading and writing CSV files. This module simplifies the process of handling CSV files, allowing developers to easily manipulate tabular data.

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1. Reading CSV Files

To read a CSV file, you can use the csv.reader object. Here is a simple example:

Example

import csv

# Open the CSV file
with open('data.csv', mode='r', encoding='utf-8') as file:
    # Create a csv.reader object
    csv_reader = csv.reader(file)
    
    # Read data row by row
    for row in csv_reader:
        print(row)

Code Explanation:

• open('data.csv', mode='r', encoding='utf-8'): Opens the file named data.csv in read-only mode, specifying the encoding as UTF-8.
• csv.reader(file): Creates a csv.reader object for reading the file content.
• for row in csv_reader: Reads the file content row by row, with each row of data parsed as a list.

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2. Writing CSV Files

To write a CSV file, you can use the csv.writer object. Here is an example:

Example

import csv

# Data to write
data = [
    ['Name', 'Age', 'City'],
    ['Alice', '30', 'New York'],
    ['Bob', '25', 'Los Angeles']
]

# Open the CSV file
with open('output.csv', mode='w', encoding='utf-8', newline='') as file:
    # Create a csv.writer object
    csv_writer = csv.writer(file)
    
    # Write data
    for row in data:
        csv_writer.writerow(row)

Code Explanation:

• open('output.csv', mode='w', encoding='utf-8', newline=''): Opens the file named output.csv in write mode, specifying the encoding as UTF-8. newline='' is used to avoid blank lines on Windows systems.
• csv.writer(file): Creates a csv.writer object for writing file content.
• csv_writer.writerow(row): Writes each row of data to the file.

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3. Reading and Writing CSV Files Using Dictionaries

The csv module also provides the DictReader and DictWriter classes, which can parse each row of a CSV file as a dictionary, or write dictionaries to a CSV file.

Reading CSV Files with DictReader:

Example

import csv

with open('data.csv', mode='r', encoding='utf-8') as file:
    csv_dict_reader = csv.DictReader(file)
    
    for row in csv_dict_reader:
        print(row)

Writing CSV Files with DictWriter:

Example

import csv

data = [
    {'Name': 'Alice', 'Age': '30', 'City': 'New York'},
    {'Name': 'Bob', 'Age': '25', 'City': 'Los Angeles'}
]

with open('output.csv', mode='w', encoding='utf-8', newline='') as file:
    fieldnames = ['Name', 'Age', 'City']
    csv_dict_writer = csv.DictWriter(file, fieldnames=fieldnames)
    
    # Write the header
    csv_dict_writer.writeheader()
    
    # Write data
    for row in data:
        csv_dict_writer.writerow(row)

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Common Attributes and Methods

Core Methods of the csv Module

Method	Description	Example
csv.reader()	Read CSV data from a file object	reader = csv.reader(file)
csv.writer()	Write data to a CSV file	writer = csv.writer(file)
csv.DictReader()	Read CSV rows as dictionaries (with headers)	dict_reader = csv.DictReader(file)
csv.DictWriter()	Write dictionaries to a CSV file (field names required)	dict_writer = csv.DictWriter(file, fieldnames)
csv.register_dialect()	Register a custom CSV format (e.g., delimiter)	`csv.register_dialect(‘mydialect’, delimiter=’
csv.unregister_dialect()	Unregister a registered dialect	csv.unregister_dialect('mydialect')
csv.list_dialects()	List all registered dialects	print(csv.list_dialects())

Common Methods of csv.reader and csv.writer Objects

Method	Description	Applicable Object
__next__()	Iteratively read the next row (or use a for loop)	reader
writerow(row)	Write a single row of data	writer
writerows(rows)	Write multiple rows of data (list of lists)	writer

csv.DictReader and csv.DictWriter Object Features

Feature/Method	Description	Example
fieldnames	List of field names (DictReader auto-obtains from the first row)	dict_reader.fieldnames
writeheader()	Write the header row (DictWriter only)	dict_writer.writeheader()

Common Parameter Descriptions

Parameter	Description	Example Value	Applicable Method
delimiter	Field delimiter	',' (default), '\t'	reader/writer
quotechar	Quote character (wraps special fields)	'"' (default)	reader/writer
quoting	Quoting rule	csv.QUOTE_ALL (quote all)	reader/writer
skipinitialspace	Ignore spaces after delimiter	True/False	reader
lineterminator	Line terminator	'\r\n' (default)	writer
dialect	Predefined dialect name	'excel' (default)	All methods

Examples

1. Reading a CSV File

Example

import csv

with open('data.csv', 'r') as file:
    reader = csv.reader(file, delimiter=',')
    for row in reader:
        print(row)  # Each row is a list

2. Writing a CSV File

Example

data = [['Name', 'Age'], ['Alice', 25], ['Bob', 30]]

with open('output.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerows(data)  # Write multiple rows

3. Using DictReader and DictWriter (with Headers)

Example

# Reading
with open('data.csv', 'r') as file:
    dict_reader = csv.DictReader(file)
    for row in dict_reader:
        print(row['Name'], row['Age'])  # Access by field name

# Writing
fieldnames = ['Name', 'Age']
with open('output.csv', 'w', newline='') as file:
    dict_writer = csv.DictWriter(file, fieldnames=fieldnames)
    dict_writer.writeheader()  # Write the header
    dict_writer.writerow({'Name': 'Alice', 'Age': 25})

4. Custom Dialect (e.g., Handling TSV Files)

Example

csv.register_dialect('tsv', delimiter='\t', quoting=csv.QUOTE_NONE)

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