Understanding CSV File Format: Line-by-line Parsing and Data Processing

# 1. Introduction to CSV Files
- 1.1 What is CSV File Format
- 1.2 Advantages and Uses of CSV Files

# 2. Parsing the Structure of a CSV File

#### 2.1 Basic Structure of a CSV File

CSV files are a common file format characterized by comma-separated values and are typically composed of rows and columns. Each row represents a record in the file, and each column corresponds to a field within that record. Fundamentally, a CSV file is a simple text file that uses commas or other delimiters to identify different data fields.

#### 2.2 The Relationship Between Columns and Rows

In a CSV file, each line of data generally contains the same number of fields, with fields separated by delimiters such as commas or semicolons. Each line constitutes a record, while each column represents a specific type of data.

#### 2.3 Handling Data Containing Special Characters

When a CSV file contains special characters (such as commas, quotes, etc.), fields can be enclosed in double quotes to ensure correct data identification. This allows fields to be accurately delimited by quotes during file parsing, preserving the accuracy and integrity of the data.

# 3. Parsing CSV Files Line by Line

Line-by-line parsing is a common and efficient method for handling CSV files. By reading the CSV file line by line, data can be processed line by line, which is suitable for processing large CSV files or scenarios that require row-by-row data handling. This chapter will introduce how to parse CSV files line by line and demonstrate the implementation with Python code.

#### 3.1 Methods for Reading CSV Files Line by Line

Reading a CSV file line by line can usually be achieved by opening the file, reading each line, and parsing the data line by line. This approach avoids loading the entire file at once, making it suitable for handling large data files, conserving memory, and improving efficiency.

#### 3.2 Implementing Line-by-Line Parsing Using Python Code

Below is a Python example code that demonstrates how to read and parse a CSV file line by line:

import csv

# Open the CSV file
with open('data.csv', mode='r') as ***
     ***
     ***
     ***
         ***
         ***

#### 3.3 Error Handling and Exception Management

When parsing CSV files line by line, it is essential to consider error handling and exception management. For example, situations such as the file not existing, the file being corrupted, or data formatting errors can all trigger exceptions. When processing data, it is advisable to use try-except statements to catch exceptions and handle them appropriately to ensure the stability and reliability of the program.

With the above example code, readers can understand how to parse CSV files line by line using Python and how to expand and optimize the code for specific requirements in actual development.

# 4. Data Processing and Cleaning

Data processing and cleaning are crucial when handling CSV files. This chapter will cover how to perform data processing and cleaning on CSV files, including data splitting and extraction, data type conversion and formatting, and handling missing values.

#### 4.1 Data Spl