


How to use the csv module to read and write CSV files in Python 2.x
How to use the csv module to read and write CSV files in Python 2.x
Introduction:
CSV (Comma Separated Values) is a common file format used to store and exchange data . Python's csv module provides an easy way to read and write CSV files. This article will introduce how to use the csv module to read and write CSV files in Python 2.x, and provide corresponding code examples.
1. Reading CSV files
To read CSV files, you first need to import the csv module. Then, read the contents of the CSV file by opening the file and creating a csv.reader object.
Code example:
import csv # 打开CSV文件 with open('data.csv', 'r') as file: # 创建csv.reader对象 reader = csv.reader(file) # 读取文件内容 for row in reader: # 打印每一行数据 print(row)
In the above code, we use with open('data.csv', 'r') as file
to open the CSV file and create A csv.reader object. We can then read the contents of the file line by line by looping over the csv.reader object. The data of each row is returned in the form of a list, and we can process each row accordingly.
2. Write CSV file
To write data into a CSV file, you also need to import the csv module first. Then, write the CSV file by opening the file and creating a csv.writer object.
Code example:
import csv # 要写入的数据 data = [ ['Name', 'Age', 'Gender'], ['Alice', '20', 'Female'], ['Bob', '25', 'Male'], ['Charlie', '30', 'Male'] ] # 打开CSV文件 with open('data.csv', 'w') as file: # 创建csv.writer对象 writer = csv.writer(file) # 写入数据 for row in data: writer.writerow(row)
In the above code, we first define the data to be written to the CSV file, which is represented here by a list. Then, we open the CSV file using with open('data.csv', 'w') as file
and create a csv.writer object. We then iterate through the data and write each row of data to the file using the writer.writerow(row)
method.
3. Specify the delimiter
By default, the csv module uses commas as the delimiter. If the CSV file uses other characters as delimiters, this can be set by specifying the delimiter
parameter.
Code example:
import csv # 打开CSV文件,指定分隔符为分号 with open('data.csv', 'r') as file: reader = csv.reader(file, delimiter=';') for row in reader: print(row)
In the above code, we use the delimiter
parameter to set the delimiter to a semicolon. This way, when reading a CSV file, csv.reader will use semicolons as the delimiter for each row of data.
Summary:
This article describes how to use the csv module in Python 2.x to read and write CSV files, and provides corresponding code examples. When reading a CSV file, you need to create a csv.reader object and read the contents of the file line by line by iterating over the object. When writing a CSV file, you need to create a csv.writer object and use the writer.writerow(row)
method to write each row of data to the file. Additionally, we also covered how to set the delimiter by specifying the delimiter
parameter. The above method can help you use Python 2.x to process data in CSV files.
The above is the detailed content of How to use the csv module to read and write CSV files in Python 2.x. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

Atom editor mac version download
The most popular open source editor

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

SecLists
SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.